RSF Conference Series: Engineering and Technology

Responsibility of PSB (Photosynthetic Bacteria) and Chitosan on the Growth of Banana Lase (Musa acuminata L.)

Rina Srilestari — 2025-10-15

Banana (Musa spp.) is a crucial tropical fruit crop, but its cultivation faces significant challenges related to seedling availability and reliance on chemical fertilizers. Tissue culture provides a solution for large-scale seedling production. However, post-acclimatization remains a critical stage due to plant sensitivity to environmental stress. Sustainable alternatives, such as photosynthetic bacteria (PSB) and chitosan, have been suggested to improve growth and reduce chemical input dependency; however, their combined effects on banana remain underexplored. This study aimed to evaluate the influence of PSB and chitosan applications on the post-acclimatization growth of tissue-cultured Lase banana seedlings. A field experiment was conducted using a split-plot design, with PSB concentrations (10, 20, and 30 ml/L) as the main plots and chitosan concentrations (10, 15, and 20 ml/L) as subplots. Growth parameters were measured and analyzed using ANOVA at the 5% significance level, followed by DMRT for mean separation. The results revealed a significant interaction between PSB at 10 ml/L and chitosan at 10 ml/L, which produced the highest values for plant height and leaf number. This indicates that the synergistic application of PSB and chitosan enhances the early establishment of Lase banana seedlings after acclimatization. The findings contribute both practically and academically, demonstrating an effective strategy for reducing dependence on chemical fertilizers while improving seedling vigor and providing new insights into the integration of microbial inoculants and biopolymers in sustainable banana micropropagation.

Comparative Study Between Object-Based Image Analysis Using Mean Shift and Multiresolution Segmentation Algorithms for Green Open Space Identification: Case Study in Sleman Regency

Dessy Apriyanti — 2025-10-15

We elaborate on the critical importance of green open spaces in the context of urban sustainability. Public health is inextricably linked to the green open spaces in urban regions, as green spaces contribute to the ecological balance. In Indonesia, Green Open Space (GOS) is guided by Law No. 26 of 2007, which designates at least 30% of urban areas as GOS. However, tracking GOS is challenging due to urbanization and a lack of ground surveys. Remote sensing techniques and Object-Based Image Analysis (OBIA) may help solve this problem. We used high-resolution SPOT-7 imagery to determine GOS in Sleman Regency, Indonesia. The study also compares two OBIA segmentation algorithms, Mean Shift and Multiresolution Segmentation. The classification included city parks, rice fields, gardens, buildings, water bodies, and areas labeled as unclassified. Mean Shift segmentation, combined with SVM, achieved an accuracy of 81.25% and a Kappa index of 0.739. On the other hand, Multiresolution Segmentation with Nearest Neighbour attained 91.25% accuracy and a Kappa index of 0.878. Although these results indicate the superiority of Multiresolution Segmentation over Mean Shift in heterogeneous urban settings, there is a potential for the latter in fine-scale feature detection.

Influence of Volcanic Lithology on Soil Physical Properties in the Watugede Sub-watershed

Vinni Lovita — 2025-10-15

Lithology is one of the primary geological factors that control landform dynamics and soil development, particularly in tropical volcanic regions where weathering is intense. While previous research has emphasized the role of climate, slope, and land cover on soil properties and land degradation, studies that directly address the influence of lithological variation on soil physical properties through geomorphology at the sub-watershed scale remain limited. This study focuses on the Watugede Sub-watershed in Yogyakarta, Indonesia, which comprises three distinct volcanic formations: Kebobutak, Semilir, and Nglanggeran. These formations represent diverse lithological and geomorphological conditions. The objectives of this study are to (1) identify the lithological and geomorphological characteristics of the Watugede Sub-watershed, and (2) analyze the physical properties of soils that develop above each formation. Lithological data were obtained from geological maps and field surveys, while soil data were collected using purposive sampling at two depths (0–30 cm and 30–60 cm) with four replications. Laboratory analyses included bulk density, specific gravity, texture, permeability, maximum water content, and soil cohesion. The results show that lithological differences strongly influence soil physical characteristics and slope stability. Soils on the Kebobutak Formation have sandy to sandy loam textures with moderate cohesion and permeability, indicating relatively stable conditions but prone to local water saturation in fine tuff layers. The Semilir Formation produces heterogeneous soils with very fast permeability and low cohesion, reflecting susceptibility to erosion and slope deformation. The Nglanggeran Formation yields sandy loam soils with fast to moderate permeability and higher cohesion than those of Semilir, but instability persists on steep slopes due to intense fracturing and weathering. This study contributes to a deeper understanding of lithology–geomorphology–soil interactions in tropical volcanic watersheds, providing a scientific basis for watershed management and slope stability assessment.

Influence of Acetyl Content and Degree of Substitution on the Structural Properties of Cellulose Acetate for Pressure Retarded Osmosis

Retno Dwi Nyamiati — 2025-10-15

Cellulose acetate (CA) has been extensively utilized as a membrane material in pressure retarded osmosis (PRO) owing to its adjustable hydrophilicity, mechanical robustness, and chemical stability. Although earlier research has highlighted the role of acetylation in modifying the properties of CA, the specific impact of acetyl content and degree of substitution (DS) on structural features pertinent to PRO applications is still not well understood. The present study aims to fill this gap by systematically investigating CA derived from different lignocellulosic feedstocks. The purpose is to assess the relationship between acetyl content, DS, and the resulting structural properties of CA, and to determine the most appropriate biomass precursor for the development of PRO membranes. Cellulose was isolated from oil palm empty fruit bunches (EFB), rice straw, and waste paper, followed by acetylation. The obtained CA was characterized using Fourier-transform infrared spectroscopy (FTIR) to confirm esterification, while acetyl content and DS were quantitatively determined. Commercial CA served as the reference standard. The results demonstrated marked differences among the feedstocks. Waste paper yielded cellulose monoacetate (DS = 1.37; acetyl 26.9%), exhibiting incomplete acetylation with weak ester absorption. EFB produced cellulose diacetate (DS = 2.80; acetyl 43.0%), displaying spectral features comparable to commercial CA. Rice straw resulted in cellulose triacetate (DS = 3.91; acetyl 51.6%), indicating the most extensive substitution and superior structural quality. Higher DS was positively associated with enhanced thermal stability, reduced hydrophilicity, and improved mechanical performance, all of which are critical for PRO operation.

Photocatalytic Effect of Zinc Oxide on The Degradation of Crystal Violet Dye Waste Water under Visible Light

Renung Reningtyas — 2025-10-15

The textile industry is a major contributor to water pollution. Crystal Violet (CV) is a widely used cationic dye; however, it is toxic, difficult to degrade, and potentially carcinogenic, posing a significant threat to both aquatic ecosystems and human health. Zinc oxide (ZnO) is a semiconductor with a wide band gap, high chemical stability, and the ability to generate oxidative radicals capable of degrading complex organic compounds. This study aimed to examine the photocatalytic effect of ZnO on the photodegradation of Crystal Violet in a visible light-based reactor system. ZnO was synthesized using the sol-gel precipitation method, characterized using BET and a Particle Size Analyzer (PSA), and then tested for its photocatalytic activity. The test results showed that ZnO synthesized by a simple process has the potential to be an effective photocatalyst for sustainable textile wastewater treatment. Degradation CV using ZnO under 6 hours of visible light conditions could reach up to 70%.

You Only Look Once Version 11 (YOLOv11) Based Object Detection for 3D City Modeling: A Study in the Jatirejo Area

Ni Putu Atmelia Putri — 2025-10-15

Digital three-dimensional (3D) modeling has become an essential requirement in modern spatial mapping and visualization, as it can provide a more realistic and detailed representation of objects or areas. This study uses image segmentation techniques using YOLO v11, which automatically recognizes and separates objects, thereby increasing the accuracy of image extraction and accelerating the modeling process. With the help of software and the web, namely Roboflow, Google Colab, and QGIS. The results of this study show that the integration of image extraction algorithms, deep learning, and image segmentation based on YOLO v11 produces a more precise, efficient, and realistic 3D model. The Confusion Matrix shows that the segmentation results are perfectly detected at a rate of more than 85.64%, with the remaining segmentation not being perfectly detected, accounting for 9.23% and 5.13% of the undetected part. The calculation of the precision value of 95.94% indicates that the model rarely makes mistakes in predicting objects. The resulting Recall value is 87.58% and the F1 score is 91.57%. Thus, the use of AI-based technology and computer vision offers an innovative solution in accelerating the development of effective, accurate, and cost-effective digital 3D city models that can be used as local government data.

