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This study aims to estimate coal resources using the kriging method at PT. Inti Bara Perdana, Taba Penanjung, Bengkulu. Geostatistical analysis was applied to evaluate spatial variability of coal quality parameters, including total moisture (TM), inherent moisture (IM), ash content (ASH), volatile matter (VM), fixed carbon (FC), and calorific value (CV). The research utilized drilling data with an average spacing of 80 meters. Variogram modeling was conducted using SGeMS software, employing spherical models to determine nugget, sill, and range parameters. The results show a low nugget effect (0%) indicating strong spatial continuity. The obtained ranges vary between 180–1296 meters depending on the parameter. Blo./ck kriging estimation was performed using block dimensions of 25 × 25 × 8 meters and a coal density of 1.3 ton/m³. The total estimated coal resource up to an elevation of 230 m is 253,500 tons. These findings demonstrate that kriging provides reliable resource estimation and supports mine planning optimization. This research contributes to improving coal resource evaluation accuracy and operational decision-making in open-pit mining.

Indonesia's territorial waters, encompassing the world's most strategically significant maritime chokepoints including the Malacca, Sunda, and Lombok Straits, face acute and escalating marine pollution threats from the dense vessel traffic that transits these corridors daily. This study evaluates the effectiveness of MARPOL Annex I–VI compliance enforcement in Indonesian waters, identifying systemic implementation gaps and proposing an optimized enforcement and early warning response model. Employing a qualitative research design with thematic analysis and documentary review, the study engaged marine environmental inspectors, port state control officers, maritime law academics, and environmental scientists as primary respondents. Findings reveal an overall MARPOL implementation effectiveness composite score of 3.89 out of 5.00, with Annex I (oil pollution) and Annex VI (air pollution) enforcement identified as the most critically deficient implementation domains. The research demonstrates that Indonesian MARPOL enforcement is constrained by inspection capacity limitations, inter-agency coordination failures, and inadequate pollution response infrastructure across outer island port jurisdictions. The study contributes an enforcement optimization model and early warning pollution response system framework for Indonesian maritime environmental governance, with direct implications for maritime professional education at STIP Jakarta.

This research aims to evaluate the effectiveness of Online Travel Agent (OTA) distribution channels in influencing room sales volume and net profit for hotels in Java. Although OTAs have become a primary distribution choice that successfully boosts sales figures, there is still a lack of research highlighting the impact on net profitability due to high commission costs.Using a quantitative associative method through panel data regression analysis, this study examines the causal relationship between the proportion of sales made via OTAs and two performance indicators over a two-year period (2021–2023). The primary findings reveal a dual effect:OTA Distribution Channels have a positive and significant influence on Room Sales Volume (supporting Hypothesis H1).Conversely, OTAs have a significant negative impact on Hotel Profit Margins (supporting Hypothesis H2), indicating a substantial financial trade-off.The contribution of this research is to provide balanced empirical evidence regarding volume gains versus margin losses resulting from OTA usage. The managerial implications suggested by these findings are that hotels need to implement distribution strategies focused on Net Revenue Management and channel mix optimization to achieve a balance between volume requirements and profitability.

The Indonesian hospitality industry is currently facing a post-pandemic "profitability paradox," a phenomenon where increased occupancy rates do not guarantee a proportional increase in net profit margins due to persistent operational cost inflation. This study aims to evaluate operational cost efficiency strategies and their impact on profitability across three star-rated hotels with contrasting locational and market characteristics: @Hom Hotel Kudus (Central Java), Grand Verona Samarinda (East Kalimantan), and FUGO Hotel Banjarmasin (South Kalimantan). This research adopts a descriptive qualitative approach with a comparative multiple-case study design. Data were collected through in-depth interviews with top management, participant observation, and financial document analysis. The results reveal that geographical characteristics and market segments are the primary determinants in selecting efficiency strategies. (1) Hom Hotel Kudus, located in a secondary industrial area, implements Lean Operations strategies through workforce multi-skilling to address market price sensitivity. (2) Grand Verona Samarinda, in the East Kalimantan business hub, focuses on Supply Chain Engineering by localizing raw materials to mitigate high logistical costs. (3) FUGO Hotel Banjarmasin, in the lifestyle segment, adopts Technology-Driven Efficiency to suppress utility costs without degrading the guest experience. The study concludes that sustainable profitability is achieved not through aggressive cost-cutting, but through strategic cost management adaptive to local contexts. These findings provide a new managerial framework for the hospitality industry to shift from a revenue-centric orientation to value optimization.