Robustness of Soil Phosphorus Availability, Nutrient Dynamics, and Shallot Vegetative Growth Through Arbuscular Mycorrhizal Fungi (AMF) Inoculation

Umi Munawaroh — 2025-10-15

Phosphorus (P) is an essential plant nutrient and one of the most limiting in natural habitats as well as in agricultural production worldwide. Here, we present the experiment between shallot crops, AMF inoculated and without inoculation, to examine the impacts of the AMF symbiosis on soil phosphorus availability, nutrient dynamics, growth, and biomass. We used a Randomized Complete Block Design (RCBD) with 5 (Five) replicates. The findings show that AMF enhances Phosphorus availability, total Potassium, and C-organic matter, while not affecting total Nitrogen in the soil. The application of mycorrhiza significantly enhanced soil phosphorus availability, increasing from 30.56 ppm in non-inoculated soils to 40.81 ppm with mycorrhizal treatment, equivalent to an improvement of approximately 33%. Furthermore, AMF inoculation has affected the growth and biomass of shallots in the vegetative stage. The results revealed a significant growth-promoting effect of mycorrhizal fungi, with plant height increasing by ~23.7% (from 38.60 to 47.70 cm) and biomass nearly doubling, showing an increase of ~75.2% (from 18.15 to 31.78 g). Therefore, the utilization of AMF in Shallot cultivation is important for nutrient dynamics and vegetative growth.

Hydrogeochemical Modeling of Mineral Processes in Hot Springs and Mine Waters

Ilham Firmansyah — 2025-10-15

Inventory of Cacao Diseases in Kulon Progo Regency

Aurelia Danadyaksa — 2025-10-15

Cocoa (Theobroma cacao L.) is a strategic plantation commodity that significantly contributes to Indonesia's national economy. However, national cocoa productivity has declined in recent years, mainly due to inadequate management of plant diseases. This study aims to profile and characterize the pathogenic microorganisms associated with disease symptoms and determine the effect of cultivation methods on the incidence of disease in cocoa plants in Kulon Progo Regency, Special Region of Yogyakarta. The research employed a field survey method with purposive sampling and a diagonal pattern to collect symptomatic plant samples. The result is the disease that appears in cacao plantations in Kulon Progo, including vascular strike dieback, black pod rot, and cocoa swollen shoot virus (CSSV), with a tendency for lower damage intensity on intensively managed plantations.

The Effect of a Mixture of Leaf Waste and Ash with a Bioactivator on Compost Characteristics and Corn Growth

Didi Saidi — 2025-10-15

This study aimed to analyze the characteristics of ash from waste combustion, the quality of compost made from leaf waste, ash, and various bioactivators, as well as their effects on corn growth. The research was conducted in two stages. The first stage focused on compost production using two factors: the proportion of leaf waste and ash (A0: 0% ash, A1: 5%, A2: 10%, A3: 15%, A4: 20%) and the type of bioactivator (B0: none, B1: EM4, B2: Stardec, B3: straw isolate, B4: Trichoderma). The second stage tested the resulting compost on corn plants using a completely randomized design with one factor and three replications. Data were analyzed using analysis of variance (5%) and the Duncan test (5%). The results showed that the combustion ash had varying qualities: the pH, NPK, Ca, Fe, and Zn contents met quality standards, while the organic carbon content was below the standard, and the C/N ratio exceeded it. Heavy metal Hg levels were below the limit, but Pb and Cd exceeded quality standards. The compost produced from a mixture of leaf litter, ash, and bioactivators also varied, with its pH, organic carbon, and total N+P+K content meeting the Indonesian National Standard (SNI) for organic fertilizer; however, the nitrogen and phosphorus contents were below the SNI requirements. Regarding corn growth, the highest plant height was observed in treatments with 5% ash and the Stardec bioactivator. In contrast, the lowest height was observed in compost without ash and with the Trichoderma bioactivator.

Integrating Remote Sensing and Field Observations for Karst Morphological Analysis: Evidence from Rongkop, Gunung Kidul

Utama P P — 2025-10-15

Incentive Mechanisms through Payments for Environmental Services in Sustainable Agriculture, Sleman, Indonesia

Farida Afriani Astuti — 2025-10-15

Food security is a strategic issue heavily influenced by the sustainability of agricultural land. In this context, Sleman Regency has established a Sustainable Food Agriculture Area (KP2B) through Regional Regulation Number 6 of 2020 on the Protection of Sustainable Food Agricultural Land (LP2B). This regulation mandates the provision of incentives to farmers of LP2B, although the Regent Draft Regulation (Raperbup) governing the technical mechanisms of incentives has not been ratified. Therefore, this research aimed to identify key parameters in calculating LP2B incentives as a form of implementing Payments for Environmental Services (PES). The method adopted was Interpretive Structural Modeling (ISM), which included seven experts from academia, government, farmers, and the private sector. The results showed that soil fertility, irrigation availability, and agricultural productivity were key parameters complementing each other. Soil fertility was the basic potential, irrigation was the main supporting factor, and productivity was the tangible output. These results confirmed that the LP2B incentive scheme was an effort to internalize the value of environmental services into public policy. Furthermore, PES-based incentives served as a strategic mechanism based on regulations to maintain regional food security and environmental quality.

GIS-Based Spatial ID3 Analysis for Cocoa Land Suitability

Andi Nurkholis — 2025-10-15

The decline in suitable cocoa land in Indonesia has led to reduced productivity and increased reliance on imports. This study addresses the gap for cocoa land suitability analysis by utilizing the Spatial ID3 algorithm, a method not previously applied in this region, to assess cocoa cultivation potential. A key contribution of this paper is the development of an interactive, web-based geographic information system tool that integrates spatial ID3 classification with mapping capabilities, providing decision-makers with a valuable tool for sustainable cocoa production and land management. The model used eight predictor variables, including soil, topography, and environmental factors, to generate 53 rules, which were then converted into interactive graphics. The tool consists of three main elements: an interactive Leaflet map for cocoa land suitability, detailed suitability classifications at the village level, and recommendations for five cocoa genotypes best suited to local conditions. Results indicate that the most significant area (231,018 ha) is classified as S3 (marginally suitable), followed by S2 (moderately suitable) with 16,443 ha. The unsuitable (N) land covers 49,253 ha, and the unclassified land accounts for 1,363 ha. No S1 (highly suitable) land was found, suggesting that ideal conditions may be absent in the region. This system equips decision-makers with evidence-based tools to prioritize sustainable cocoa production strategies, optimize land management in S2 zones, and implement adaptive interventions in S3 areas. Ultimately, this methodology supports sustainable agricultural development and aids Indonesia in its goal of cocoa self-sufficiency.

Isolation and Propagation of Methomyl-Degrading Bacteria from Pesticide-Polluted Land

Zulfa Fatmawati — 2025-10-15

Methomyl is a widely used carbamate pesticide in horticulture, valued for its broad-spectrum insecticidal properties and rapid action. Despite its efficacy in pest control, methomyl poses significant environmental and human health risks due to its persistence in soil and toxicity to non-target organisms. Residual methomyl can contaminate soil and water bodies, leading to bioaccumulation in ecosystems and potential adverse effects on human health. This study aimed to isolate and identify indigenous bacteria from shallot farm soils in Central Java, Indonesia, capable of utilizing methomyl as a carbon and energy source, thereby facilitating its biodegradation. Soil samples from methomyl-treated fields were collected and subjected to enrichment culture techniques using Minimal Salt Medium with varying methomyl concentrations to select for resistant and metabolizing bacteria. Four distinct bacterial isolates (RW, RC, RY, and RR) were recovered, showing morphological diversity and varied growth responses to methomyl exposure. Among these, isolates RW and RC exhibited superior adaptability and growth performance, with the filamentous isolate RC demonstrating the highest growth potential, indicative of its robust methomyl degradation capacity. These findings emphasize the promising role of native soil bacterial communities in bioremediation strategies to mitigate pesticide pollution. Further research is warranted to elucidate the metabolic pathways involved, quantify degradation efficiency, and assess the practical application potential of these isolates in contaminated environments.