This study aims to evaluate the Quran Tahfidz program at Bahrul Hikmah Islamic Junior High School using the Context, Input, Process, and Product (CIPP) evaluation model introduced by Stufflebeam. The findings of the research are as follows: First, the evaluation of the context aspect indicates that the program objectives have been comprehensively formulated. Data analysis confirms that the program implementation is well-aligned with the established goals, placing it in the 'good' category. Second, the evaluation of the input component reveals that the managerial competence of the administrators and the pedagogical capabilities of the educators have met the expected standards. Nevertheless, the infrastructure aspects require further optimization to foster a more conducive learning environment for students. Third, regarding the process aspect, the program implementation has generally achieved the targeted outcomes. However, observations identified obstacles predominantly stemming from students' internal factors; this implies the crucial role of teachers in integrating motivational stimuli as a preventive measure against declining learning enthusiasm. Fourth, the product evaluation shows that the daily memorization targets are generally achieved, although some students require remedial sessions. Ultimately, students are capable of completing the memorization of three juz within the three-year period.

The objective of this activity is to foster a spirit of entrepreneurship among students by utilizing productive land on the STT Sabda Agung campus as an educational vegetable garden. This activity is designed to engage students actively and collaboratively throughout the entire agricultural cycle, from the planning stage, land preparation, planting various types of vegetables such as water spinach, mustard greens, and spinach, maintenance, to the harvesting and marketing of the produce. The primary focus of this activity is not only on the technical aspects of farming but also on character development, fostering independence, and enhancing students’ managerial skills in managing small-scale business units. The outcomes of this initiative demonstrate a significant increase in students’ interest and understanding of agriculture-based entrepreneurship, particularly regarding the utilization of backyard spaces. In addition to providing educational value, this land optimization has successfully transformed the campus area into a productive and aesthetically pleasing green space. As a result, students now possess practical skills that can serve as a foundation for future economic independence, particularly in the service sector. Through this integration of theory and practice, it is hoped that an innovative learning ecosystem will be created to foster the emergence of competent young entrepreneurs who are environmentally conscious.

The research entitled Service Quality in Handling Complaints of BPJS Kesehatan Participants in Jambi City aims to investigate the quality of BPJS Kesehatan services in handling participant complaints and identify improvement efforts that are carried out in a sustainable manner. This study uses a qualitative approach with a phenomenological design to understand participants' experiences, perceptions, and satisfaction levels in depth. Data was collected through interviews, observations, and documentation of participants and service officers, then analyzed through the stages of data reduction, data presentation, and conclusion drawing systematically. The results of the study show that the quality of service at BPJS Kesehatan Jambi City is relatively good, characterized by adequate facilities, relatively clear service procedures, information transparency, and high responsiveness of officers in following up on complaints. However, accessibility challenges are still found, especially for participants who have limitations in the use of digital technology and access to information. Improvement efforts such as the development of digital-based complaint channels, optimization of face-to-face services, improving officer competence, and consistently implementing standard operating procedures reflect the institution's commitment to improving the quality of public services effectively and sustainably.

This study aims to analyze the effect of competency synergy and training on performance with job satisfaction both at the Department of Women's Empowerment and Child Protection and Population Control and Family Planning of Pekalongan Regency directly and indirectly. The population used is the Department of Women's Empowerment and Child Protection and Population Control and Family Planning of Pekalongan Regency 160 people, with a sampling technique using the Slovin formula totaling 114 respondents. The data collection method was carried out by means of a questionnaire, the analysis technique used was PLS (Partial Least Square). The results of the study showed that competency synergy had a positive and significant effect on performance optimization and training had a positive and significant effect on performance optimization. Competency synergy had a positive and significant effect on job satisfaction, training had a positive and significant effect on job satisfaction, job satisfaction had a positive and significant effect on performance optimization. And job satisfaction can intervene the effect of competency synergy on performance optimization and job satisfaction can intervene the effect of technology utilization on performance optimization

Nabire Regency in Central Papua Province confronts significant geographical complexities in transportation system development, characterized by hilly topography and limited road infrastructure that impacts community mobility efficiency. This research analyzes road route optimization through Geographic Information System (GIS) approach using QGIS 3.28.3 software with QNEAT3 plugin for network analysis. The research methodology applies network analysis considering multiple parameters including travel distance, travel time, road surface conditions, slope gradients based on Digital Elevation Model (DEM), and impedance factors according to infrastructure quality. Spatial data were obtained from Geospatial Information Agency (BIG) and OpenStreetMap (OSM) with analysis focusing on 8 origin-destination pairs representing critical movements to health facilities, education centers, and economic hubs. Analysis results identified alternative routes demonstrating 12.5-20% travel time efficiency compared to existing routes, with an average optimization of 15.7%. Field validation confirmed model prediction accuracy with error rates below 8%. These research findings provide strategic recommendations for local government in sustainable transportation infrastructure planning that can enhance regional accessibility and support local economic development in the Central Papua region.

This study presents a comprehensive comparative analysis of four traditional machine learning algorithms Decision Tree, Random Forest, K-Nearest Neighbors, and Support Vector Machine for Android malware detection using the preprocessed TUANDROMD dataset comprising 4,465 instances and 241 features representing both static and dynamic application characteristics. Motivated by the limitations of conventional signature-based and hybrid detection methods, especially in managing imbalanced datasets and detecting emerging malware variants, the study employed SMOTE to ensure balanced training data and fair model evaluation. The dataset was divided into 80% training and 20% testing subsets, and models were assessed using key performance metrics including accuracy, precision, recall, F1-score, and ROC AUC. The findings revealed that the proposed Random Forest model outperformed the other classifiers, achieving an accuracy of 0.993, precision of 0.992, recall of 1.000, F1-score of 0.996, and a near-perfect ROC AUC of 0.9998 surpassing state-of-the-art approaches. These results affirm the superior predictive capability, consistency, and robustness of the Random Forest algorithm in Android malware detection. The study concludes that base models, when integrated with class-balancing techniques, provide reliable and efficient malware detection across imbalanced datasets. For future research, the study recommends exploring advanced hybrid or ensemble frameworks that integrate Random Forest with deep learning architectures or other meta-heuristic optimization techniques to further enhance detection accuracy, adaptability, and resilience against rapidly evolving Android malware threats.

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in economic development; however, their competitiveness is often constrained by weak branding and limited digital marketing capabilities. This community engagement program aimed to strengthen brand identity and digital capacity of the “Pukle” catfish cracker MSME in Karangsuwung Village, Cirebon Regency, through an integrated branding and sharia-based digital marketing approach. A participatory–collaborative method was employed, consisting of needs assessment, Workshops, technical mentoring, and monitoring and evaluation. The interventions included the development of brand identity elements (logo, tagline, and visual guidelines), improvement of informative packaging, activation and optimization of WhatsApp Business, and utilization of TikTok Shop as a social commerce channel. In addition, a standard operating procedure for sharia-compliant digital content based on the principles of shiddiq (truthfulness), amanah (trustworthiness), fathanah (competence), and tabligh (communicativeness) was formulated to enhance consumer trust. The results indicate improvements in product professionalism, digital channel management, content consistency, and customer interaction. The integration of branding and sharia digital marketing proved relevant in building differentiation, expanding market access, and strengthening long-term business reputation. The program highlights that MSME digital transformation requires capacity building, continuous mentoring, and ethical value integration to ensure sustainable competitiveness.

Copyright infringement in the music sector continues to be a significant issue in Indonesia, particularly when musical works are commercially used by business operators. Copyright law provides legal protection for creative works, including songs or music, by granting exclusive rights to control use and derive benefits from such creations. This research examines the legal analysis of copyright holders in compensation for royalty payments. The method used in this research is normative, supplemented by literature studies, including relevant regulations and previous research on song or music copyright. The research findings indicate that royalty payment is a legal obligation for every user of songs in commercial activities, and creators are entitled to such compensation. However, in the Mie Gacoan case in Bali, it is evident that the implementation of these provisions remains constrained due to weak legal understanding, supervision, and compliance, necessitating strengthened law enforcement and optimization of the role of collective management institutions.