Classification Of Merapi Volcano Images Based on HSV Color Feature Extraction and Local Binary Pattern Texture Feature Extraction Using The K-Nearest Neighbors Method

Awang Hendrianto Pratomo — 2025-10-15

The BPPTKG (Center for Volcanology and Geological Hazard Mitigation) routinely monitors Merapi Volcano’s activity through visual imagery captured with DSLR lenses at several observation posts. However, not all recorded imagery can be used for analysis due to frequent cloud or fog cover. This not only makes it difficult for experts to accurately monitor Merapi's condition but also reduces the efficiency of data storage capacity. To examine the application of HSV color feature extraction, LBP texture feature extraction, and the K-Nearest Neighbor method for classifying Merapi Volcano images based on appearance. The dataset used consists of Merapi Volcano images captured from the Tunggularum observation post between October 1st and 10th, 2023, categorized into six classes based on the volcano's appearance. Preprocessing steps include cropping, masking, and image sharpening. Classification was performed using the K-Nearest Neighbor method to obtain the classification results of Mount Merapi images. Based our result, the classification method using HSV and LBP using the K-Nearest Neighbor method was successfully performed. The optimal value of k was 1, achieving an accuracy of 95%, while the worst value of k was 9, with an accuracy of 87%.

Spatial Analysis of Water Infiltration Areas and Flood Risk in Yogyakarta City

Ismi P Cendikia — 2025-10-15

Yogyakarta City faces environmental problems due to the reduction of water catchment areas resulting from urbanization and changes in land use. This reduction can disrupt the hydrological cycle, leading to groundwater depletion and an increased risk of flooding and inundation. Using a Geographic Information System (GIS) approach, this research will map the water catchment potential. The data analysed included soil type, rainfall, land slope, land use, and soil infiltration rate. Scoring and overlay methods were used to create a thematic map depicting the condition of water infiltration in Yogyakarta City. The results show that Yogyakarta City is dominated by regosol soil type (99.87%), residential land (61.08%), and slope <8% (45.16%). The highest infiltration zone is classified as “Very Large” (24.55%), while the lowest is “Very Small” (0.06%). Most areas have a “natural normal” condition (16.23%). Further analysis showed a relationship between infiltration ability and flood risk. This research is expected to serve as a basis for BPBD Yogyakarta City in formulating groundwater conservation and flood mitigation policies that support more adaptive decision-making in response to climate change and urban growth.

Automated Penetration Testing Using Deep Learning Methods on Wireless Networks

Aldila Putri Linanzha — 2025-10-15

Wireless network security is an important aspect of protecting organizational information systems; therefore, penetration testing is necessary to evaluate potential vulnerabilities in network configurations and password policies. This study focuses on conducting penetration testing using Kali Linux with the Aircrack-ng toolset to assess the strength of WPA/WPA2 passwords. One of the main challenges in the password cracking process is the limitation of static wordlists such as common_password.csv, which often fail to capture diverse and contextual password patterns. To address this issue, this research proposes a generative deep learning–based approach utilizing a Long Short-Term Memory (LSTM) architecture. The LSTM model is trained using the common_password.csv dataset to learn character patterns and password structures. The training process includes character tokenization, char-to-index mapping, sequence formation, and training the LSTM network to predict the next character. Once the model is trained, a probabilistic sampling mechanism is applied to generate new password variations that resemble the original dataset distribution while being more diverse. The dynamically generated wordlist is then integrated into penetration testing scenarios using Aircrack-ng to increase the success rate of dictionary-based attacks. The experimental results show that penetration testing using Aircrack-ng with a dataset generated through the LSTM method accurately identified the SSID password, as demonstrated by a testing time ranging from 9 to 12 minutes.

Petrographic Analysis and Facies Interpretation of The Mundu Formation Carbonates: Implications For Reservoir Potential

Siti Umiyatun Choiriah — 2025-10-15

From Theory to Practice: Examining the Link Between Classroom Learning on Gender and Advocacy Engagement

Amalia Nurul Huda — 2025-10-15

Floral trait evaluations in melon are still limited, despite their importance in breeding programs. This study aimed to evaluate the performance of melon genotypes and to identify their clustering patterns based on floral traits. The experiment was conducted from June to August 2025 in a greenhouse at the Wedomartani Experimental Station, UPN Veteran Yogyakarta, using eleven melon genotypes arranged in a randomized complete block design (RCBD) with three replications. Significant differences were detected for hermaphrodite flower petal length (HFPL) and hermaphrodite flower petal width (HFPW). Genotypes G11 (3.3 cm and 2.3 cm) and G9 (3.2 cm and 2.2 cm) exhibited the highest HFPL and HFPW values, respectively. Based on the traits of HFPL and HFPW, genotypes G9 and G11 were selected as sources of genetic material to be continued in the next planting season. Cluster analysis using Ward’s method grouped the genotypes into three major clusters. The first cluster consisted of genotypes G1 and G3. The second cluster consisted of genotypes G2, G7, G14, G10, G13, and G15. The third cluster consisted of genotypes G5, G9, and G11. The first group consisted of genotypes derived from the offspring of the Makuwa group. The genotypes in the second group were mainly from the Cantalupensis melon group, while those in the third group belonged to the Inodorus melon group. This indicates that the clustering analysis effectively distinguished the genotypes according to their group. The relationships among the eleven genotypes based on floral traits provide valuable insights for melon breeding and the development of improved cultivars.

Aftershock Identification in Deep Underground Mines Using DBSCAN Clustering

Wahyu Hidayat — 2025-10-15

Salinity Effects on Anionic AEC Surfactant with n-Decane: IFT, Phase Behavior, Solubilization, Microemulsion Viscosity

Boni Swadesi — 2025-10-15

n-Decane is a common model oil for isolating salinity effects in surfactant systems. In anionic AEC formulations, salinity influences IFT reduction, microemulsion topology, solubilization capacity, and flow behavior. The objectives of this study were to evaluate the effect of NaCl salinity (0–32,000 ppm) on IFT, Winsor transitions, solubilization ratio, and microemulsion viscosity in n-decane/AEC systems, and to determine working concentrations using a CMC test derived from IFT. In this study, the method used was to determine the CMC from the breakpoint of the IFT curve versus the log concentration of AEC in the reference brine. Working concentrations of 2 percent w/w. were selected above the CMC. IFT was measured with a spinning-drop tensiometer at a controlled temperature. Phase behavior was mapped through a salinity scan to identify Winsor I–III–II. The solubilization ratio was calculated from the volume of the middle phase at equilibrium composition. The viscosity of the microemulsion was characterized using a Brookfield DV3T (C40 spindle) with a stepwise shear protocol. In n-decane model systems, salinity governs interfacial properties and phase structure that, in turn, modulate rheology. CMC-by-IFT selection of working dose and tuning salinity near HLD 0 provide a reliable framework for AEC formulation design and for calibrating process parameters ahead of controlled core-flood studies.

Subsurface Lithology Modelling of Landslide-Prone Areas in Sriharjo, Bantul Using the Geoelectrical Method

Uli Ulfa — 2025-10-15

Rice Straw Based Thickening Agent for Dysphagia Supplements

Avido Yuliestyan — 2025-10-15

The increasing prevalence of dysphagia among elderly and neurologically impaired populations highlights the urgent need for safe and stable texture-modified diets. Starch, the conventional thickening agent, is prone to rapid enzymatic breakdown by salivary amylase, resulting in compromised viscosity and safety risks during swallowing. Carboxymethyl cellulose (CMC), a cellulose derivative, offers superior viscosity stability and resistance to enzymatic degradation. This study aimed to synthesize CMC from underutilized agricultural waste, namely rice straw, and evaluate its potential as a sustainable thickening agent for dysphagia supplements in comparison with commercial pharmaceutical-grade CMC. Cellulose was extracted from rice straw, carboxymethylated, and incorporated into supplement formulations. The products were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and rheological analysis with rotational and shear rheometry. Rice straw-derived CMC achieved a degree of substitution (DS) of 0.79, while commercial CMC displayed a higher DS of 1.3. Both types of CMC resisted amylase-induced degradation, in contrast to starch solutions, which exhibited a loss of more than 97% in viscosity. Rheological results confirmed pseudoplastic behavior; commercial CMC showed higher viscosity (1460 cP, honey-like), whereas rice straw CMC demonstrated lower but more stable viscosity (268 cP, nectar-like). The novelty of this research lies in valorizing rice straw, an abundant agricultural residue, into a functional biopolymer for dysphagia-oriented nutrition. Practically, this approach provides a safer alternative to starch-based thickeners while promoting sustainable resource utilization, thereby addressing both clinical nutrition challenges and environmental concerns.