Freshwater fish diseases significantly affect aquaculture productivity and economic sustainability, while accurate visual classification remains challenging due to interclass similarity and image variability. This study presents a comparative evaluation of three deep learning architectures—DenseNet201, ResNet50, and EfficientNetV2-S—using a stepwise optimization strategy combined with Gradient-weighted Class Activation Mapping (Grad-CAM) for freshwater fish disease classification. Models were trained through three phases: baseline, optimized, and fine-tuned. Performance was evaluated using accuracy, precision, recall, F1 score, Matthews correlation coefficient (MCC), Cohen’s kappa, and per-class ROC–AUC. Results show consistent performance improvement across all architectures, with EfficientNetV2-S achieving the highest accuracy (97.14%), followed by ResNet50 (96.11%) and DenseNet201 (94.40%). High ROC–AUC values (>0.98) indicate strong discriminative capability. Grad-CAM analysis confirms that all optimized models focus on biologically relevant lesion regions, enhancing model transparency and reliability.

Heart disease is the leading cause of death in Indonesia and globally, necessitating an early screening system that is both accurate and clinically trustworthy. Although XGBoost demonstrates high predictive performance, its black-box nature undermines clinical trust, while low recall risks missed diagnosis an unacceptable consequence in population screening, especially in middle-income countries with limited healthcare resources. This study aims to develop a sensitive, transparent, and implementation-ready heart disease screening framework through the integration of SHAP-based Explainable AI. The CDC's Indicators of Heart Disease dataset (319,795 samples) was processed according to WHO/CDC standards, followed by class imbalance handling, hyperparameter optimization using RandomizedSearchCV, evaluation based on metrics sensitive to minority classes (AUC, recall, F1-score, AUC-PR), and threshold tuning to maximize recall. The baseline model showed a very low recall of 12.18%. After optimization and threshold tuning at 0.10, the model achieved recall >96% (96.79%) with a G-mean of 0.7477, supported by SHAP interpretation stability and the ability to capture non-linear interactions between advanced age (AgeCategory_WHO) and poor general health (GenHealth). SHAP analysis confirmed the alignment of dominant features with medical evidence, and its visualizations provide transparent explanations for healthcare professionals indicating its potential implementation as an interpretable clinical decision support system.

Software Defined Network is a popular computer network concept today because of the ease of managing network traffic with the control plane. Massive internet usage makes web server services on SDN networks overloaded. There are many load balancing concepts to overcome this problem, one of which is implementing the K-NN algorithm. This study aims to maximize the performance of the K-NN algorithm on SDN networks by optimizing the K value using Grid Search Cross Validation, and adding server status selection logic based on the smallest disk if the server status calculated by K-NN has the same. All implementations of the load balancing concept in this study were created virtually using Open vSwitch and virtualbox. Testing was carried out using CPU, MEMORY, and DISK parameters sent by the server with the help of the psutils component. JMeter software was used for testing by sending data using the POST method. The data type is text/plain with a data size of 1MB, testing was carried out in stages with threads 100, 200, 300, 400. The test results showed that the performance of the K-NN algorithm was running optimally. There was no significant difference in the distribution of the load to the server, this made the optimization and addition of logic successful.

This research investigates intelligent cooling system design for main ship engines operating in tropical waters, integrating advanced machinery engineering with human factors to address thermal management challenges affecting engine performance, reliability, and crew operational effectiveness. Tropical maritime environments impose severe cooling demands through elevated seawater temperatures (28-32°C), high ambient conditions (28-35°C), and accelerated biofouling, reducing conventional cooling system effectiveness by 15-25% while increasing maintenance burdens and operational risks. Through qualitative analysis involving marine engineers, chief engineers with tropical operational experience, cooling system manufacturers, naval architects, automation specialists, and maritime training institutions, this study examines how intelligent cooling systems incorporating variable-speed pumps, adaptive control algorithms, predictive maintenance, and crew-centered interfaces can optimize thermal management while supporting effective human-machine collaboration. Results demonstrate that intelligent systems can reduce cooling energy consumption by 20-35%, improve temperature stability by 50-65%, extend maintenance intervals by 40-80%, and enhance crew situational awareness through intuitive monitoring interfaces, while requiring comprehensive training programs developing technical understanding and operational competencies. Key implementation challenges include control system complexity, sensor reliability in harsh marine environments, integration with existing engine management platforms, crew competency development requirements, and lifecycle cost justification. Findings reveal that successful intelligent cooling system implementation requires holistic sociotechnical approach addressing machinery engineering optimization, automation technology deployment, and human capability development through coordinated design and training strategies. This research contributes to marine engineering literature by providing integrated frameworks for intelligent system design incorporating machinery performance, automation capabilities, and human factors supporting operational excellence in tropical maritime operations.

The growth of the culinary industry requires small-scale food businesses to implement effective and efficient operational management. This study analyzes the optimization of operational management at Teen Canteen by examining the use of digital systems, staff performance, the implementation of Standard Operating Procedures (SOP), and operational constraints. A descriptive qualitative approach was employed, with data collected through semi-structured interviews and direct observation. The informant was purposively selected, namely the Head Bar, who is directly involved in daily operational activities. Data analysis was conducted using the Miles and Huberman model. The findings indicate that Teen Canteen’s operational management has not been optimally implemented due to the discontinuation of digital cashier systems, reliance on manual transaction and inventory records, and inconsistent SOP implementation. Although staff performance is generally adequate, issues related to discipline and service responsiveness remain. This study recommends reintroducing digital cashier systems and establishing written SOPs to improve operational effectiveness.

Background: Hand grip strength is an essential indicator of physical capacity and nutritional status that can identify obesity risk. Adipose tissue accumulation in central obesity contributes to decreased hand grip strength quality through impaired muscle force transmission. Previous studies showed inconsistent results regarding the relationship between waist circumference and hand grip strength, especially in populations with high physical activity. Objective: To analyze the relationship between waist circumference and hand grip strength in male construction workers with high physical activity in Medan City. Methods: This descriptive-analytic study with cross-sectional design involved 100 male construction workers aged 30-39 years selected using purposive sampling technique. Waist circumference was measured using measuring tape, while hand grip strength was measured using handgrip dynamometer. Data analysis used Chi-Square test with significance level α=0.05. Results: The majority of respondents had normal waist circumference (64%) with mode 70 cm and normal grip strength category (53%) with mode 41.7 kg. Chi-Square test showed significant relationship between waist circumference and hand grip strength (p=0.039). Conclusion: There is a significant relationship between waist circumference and hand grip strength in construction workers. High physical activity does not completely prevent central obesity, therefore nutritional management and health education programs are needed for optimization of body composition and muscle functional capacity.

This study is based on the need to develop a more effective concentrate ration for lactating dairy cows, as existing formulations in the field are greatly influenced by the availability of ingredients and varying quality. Therefore, this study focuses on optimizing concentrate in dairy cow feed rations to meet SNI standards, which include crude protein (CP), Total Digestible Nutrients (TDN), Calcium (Ca), and Phosphorus (P), with more efficient results in terms of price and nutrition. This study uses the Whale Optimization Algorithm (WOA) metaheuristic approach, which balances the exploration and exploitation processes in finding the best solution to optimization problems. This algorithm has fewer parameters than other metaheuristics such as GA, PSO, and DE. WOA runs naturally in continuous space without the need for genetic operators such as crossover and mutation. The dataset used contains types of dairy cow feed ingredients along with nutritional requirements and prices so that researchers can process the data into efficient feed concentrate that is suitable for lactating dairy cows.

The increasing demand for housing in tropical regions requires building materials that are fast to apply, environmentally friendly, and resilient to extreme climate conditions as well as disaster risks. Conventional interlocking bricks are often chosen for their ease of construction, yet they still face challenges such as moisture and early cracking. This study proposes the innovation of the Hybrid Living Green Brick, a combination of lightweight bricks made from rice husk ash and fly ash waste (FRCB) with a biological layer of cyanobacteria. FRCB improves compressive strength by approximately 30% with the addition of 5% rice husk ash, achieving 65 kg/cm², thereby meeting Class 50 requirements (≥50 kg/cm²) according to SNI-15-2094-2000. The incorporation of 3% cyanobacteria provides an additional though not significant strength improvement, while still within the Class 50 category. It also reduces brick weight by 4.3%, with further optimization potential through cyanobacteria integration, and lowers carbon emissions from the firing process. Cyanobacteria induce the formation of CaCO₃ layers that seal pores, reduce water absorption by an average of 10%, and provide self-healing properties for microcracks. Preliminary observations indicate that FRCB offers stable mechanical performance, while biological activity was observed on the 7th day with the formation of pale-white mineral layers continuing until the 28th day. This hybrid innovation shows potential to support sustainable and disaster-resilient tropical construction by combining the mechanical strength of waste-based materials with the biological durability of cyanobacteria against extreme climates. Despite challenges related to moisture control and production standardization, the Hybrid Living Green Brick concept opens new pathways for developing environmentally friendly construction materials that are more adaptive to disaster-prone tropical conditions.