Study on the Mine Drainage System of The Pit Nusa in Lhoknga, Aceh Besar, Aceh

Faizal Agung Riyadi — 2025-10-15

Mine drainage management is a crucial aspect of mining operations, ensuring safety, efficiency, and sustainability. Poor water control may lead to operational disturbances, slope instability, and long-term environmental risks. Although studies on mine drainage exist, research focusing on integrated hydrological and hydrogeological analysis for both operational and post-mining conditions in the Lhoknga mining area, Aceh, remains limited. This study aims to design an effective mine drainage system that supports mining safety and minimizes environmental impacts. The research employed a combination of primary and secondary data, including rainfall records, groundwater measurements, hydraulic conductivity tests, infiltration rates, and topographic data. Hydrological analysis was conducted to calculate design rainfall, rainfall intensity, and runoff using the Gumbel distribution, Mononobe equation, and Rational method. Hydrogeological modeling applied Darcy’s Law, utilizing finite-difference numerical simulation, to evaluate groundwater flow and pit inflow. Water balance components were also analyzed, encompassing rainfall, evapotranspiration (using the Thornthwaite method), infiltration, runoff, and groundwater contribution. The results established a 30-year return period design rainfall of 57.5 mm/day, yielding an intensity of 7.91 mm/hour. The water balance analysis revealed that surface runoff is the dominant component, accounting for 70.33% of total precipitation. The hydrogeological model (R2=0.8) accurately predicted the formation of a cone of depression post-mining, with an estimated groundwater table drawdown of 5-15 meters. The primary contribution is a detailed technical drainage plan specifying designs for open channels and sumps for the mine drainage system. The plan necessitates a combination of open-channel drainage and a pumping system for the Northern Pit, while the Southern Pit can initially rely on gravity drainage.

Resistance of Eight Premium Melon Varieties to Viral Diseases in a Commercial Greenhouse in Central Kalimantan

Bambang Supriyanta — 2025-10-15

Melon (Cucumis melo L.) is one of the most important horticultural commodities in Indonesia, especially premium varieties with high market value. However, viral diseases such as Cucumber mosaic virus (CMV), Zucchini yellow mosaic virus (ZYMV), Papaya ringspot virus (PRSV), and Watermelon mosaic virus (WMV) remain a significant constraint, causing mosaic, chlorosis, deformation, and yield reduction. This study aimed to evaluate the resistance of eight premium melon varieties against viral diseases under commercial greenhouse conditions in Palangka Raya, Central Kalimantan. The experiment was conducted in a hydroponic production system under natural infection pressure without artificial inoculation. Disease incidence was visually assessed at both vegetative and reproductive stages, and disease progression was quantified using the Area Under the Disease Progress Curve (AUDPC). Results showed apparent variation among varieties in their response to viral infection. Inthanon exhibited the highest disease incidence (up to 45%) and the highest AUDPC value (12.36), indicating high susceptibility. Kirin and Sweet D25 also displayed relatively high incidence and AUDPC values (7.6–7.7). Conversely, Alisha and Meldo UPNVY No. 1 consistently showed the lowest incidence (<15% and <5%, respectively) and the lowest AUDPC values (0.83 and 3.24), demonstrating strong resistance. The remaining varieties (Apollo, Sweet D25, Meldo UPNVY No. 2, and Sweet Hami) showed intermediate resistance. These findings underscore the significance of varietal selection in the integrated management of viral diseases in melon. Resistant varieties such as Alisha and Meldo UPNVY No. 1 may serve as promising candidates for commercial production and future breeding programs to reduce yield losses and minimize reliance on chemical or vector control strategies.

IoT Adoption in Agriculture: Linking Technology Readiness, Acceptance and Entrepreneurial Ambidexterity Among Small-scale Farmers in Sabah

Nurul Alam Mohd Yaakub — 2025-10-15

The adoption of Internet of Things (IoT) technologies in agriculture has the potential to enhance productivity, efficiency, and sustainability. However, small-scale farmers often face barriers related to technological capability, acceptance, and limited resources. The Sabah state’s alarming long-term food security is further challenged by a declining workforce and limited productivity. Understanding the readiness and acceptance of Sabahan farmers towards IoT adoption is therefore needed in shaping effective interventions. The goals of this study are (i) to investigate the influence of technology readiness on technology acceptance within a technology readiness–acceptance framework; (ii) to examine the effects of perceived usefulness and perceived ease of use on IoT adoption intention; and (iii) to analyse the mediating role of entrepreneurial ambidexterity in strengthening the relationship between technology acceptance and adoption intention among small-scale farmers in Sabah. A cross-sectional quantitative research design was applied, with data collected from small-scale farmers using proportionate stratified random sampling. The dataset was analysed using partial least squares structural equation modeling (PLS-SEM) to test the research framework. The findings demonstrate that (i) technology readiness motivators significantly influence technology acceptance, (ii) perceived usefulness is the strongest predictor of IoT adoption intention, and (iii) entrepreneurial ambidexterity plays a significant mediating role, particularly through perceived ease of use. This study contributes to providing empirical evidence on the behavioural factors shaping IoT adoption among smallholder farmers. The results propose practical directions for policymakers, agricultural technology providers and stakeholders in designing strategies that align with farmers’ readiness and support the digital transformation of Sabah’s agricultural sector.

Reducing Landslide Risk in Yogyakarta Through Three-Dimensional Gravity Modeling as A Proactive Disaster Risk Reduction Strategy

Yohana Noradika Maharani — 2025-10-15

Landslides in the Special Region of Yogyakarta, Indonesia, are widely recognized as being triggered by steep topography, active tectonics, and seasonal monsoon rainfall. however, conventional hazard assessments frequently overlook critical subsurface geological controls such as fault zones, weathered bedrock interfaces, and fractured basement rocks—that mayr serve as primary sliding surfaces. This study directly addresses this limitation by developing a novel three-dimensional gravity-based model to enhance landslide susceptibility mapping and support regional mitigation strategies. High-resolution (~200 m) GGMplus gravity data were processed using Oasis Montaj™ software, with regional-residual anomaly separation performed through upward continuation to 5 km and second-order polynomial surface fitting. Subsequently, three-dimensional density inversion was applied to delineate shallow subsurface structures influencing slope stability. The total Bouguer anomaly ranges from –18.6 to +181.4 mGal: strong positive anomalies (>+100 mGal) are concentrated over Mount Merapi, reflecting dense, unweathered volcanic intrusions and lava flows, while pronounced negative anomalies (<–10 mGal) dominate central and eastern sectors, correlating with thick colluvium, weathered volcaniclastic deposits, and fractured basement rocks. The residual anomaly map (–2.5 to +2.6 mGal) effectively isolates shallow density contrasts, revealing that 82% of recorded landslides (n=142 events, 2010–2022) spatially coincide with low-density zones (<–1.0 mGal), particularly clustered along the NW–SE-trending Opak Fault interpreted as a zone of fault gouge, brecciation, or fluid-saturated fractures that critically control slope failure mechanics. Conversely, positive residual anomalies (>+1.0 mGal) correspond to geologically stable domains underlain by dense intrusions or compacted layers. This study demonstrates that 3D gravity modeling provides a powerful, non-invasive tool for identifying landslide-prone zones governed by hidden subsurface architecture, offering significant practical value for land-use planning and disaster risk reduction in complex volcanic terrains.

Comparison of Intensive and Non-Intensive Cocoa Cultivation on Cocoa Pod Diseases In Nglanggeran Village

Meisha Vabrizio Hero — 2025-10-15

Cocoa (Theobroma cacao L.) is one of Indonesia's main plantation commodities, but its productivity is hampered by pod diseases such as black pod (Phytophthora palmivora) and anthracnose (Colletotrichum gloeosporioides). This study, conducted in Nglanggeran Village, aimed to assess the incidence and severity of disease under different cultivation practices, as well as to observe the symptoms caused by the diseases on the pods. Twenty trees were deliberately selected, with 10 trees from intensive cultivation and 10 from non-intensive cultivation. The incidence and severity of disease were measured every 5 days. Incidence was calculated by comparing the number of healthy pods with the number of diseased pods, while intensity was calculated using a scoring system. The data were analyzed to compare the intensity and incidence between cultivation practices. The results showed that the incidence and intensity of anthracnose were higher than those of black pod. Intensive cocoa cultivation can suppress the spread of disease and produce more pods.

The Effect of Divalent Ion Addition to Rhamnolipids Solution Through Fluid-to-Fluid Testing for Enhanced Oil Recovery: A Review

Hariyadi Hariyadi — 2025-10-15

Hybrid Sentiment Intelligence: A CNN-Based Analysis of Visitor Experience at the “History of Java” Museum in Yogyakarta

Yuli Fauziah — 2025-10-15

Visitor feedback is a critical yet underutilized resource for optimizing cultural heritage experiences. This study introduces a novel hybrid sentiment analysis framework that integrates digital reviews (Google, TripAdvisor, Traveloka) with digitized physical guestbook entries, capturing both reactive online sentiment and reflective on-site feedback. Leveraging a Convolutional Neural Network (CNN) with custom-trained Word2Vec embeddings, our model classifies visitor sentiment into Positive, Neutral, and Negative categories with 94.7% accuracy and 0.93 F1-score, significantly outperforming traditional models (SVM, Naïve Bayes). Analysis reveals a striking sentiment divergence: physical guestbooks exhibit 71.2% positivity, compared to 58.9% on Google Reviews, highlighting a systematic negativity bias in digital platforms. We further prototype a real-time dashboard for museum staff, enabling data-driven interventions based on sentiment drift and keyword trends. This work pioneers the fusion of analog and digital visitor voices in Indonesian cultural analytics, offering museums a scalable, explainable, and context-aware tool for experience optimization.

Deep Learning Approaches for Batak Script Recognition: A Literature Review

Dhimas Arief Dharmawan — 2025-10-15

The Batak script, one of Indonesia’s ancient writing systems, has recently garnered increasing attention in the fields of digital preservation and pattern recognition. However, the complexity of its character structures and the limited availability of annotated datasets pose significant challenges to automated recognition. This paper presents a comprehensive literature review on deep learning approaches for Batak script recognition. We analyze existing studies that apply convolutional neural networks (CNNs), recurrent neural networks (RNNs), hybrid models, and transfer learning to character recognition tasks. Furthermore, we highlight the strengths and limitations of these methods in addressing challenges such as character similarity, dataset scarcity, and noise in historical manuscripts. The review also discusses research gaps and potential future directions, including the integration of attention mechanisms, data augmentation strategies, and multimodal approaches. By synthesizing recent developments, this study provides valuable insights for researchers aiming to advance Batak script recognition and contributes to the broader effort of preserving Indonesia’s cultural heritage through deep learning technologies.

Integrated Study of Geochemical, Geomechanical, and Mineralogy Leak Potential on Caprocks with Shale: A Review

Aris Buntoro — 2025-10-15

Effect 0f Glycerol Dosage on Antifungal Performance of Black Cumin Oil–Fortified Edible Coatings on Red Chili (Capsicum Annuum)

Nova Wahyu Pratiwi — 2025-10-15

The Effect of HNO3 Concentration Variations on the Recovery of REEs from Coal Fly Ash Through Hydrometallurgical Process

Tri Wahyuningsih — 2025-10-14

In this study, coal fly ash was used as the primary material for analysis and extraction of REEs contained therein. Coal fly ash is a waste product from coal combustion, commonly used in the power generation sector, which is typically disposed of without furthering processing. Therefore, this study was conducted to utilize this waste, which contains a significant amount of REEs, for use in the metallurgy industry as strategic additives in material engineering. The rare earth metal recovery process involved leaching with strong acid HNO₃at concentrations of 0.6 M, 0.8 M, and 1 M. Analysis using the ICP-OES method on the three variations yielded very low dissolution of REEs. Characterization with XRD of the leaching results showed that the leaching process effectively mobilized and reformed REEs into various new crystalline phases.

Volcanic Facies Architecture of Sedringo Volcano, Dieng Volcanic Complex

Dwi Fitri Yudiantoro — 2025-10-15

The Dieng Volcanic Complex (DVC) in Central Java, Indonesia, is situated within an active magmatic arc formed by the oblique subduction of the Indo-Australian Plate beneath Eurasia, with an additional influence from the Pacific Plate. Despite its importance as a major geothermal field, the eruptive history of Sedringo Volcano—a key but poorly studied edifice within the DVC remains undocumented. This study presents the first systematic reconstruction of Sedringo’s volcanic evolution and introduces a novel, process-based volcanic facies model to link surface geology with subsurface reservoir architecture. We integrate field mapping, stratigraphic logging, and petrographic analysis of volcanic lithologies. Results reveal a bipartite facies architecture: (1) a central facies of coherent andesitic lava flows and caldera-related agglomerates, and (2) a proximal facies dominated by poorly sorted pyroclastic flow deposits. This pattern records a clear shift from effusive to explosive activity, culminating in caldera collapse and the formation of peripheral cones. The new facies model provides the first geologically constrained framework for interpreting geothermal reservoir geometry in the Sedringo sector. Moreover, the identification of hazardous pyroclastic units and caldera structures offers actionable guidance for geothermal well placement and volcanic hazard zonation. By directly connecting volcanic stratigraphy to energy exploration and risk mitigation, this work demonstrates how fundamental geological research enhances sustainable development in active volcanic systems.

Fabrication and Performance Evaluation of CA–PEG–PVC/GO Nanocomposite Membranes Prepared by Phase Inversion for Desalination in Drinking Water Treatment

Renung Renintyas — 2025-10-15

Increasing Dishwashing Soap Production Capacity through the Implementation of Mixer Machines in Small and Medium Enterprises

Yuni Siswanti — 2025-10-15

Comparison of Semi-Supervised Learning Performance in Indonesian Sentiment Analysis: An Empirical Study between Statistical Machine Learning and Deep Learning Approaches

Rochmat Husaini — 2025-10-15

The limited availability of labeled data is a significant challenge in developing sentiment analysis models, especially for Indonesian, which still has minimal annotated resources. Semi-supervised learning (SSL) offers a solution by utilizing large amounts of unlabeled data. This study aims to compare the performance of two main paradigms in SSL—Statistical Machine Learning (SML) and Deep Learning (DL)—in the context of Indonesian text sentiment classification. Four SML models (KNN, Naïve Bayes, Random Forest, SVM) with TF-IDF, Word2Vec, and FastText feature representations were compared with a FastText embedding-based Bi-LSTM architecture that was fine-tuned. Experiments were conducted on two datasets: product reviews (14,000 instances) and social media (22,000 instances), each with only 10% of the initial labeled data. The self-training approach was applied with a confidence threshold of 0.8 and a maximum of 3 iterations. The results show that DL consistently outperforms in accuracy (achieving 89.7% vs. 84.2% on large datasets), F1-score (89.4% vs. 83.6%), and efficiency in utilizing unlabeled data (95.6% accepted pseudo-labels vs. 90.2%). However, this advantage comes at the cost of 4x higher computational costs and lower interpretability. SML remains relevant for scenarios with limited resources or when model transparency is a priority. This study recommends using DL if the infrastructure is adequate, and SML if interpretability and computational efficiency are prioritized. These findings provide empirical guidance for practitioners and academics in choosing the optimal SSL approach for Indonesian language sentiment analysis.

Enhancing Regenerative Agriculture Systems in Karst Landscape Based on Biophysical Properties and Farmers’ Practices

Ali Munawar — 2025-10-15

Conventional farming practices can lead to soil degradation and a decline in productivity. In the era of the climate change, regenerative agriculture (RA) is considered one of the the solutions to these issues. This research aimed to investigate the the potential of RA implementation in areas of Karst in Pacarejo, Semanu, Gunungkidul, Yogyakarta,, based on the existing land characteristicscharacteristics and farmers’ practices in the area. Some investigations were conducted through characterisation and observation of biophysical aspects, including soil, vegetation, and water resources,resources, as well as socioeconomicsocial-economic conditions. Some soil physical and chemical properties, vegetative growth of teak trees, and litter accumulation at three different locations in variably sloping lands in the Teak Plantation Station UPN “Veteran” Yogyakarta were investigated. The social and economic conditions of the local farmers were described based on direct discussions and questionnaires handed to 10 farmers. Collected data showed that most soils were generally thin, with similar physical and chemicalchemical properties, and low fertilityfertility, especially in N, P, and K nutrients, and resulting in relatively low growth of the teak trees. However, the living teak plantation and terraces support soil conservation. Farming activities mostly occur during the rainy season and with a limited number of crops to grow. Currently, farmers have been well aware of the need to balance both organic and inorganic fertilizers. In conclusion, these areas can be potentially used for developing regenerative agriculture systems.

Coconut Shell Biochar and Sheep Manure for Food Security of Maize on Samas Coastal Sandy Land

Susila Herlambang — 2025-10-15

Coastal sandy soils have limited productivity due to their low organic matter content, cation exchange capacity, and water-holding ability, thus requiring environmentally friendly soil management innovations. Coconut shell biochar is known to improve soil physico-chemical properties, while sheep manure serves as a source of readily mineralizable organic nutrients. However, the interaction between the two in maize cultivation systems on coastal sandy soils has not been extensively studied. This study aimed to evaluate the effects of combined doses of coconut shell biochar and sheep manure on soil chemical properties and maize productivity in the sandy soils of Samas Coast. The research employed a Randomized Block Design (RBD) with two factors: biochar dose (0, 10, 15, and 20 tons/ha) and sheep manure dose (0; 2,5; 5; and 7,5 tons/ha). Observed parameters included soil organic C, cation exchange capacity (CEC), plant dry weight, and maize yield (tons/ha). Data were analyzed using analysis of variance (ANOVA), followed by post-hoc tests to determine differences among treatments. The results showed that the addition of biochar and sheep manure had significant effects on all observed parameters. The combination of medium biochar dose (20 tons/ha) and high sheep manure dose (30 tons/ha) (B2K3) resulted in the highest increase in CEC (28.5 me%), organic C (1.25%), plant dry weight, and maize yield exceeding 10 tons/ha. This indicates a synergistic effect between biochar and sheep manure in improving soil fertility and maize productivity on sandy soils. These findings contribute to the development of sustainable coastal soil management strategies, reducing dependence on chemical fertilizers and thereby supporting food security.

The Influence of Coal Characteristics on Coke Formation in Indonesia’s Steel Industry

Edy Nursanto — 2025-10-15

Indonesia possesses abundant coal resources with diverse characteristics, which directly influence their potential in the steel industry, particularly in metallurgical coke production. Coke serves as both a reducing agent and a crucial fuel in the blast furnace process, requiring specific coal qualities such as high fixed carbon content, low sulfur content, good caking ability, and sufficient thermoplastic properties. However, Indonesian coal is predominantly sub-bituminous and lignite, which are limited for coking purposes. This paper examines the influence of coal characteristics on coke formation, evaluates the potential of Indonesian coal, including coking coal prospects in Muara Teweh, Central Kalimantan, for metallurgical applications, and reviews strategies for enhancing coal utilization to achieve competitive coke production. Furthermore, the role of Environmental, Social, and Governance (ESG) principles in developing a sustainable coke industry is also discussed. Findings suggest that enhancements in beneficiation processes, coal blending strategies, and ESG integration can improve domestic coke self-sufficiency while promoting sustainable development.

Coal-Based Humic Acid Fertilizer Effects on Soil Properties and Mustard Growth

Partoyo Partoyo — 2025-10-15

Humic acid is an essential organic substance that improves soil quality and enhances plant growth. This study investigates the novel application of low-rank coal waste as a source of humic acid for agricultural purposes. Humic acid was extracted from coal and applied as a soil amendment to two contrasting soil types under greenhouse conditions. The application of coal-derived humic acid significantly improved soil pH, electrical conductivity, and organic carbon content, leading to enhanced mustard crop performance. Higher concentrations of humic acid promoted stronger plant growth and increased leaf greenness. The results highlight the potential of converting low-rank coal waste into humic-based fertilizers as an effective strategy for improving soil fertility and supporting sustainable agricultural practices.

Web-Based ISBN Registration System Development at LPPM UPN “Veteran” Yogyakarta Using the RAD Method

Dhimas Arief Dharmawan — 2025-10-15

This research aims to develop an integrated web-based information system to support the registration process of the International Standard Book Number (ISBN) at the Institute for Research and Community Service (LPPM), UPN "Veteran" Yogyakarta. The background of this study lies in the limitations of the current system, which relies on Google Forms. This existing approach is considered inefficient, unstructured, and vulnerable to data security breaches. The research methodology includes several stages: data collection, requirement analysis, selection of system development methods, design, implementation, testing, and evaluation. The Rapid Application Development (RAD) approach was chosen as it enables fast and iterative system development with direct user involvement. The expected outcome of this study is a web-based system that enhances efficiency, effectiveness, and transparency in managing ISBN processes, while also contributing to the achievement of the institution’s Key Performance Indicator (KPI) 2.3. Furthermore, the system is expected to generate positive impacts in technological, social, and economic aspects within the academic environment.

Hybrid-Quantum CNN for Enhanced Facial Emotion Recognition: A Comparative Study with VGG16 on the RAF-DB Dataset

Mangaras Yanu Florestiyanto — 2025-10-15

Facial expression recognition (FER) underpins applications in affective computing but remains challenged by computational cost and the ambiguity of compound emotions. We introduce a Hybrid-Quantum Convolutional Neural Network (HQ-CNN) that integrates quantum principles (superposition, entanglement) into a classical CNN pipeline to enhance representational power and efficiency. Evaluated on the Real-World Affective Faces Database (RAF-DB), the HQ-CNN improves accuracy by 4.60% on basic emotions and 4.47% on compound emotions, while reducing computation time by up to 22.11% and 6.20%, respectively, relative to a VGG16 baseline. Confusion-matrix analysis shows fewer misclassifications on challenging compound categories, indicating better separation of overlapping affective cues. These results support the use of quantum-enhanced architectures as a viable path toward robust, real-time FER systems.

Recovery of Neodymium from Pelabuhan Ratu Coal-Fired Power Plant: A Comparative Study of Acid Leaching Reagents on Coal Fly Ash

Yasmina Amalia — 2025-10-15

Landslide Risk Reduction via Early Warning System in Sambirejo Village, Indonesia

Eko Teguh Paripurno — 2025-10-15

Sambirejo Village, located in Wonosalam District, Jombang Regency, Indonesia, is an area with moderate to high landslide vulnerability, triggered by a combination of extreme rainfall, geological conditions, and land-use practices. This study aims to design and implement an Early Warning System (EWS) as a proactive measure for disaster mitigation and preparedness. The research methodology includes geological surveys and fracture mapping, landslide characterization, and the planning and installation of the EWS. The developed system comprises wireless sensors that monitor ground motion (extensometers), slope gradient (tiltmeters), and rainfall, all of which are connected to a real-time monitoring dashboard. The EWS successfully provides continuous data on ground motion and rainfall, which can be used to establish warning thresholds. For example, a “Warning” level can be activated if rainfall exceeds 50 mm/day, and an “Alert” level if the rate of ground motion exceeds 2 cm/day in combination with continuous rainfall. The highest alert, “Evacuation Warning,” is issued if ground motion shows exponential acceleration. This mechanism provides a scientific basis for village governments and the Regional Disaster Management Agency (BPBD) to make timely evacuation decisions. The development and implementation of the EWS have proven to be an effective solution for mitigating landslide risks at the study site. The application of this technology can significantly reduce the potential for loss of life and property damage. Furthermore, the implementation of the EWS enhances the preparedness of both the local community and the Jombang BPBD in responding to landslide threats, thereby reducing the risk of casualties and material losses

Groundwater Surface Contour Modeling Using Kriging Method Around JJLS, Purwosari District, Gunung Kidul

Peter Eka Rosadi — 2025-10-15

Kapanewon Purwosari, Gunungkidul Regency, Special Region of Yogyakarta is one of the areas that still uses groundwater to meet water needs such as household and agricultural needs. Over time, the expansion of development areas such as JJLS has resulted in changes in spatial patterns, including the groundwater conditions within them. Direct data collection in the field, such as data on rivers and residents' wells, can be used as parameters in modeling groundwater conditions in the area. Limited data can be supplemented by using the krigging method with software such as ArcGis to help in groundwater modeling. Based on 36 observation points, including 24 community wells and 12 rivers, interpolation was performed using the krigging method to produce groundwater contour lines in the area around the observation points

A Review of Shape Memory Alloys: Fundamental, Microstructure Property, and Emerging Trends in Industrial Applications

Atik Setyani — 2025-10-15

Analysis of Resistivity Data of Wenner Alpha Configuration on Granite Prospect in 'JT' area, Central Kalimantan, Indonesia

Andreas Edvian Lubis — 2025-10-15

The need for igneous rock as a support for development is increasing in line with the rapid development of infrastructure in Kalimantan. Exploration activities are imperative and must be undertaken as soon as possible. Geological and geophysical investigations, including the resistivity method, are conducted as the initial step in exploration activities. In this study, exploration at the ‘JT’ area using the Resistivity method with the Wenner Alpha configuration is supported by drill hole data. There are 17 lines oriented Northwest-Southeast and North-South, with a line length of 320 meters and 6 points drill hole crossed by a Resistivity path. The processing of the Resistivity data uses the Res2Dinv software and the drill hole by the Strater4 to produce subsurface profiles. The cross-section is correlated with the drill hole profile results using CorelDRAW software. Next is 3D modeling using the Oasis Montaj software. The results obtained from this study are lithology that is interpreted based on resistivity value are soil with resistivity < 20 Ohm-m, under soil layers there are interlocutors between sandstones with claystone with resistivity of 20 - 60 Ohm-m, below that sandstones are originating from Formation Tanjung with a resistivity of 60 - 300 Ohm-m, and below that there is granite with resistivity > 300 Ohm-m. The distribution of granite in this area has very good quality in the northern region as a prospect area. The granite in the southern part has a lower resistivity value, which is thought to be weathered granite

Design of Internet of Things (IoT) Based Indoor Hydroponic System for Pagoda Mustard (Brassica Rapa Subsp. Narinosa)

Bagus Muhammad Akbar — 2025-10-15

Dynamic Hyperparameter Tuning in Deep Co-Training for Semi-Supervised Sentiment Analysis on Social Media

Agus Sasmito Aribowo — 2025-10-15

Influence of pH and Pre-treatment on Biogas Production in Anaerobic Digestion: A Review

Ryan Keane Mahardika Pratama — 2025-10-15

Anaerobic Digestion (AD) offers a potential solution to global challenges in renewable energy production and waste management. It is also a promising low-carbon emission technology. However, its efficiency can be limited by various technical factors. This review article addresses these limitations by investigating the main effects of pH and pre-treatment on biogas production and COD removal efficiency. The research methodology involves a comprehensive review of the literature on the effects of different pH ranges and various pre-treatment methods, including thermal, chemical, and enzymatic techniques. The findings revealed that a neutral to slightly alkaline pH range (6.8–8.3) provides optimal conditions because it can balance acidogenesis and methanogenesis, leading to high biogas yield and a COD removal rate of up to 86.34%. In addition, pre-treatment can significantly increase the efficiency of the AD process. For example, thermal alkaline pre-treatment of algal biomass increased methane yield by 229%, and shock wave pre-treatment of algae increased dissolved COD by approximately 70% compared to the control group. The contribution of this study is a consolidated overview of optimal conditions and effective methods for improving AD performance, providing a basis for designing AD systems that are more efficient and stable for sustainable energy and waste management.

Assessment of Groundwater Quality and Proposed Treatment using Aeration-Filtration Methods for Iron-Rich Groundwater at UPN “Veteran” Yogyakarta

Ekha Yogafanny — 2025-10-15

Groundwater quality often does not meet the standards as a result of geological factors and human activities. This study was conducted at the University of Pembangunan Nasional “Veteran” Yogyakarta (UPNVY), Condongcatur Campus, to evaluate groundwater quality and provide appropriate treatment recommendations. Groundwater samples were taken from three bore wells: Rectorate Building (SR), Nyi Ageng Serang Lecture Hall (SNAS), and Prof. Bambang Soeroto Lecture Hall (SAL). Sampling followed SNI 6989.57:2008, while laboratory tests were performed on physical parameters (turbidity and TDS) and chemical parameters (pH and Fe). The results showed that turbidity, pH, and iron concentration at most sampling did not meet the quality standards. Water turbidity reached 39.89 NTU at the SAL, far above the threshold of <3 NTU. Iron content was recorded at 5.85 mg/L in the SNAS, exceeding the 0.2 mg/L standard. The pH values at all three sites were also below the standard, ranging from 6.1 to 6.4, indicating acidic conditions. Geological analysis indicated that the high Fe content is associated with the weathering of volcanic minerals such as augite, hornblende, and biotite, which are abundant in Merapi Muda deposits. As a follow-up, a proposed water treatment system was designed using a multitray aeration and filtration combination with shell sand media. This method is expected to be effective in reducing iron concentration by up to 99.9%, decrease turbidity by more than 90%, and raise pH to a more neutral level. In the treatment scenario for SAL, Fe concentration decreased from 2.74 mg/L to 0.002 mg/L.

Soil Quality Enhancement for Sustainable Shallot (Allium ascalonicum L.) Cultivation in Central Kalimantan

Bambang Supriyanta — 2025-10-15

Shallot (Allium ascalonicum L.) is an economically valuable horticultural crop for Indonesia’s domestic market and rural livelihoods. However, its expansion into Central Kalimantan is constrained by acidic, nutrient-poor soils such as Ultisols and Spodosols, and erratic rainfall. This study aims to develop an integrated soil quality enhancement framework combining liming, organic amendments, and biofertilizers for sustainable shallot cultivation. The research was conducted through descriptive and comparative analysis of soil properties before and after treatment in a 500 m² demonstration plot. Laboratory analyses included soil pH, organic matter, cation exchange capacity (CEC), and available phosphorus (P-Bray). Data interpretation used descriptive statistics and literature benchmarking. Results showed that integrated soil management increased soil pH from 4.5 to 6.0, organic matter from 1.2% to 2.8%, CEC from 6 to 12.5 cmol(+)/kg, and available phosphorus from 5 ppm to 18 ppm. These improvements corresponded to potential yield increases of 30–40% under optimal irrigation. The novelty of this study lies in the adaptive integration of biological and chemical amendments tailored for humid tropical acid soils. The findings provide practical insights for sustainable horticulture and local food security enhancement in Central Kalimantan.

Effectiveness of Mixing Natural Attractants for Trapping Fruit Flies in Snake Fruits Plantations

Audrey Pramudhita Kamil — 2025-10-15

Snake fruit (Salacca zalacca) is an important Indonesian fruit commodity, yet its productivity has been declining due to infestations of fruit flies. This study evaluated the effectiveness of natural attractants, including methyl eugenol–containing fragrant leaf essential oil and fermented fruit juices, either applied singly or in combination, in trapping fruit flies. The experiment was conducted in Girikerto Village, Sleman, from March to May 2024 using a Completely Randomized Design (CRD) with eight treatments: fragrant leaf essential oil (2 mL), fermented snake fruit juice (2 mL), fermented pineapple juice (2 mL), fermented mango juice (2 mL), mixtures of 1 mL essential oil with 1 mL of each fermented fruit juice, and control. Data were analyzed using ANOVA followed by LSD test at 5%. Results showed that the combination of fragrant leaf essential oil and fermented mango juice (1 mL + 1 mL) was effective in trapping Bactrocera spp., and its performance was not significantly different from 2 mL essential oil. Three species of fruit flies were identified: Bactrocera papayae, B. carambolae, and B. umbrosa. These findings highlight the potential of combining natural attractants for sustainable fruit fly management in snake fruit plantations.

Analysis of the Carburizing Process Using a Batch Atmosphere Furnace

Hendy Roesma Wardhana — 2025-10-15

The carburizing process is a heat treatment method aimed at enhancing the surface hardness, wear resistance, and corrosion resistance of materials by adding carbon at high temperatures. This study analyzes the impact of this process on low-carbon steels (STKM 13A and SPCC) and an alloy steel (SCM 435). Carburization was conducted at 900°C for 100 minutes. The tests performed included a Micro Vickers hardness test and microstructural characterization following the ASTM E-407 standard. The results showed a significant increase in the surface hardness of all materials. Critically, carbon diffusion in both STKM 13A and SPCC reached a consistent and defined depth of 0.48 mm, while in SCM 435, it diffused uniformly across the entire material thickness. Microstructural analysis revealed a phase transformation from pearlite and ferrite before carburization to martensite afterward. For STKM 13A and SPCC, the martensite phase formed up to a depth of 0.48 mm, while SCM 435 underwent a total transformation to the martensite phase, resulting in full hardening. This research provides specific quantitative data on the critical case depth (0.48 mm) achievable in STKM 13A and SPCC under these conditions, offering a clear reference point for industrial applications requiring controlled surface hardening.

Sustainable Utilization of K-Humate Coal Residue into Bead Adsorbents for Cu(II) Removal

Daniel Timotius — 2025-10-15

Tensile Testing and Macrographic Examination of Resistance Spot Welding on Aluminum–Copper–Magnesium Alloy Sheet in Accordance with AWS D17.2

Mansyur Abdul Shaleh — 2025-10-15

Anaerobic Digestion Versus Composting: A Comprehensive Review on Waste Stabilization, Resource Recovery, and Sustainability

Nina Anggita Wardani — 2025-10-15

The rapid growth of organic waste from agricultural, industrial, and municipal activities has raised serious environmental concerns. Anaerobic digestion (AD) and composting (COM) are two widely applied biological technologies developed to stabilize organic waste and recover valuable resources. This review compares their performance, products, environmental impacts, and operational challenges, and discusses the potential benefits of integrating both processes. AD degrades organic matter under anaerobic conditions into biogas and digestate, which can be used as an organic fertilizer due to its high nutrient content. COM is an aerobic self-heating process that transforms organic residues into stable compost suitable for soil improvement. Comparative data show that AD achieves higher degradation rates in shorter residence times, while COM produces a stable product with lower investment and operational complexity. Life cycle assessments indicate that COM has higher energy-related environmental burdens, whereas AD offers better energy recovery but requires higher capital costs and post-treatment of digestate. The integration of AD and COM enables the complementary use of both processes, where AD contributes to methane generation and nutrient retention. At the same time, COM enhances pathogen inactivation and moisture reduction, thereby improving the overall efficiency and sustainability of organic waste management.

Application of Organic Fertilizer and Coconut Water to Improve the Growth of Butterfly Tree (Bahunea purpurea L.) in Karst Land

Heti Herastuti — 2025-10-15

Butterfly tree (Bauhinia purpurea L.) is known to possess high adaptability and can be cultivated in karst regions of Indonesia. In this context, organic fertilization combined with coconut water as a natural growth hormone is applied to enhance plant growth. Therefore, this research aims to determine the interaction between various organic fertilizers and coconut water in increasing the growth of the butterfly tree in the experimental garden of the Faculty of Agriculture, UPN Veteran Yogyakarta. A Completely Randomized Design (CRD) was used with a Factorial method between August and September 2025. The first factor was the type of organic fertilizer, consisting of cow and goat manure, as well as vermicompost. The second factor was the 25%, 50%, and 75% concentrations of coconut water. The results showed that there was no interaction between organic fertilizers and coconut water. Organic goat manure and vermicompost produced percentage of live plants, plant height, and number of leaves than cow manure. Meanwhile, vermicompost showed the longest root length and the largest number of roots compared to cow and goat manure. The 50% coconut water concentration produced the largest percentage of live plants and the number of roots.

Overcoming Dead Time in Thermal Processes: A Comparative Evaluation of PID-SP and PID-IMC Control Strategies

Yulius Deddy Hermawan — 2025-10-15

Dead time is a critical factor that often causes instability in process systems, so appropriate control strategies are needed to address it. This study focuses on the outlet temperature control of a stirred-tank heater that exhibits dead time. A 10 L laboratory-scale tank equipped with an electric heater was constructed, and the long outlet pipeline introduces a measurable delay in the temperature response. The outlet temperature is maintained by adjusting the electrical heating input, while PID parameters are tuned using the Process Reaction Curve (PRC) method. Two control strategies are examined: PID with Smith Predictor (PID-SP) and PID with Internal Model Control (PID-IMC). System models were implemented and tested using XCOS/Scilab. Closed-loop simulation results indicate that PID-IMC performs better than PID-SP, as indicated by a lower integral absolute error (IAE). These results provide evidence of the practical advantages of PID-IMC in compensating for dead time in thermal process systems and offer useful guidance for improving process control design in industrial applications.

Evaluation of Geoelectrical Data Stability: Manual Quadrupole vs. Multi-Electrode Switch Panel Prototype

M. Fachrul Rozi Kurniawan — 2025-10-15

Effect of Rhamnolipid Biosurfactant on Enhanced Oil Recovery Through Imbibition Performance of Crude Oils: A Literature Review

Harry Budiharjo Sulistyarso — 2025-10-15

Biosurfactants applied in enhanced oil recovery (EOR) have attracted significant attention due to their biodegradability, low toxicity, and ability to modify the interactions between oil, rock, and brine. Rhamnolipids—glycolipid biosurfactants synthesized by bacterial species—have a unique amphipathic structure that can alter the characteristics of crude oil at the molecular and macroscopic levels. This study examines the impact of rhamnolipid biosurfactant on the imbibition performance of crude oils, exploring it as a potential green alternative to conventional surfactants. Laboratory experiments were designed to evaluate the reduction of interfacial tension and oil displacement efficiency under various reservoir conditions. The results demonstrate that rhamnolipid significantly enhances oil recovery by promoting water-wet conditions and improving spontaneous imbibition rates, with recovery increments surpassing those observed in conventional systems. The novelty of this work lies in the direct integration of rhamnolipid biosurfactant into imbibition-driven recovery processes, which has rarely been addressed in previous EOR studies. While prior works have primarily focused on coreflooding and micellar flooding performance, this study provides mechanistic insights into how rhamnolipids modulate capillary forces and rock–fluid interactions during imbibition. By coupling environmental sustainability with improved oil recovery efficiency, the findings highlight rhamnolipid as a dual-function agent—both as an effective surfactant and as a sustainable alternative for next-generation EOR strategies.

Copper Deportment in a VMS-Hosted Ore from Wetar via Diagnostic Sequential Leaching

Imam Prasetyo — 2025-10-15

Geoecological-Based Strategy for Ecosystem Improvement in Volcanic Zones: A Preliminary Study from Jurang Jero Area, Merapi National Park

Septyo Uji Pratomo — 2025-10-15

Mount Merapi, one of Indonesia’s most active volcanoes, has repeatedly altered surrounding river ecosystems through frequent eruptions, with the 2010 event producing over 140 million cubic meters of pyroclastic material. This preliminary study aims to analyze the geoecological dynamics of the Jurang Jero sector in Merapi National Park, which has experienced severe impacts on river morphology, sedimentation, water quality, and riparian vegetation. A desk study approach was employed, synthesizing secondary data that included geological and hazard maps, remote sensing imagery, hydrological records, and published scientific reports. Findings indicate that lahar-induced sedimentation after 2010 resulted in aggradation, channel widening, and a reduction in river capacity, with some sabo dams quickly reaching their limits. Water quality deteriorated due to extremely high suspended solids, increased turbidity, and elevated heavy metals, although these effects were partly temporary. Riparian vegetation suffered extensive damage, followed by natural succession dominated by invasive species such as Acacia decurrens, which hinders native regeneration. Nevertheless, signs of ecological recovery have emerged, as evidenced by the presence of pioneer species and the implementation of rehabilitation programs. This study highlights the need for a geoecology-based adaptive conservation strategy that integrates river morphology rehabilitation, sediment management, water quality improvement, and riparian vegetation restoration while involving local communities. The proposed framework provides a conceptual basis for future field research and practical river ecosystem management in volcanic landscapes.

The Role of Generative AI in Agricultural Game Assets Production: A Survey

Hari Prapcoyo — 2025-10-15

The growing demand for high-quality visual assets in the gaming industry has created challenges in producing diverse and realistic agricultural-themed content. Traditional techniques, such as procedural content generation (PCG) and early deep learning models—including Autoencoders, Variational Autoencoders, and Deep Convolutional GANs—often struggle with limitations in resolution, realism, and diversity. This study aims to explore how Generative Adversarial Networks (GANs), particularly StyleGAN2, can address these challenges in generating 2D assets for farming games. A systematic literature review was conducted using databases such as Scopus and Google Scholar, covering publications from the last five years. The selection criteria included studies focusing on generative models for visual game asset creation, with an emphasis on domains related to agriculture or the environment. The review highlights StyleGAN2’s style-based architecture, which enables fine-grained control over sprites, textures, and environmental elements, leading to more realistic and customizable assets. Key contributions of this work include identifying current technical strengths, outlining socio-economic implications, and discussing practical challenges such as dataset availability and evaluation standards. The findings suggest opportunities for hybrid procedural–AI approaches, domain-specific datasets, and the expansion of content toward dynamic and interactive elements. By consolidating these insights, the paper offers guidance for both researchers and practitioners on leveraging generative AI for the realistic and diverse production of agricultural game assets.

The Evolution of Mining Regulations in Indonesia: Legal Framework, Implementation, and Challenges

Ignasius Pratama — 2025-10-15

Mining regulations in Indonesia have undergone significant transformations in response to political, economic, and environmental dynamics. Beginning with Law No. 11 of 1967, which introduced a framework for foreign investment in the mining sector, the regulatory landscape has evolved through various reforms, including Law No. 4 of 2009, Law No. 3 of 2020, and Law No. 2 of 2025. These laws reflect the state’s effort to strengthen control over mineral resources, promote downstream processing, and ensure environmental protection. Despite normative improvements, implementation remains challenging due to overlapping authorities, weak enforcement, and infrastructural constraints. In addition, the further regulation focuses on technical aspect, which are Ministerial Decree No. 1806/2018 and Ministerial Decree No. 1827/2018. This paper examines the historical development, key provisions, and implications of Indonesia’s mining regulations, highlighting both progress achieved and persistent issues.