Journal Title Equivalent: Jurnal Ilmiah Sosial Teknik DOI prefix 10.59261 by Crossref Frequency 6 Issues per year (February, April, June, August, October, December) ISSN Online (2775-0833) | Print (2775-0329) Editor in Chief Chiska Nova Harsela Publisher Politeknik Siber Cerdika Internasional Indexing - EBSCO - Google Scholar - Dimensions - Sinta - Garuda Citation Analysis - Google Scholar - Dimensions Equivalent: Jurnal Ilmiah Sosial Teknik is a medium of communication for researchers, academics, and practitioners from around the world covering issues such as Civil Engineering, Environmental Engineering, computer Engineering, Industrial Engineering, Chemical Engineering, Electrical Engineering, Social and Political Sciences, Education, Economics, Management, Sociology, Religion, Law that belong to the social and engineering context. Equivalent: Jurnal Ilmiah Sosial Teknik publishes comprehensive research articles and reviews by leading experts in the field. Selected articles that have high scientific achievements, provide important new knowledge, and are of high benefit for the public, and to contribute to a deeper understanding of the complex legal and social challenges facing contemporary societies. Equivalent: Jurnal Ilmiah Sosial Teknik accepts submissions throughout the year. Submissions are reviewed upon receipt. Published Manuscripts are written in standard English. This journal welcomes submissions all year round. Submissions are reviewed upon receipt. The manuscript template can be downloaded Here. <div style="box-sizing: border-box; -webkit-font-smoothing: antialiased; color: #4b566b; font-family: Montserrat, sans-serif; font-size: 16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial; text-align: justify;">
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Determinants of Mobile Banking Adoption Intention among Rural Non-Users in Indonesia: An Extended UTAUT Model
Background: This study examines the determinants of mobile banking adoption intention among rural non-users in Indonesia by applying an exended Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods: A cross-sectional survey was conducted among 397 rural smartphone owners aged 20–59 years who had never used mobile banking, selected through purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS, with 10,000 bootstrap subsamples and one-tailed significance tests. Results: The findings indicate that awareness, facilitating conditions, and performance expectancy exert positive and significant effects on behavioral intention, whereas technology anxiety exerts a significant and substantively meaningful negative effect (f² = 0.027). Perceived risk also shows a significant negative effect, but its effect size is negligible (f² = 0.016), indicating only a marginal practical contribution despite statistical significance. By contrast, effort expectancy and social influence do not show significant effects. The model explains a moderate proportion of variance in behavioral intention (R² = 0.568) and demonstrates an acceptable model fit (SRMR = 0.049). Conclusion: The results suggest that mobile banking adoption intention among rural non-users is shaped more by perceived usefulness and enabling conditions, with technology anxiety acting as the most practically important psychological barrier and perceived risk playing a comparatively minor role. In contrast, ease of use and social influence appear to be less decisive factors. These findings provide empirical support for inclusion-oriented outreach strategies that prioritize anxiety reduction and confidence building, alongside clear value communication and structured onboarding support.
Copyright (c) 2026 Hendra Prabha, Anderes Gui https://creativecommons.org/licenses/by-sa/4.0
NIST SP 800-34-Based Disaster Recovery Plan Framework for the National Committee for Sharia Economics
Background: In today’s digital era, information technology (IT) infrastructure is critical to organizational operations, making Disaster Recovery Planning (DRP) essential for business continuity. Institutions managing strategic data assets, such as KNEKS, must address risks from disasters, cyberattacks, and infrastructure failures during PDES development. Objective: This study aims to identify KNEKS’s disaster recovery requirements under current and future PDES conditions and to develop a comprehensive DRP framework based on NIST SP 800-34. Methods: A qualitative case study approach was employed using NIST SP 800-34 Rev. 1 as the primary framework, complemented by FIPS 199, SNI ISO 31000, and NIST SP 800-53. Data were collected through semi-structured interviews with IT managers and system administrators, supported by document analysis. Triangulation and member checking were used to ensure validity. Results: The assessment revealed significant gaps in disaster recovery readiness, particularly in formalized policies, technical redundancy, and impact analysis procedures. Based on these findings, a tailored DRP framework was developed, incorporating activation, recovery, and reconstitution phases while maintaining scalability for future PDES expansion. Conclusion: A comprehensive NIST SP 800-34-based DRP is essential to ensure KNEKS’s operational continuity. The proposed framework offers a structured and scalable approach to disaster recovery and provides a practical model for emerging public-sector, data-intensive institutions.
Copyright (c) 2026 Khalil Mojadidi, Abba Suganda Girsang https://creativecommons.org/licenses/by-sa/4.0
AHP-SERVPERF Assessment of Five-Star Hotel Service Quality Using TripAdvisor Reviews in Surabaya
Background: Conventional SERVPERF-based hotel service quality assessments often rely on questionnaires, which may lead to midpoint bias, limited engagement, and subjective interpretation. Therefore, online customer reviews offer an alternative data source for capturing authentic service experiences. Objective: This study aims to evaluate service quality in five-star hotels in Surabaya by integrating SERVPERF, Analytical Hierarchy Process (AHP), text mining, sentiment analysis, and the 2-tuple linguistic model. Methods: A total of 1,200 TripAdvisor reviews from five five-star hotels in Surabaya were collected and analyzed. Expert judgments were obtained through AHP to determine the weight of each SERVPERF dimension. Review texts were segmented, classified into SERVPERF dimensions using a Large Language Model, and analyzed using TextBlob sentiment polarity. The results were then integrated into the 2-tuple linguistic model. Results: Tangibles was the most frequently discussed and most positively perceived dimension in customer reviews. However, Reliability received the highest expert-based AHP weight and became the most influential dimension after weighted SERVPERF scoring, followed by Responsiveness, Assurance, Empathy, and Tangibles. Conclusion: The proposed hybrid model provides a more comprehensive and data-driven approach to hotel service quality assessment by combining authentic customer reviews with expert-based weighting. This method helps hotel managers identify priority areas for service improvement more objectively.
Copyright (c) 2026 Keisya Tifany, Agustinus Nugroho, Adrie Oktavio, Fabiola Leoparjo https://creativecommons.org/licenses/by-sa/4.0
The Effect of Octane Booster and Nitro Race Additives on Engine Performance and Fuel Consumption of 110 CC Motorcycle Engine: An Experimental Approach
Background: Fuel quality and combustion characteristics are important factors that influence engine performance and fuel efficiency in spark-ignition engines. The use of fuel additives is one method commonly applied to improve combustion quality. Objective: This study evaluated the comparative effects of STP Octane Booster and Nitro Race additives on the engine performance and fuel consumption of a Honda Scoopy 110 cc motorcycle. Methods: A quantitative experimental method was employed using a 2022 Honda Scoopy 110 cc engine. Pertalite (RON 90) and Pertamax Turbo (RON 98) were blended with both additives at five concentration levels (5–25 ml/L). Performance parameters, including torque, power, fuel consumption, specific fuel consumption (SFC), and thermal efficiency, were measured using a chassis dynamometer. Results: Higher additive concentrations consistently increased torque and effective power while reducing fuel consumption and SFC. The combination of STP Octane Booster and Pertamax Turbo yielded the best overall performance among all tested mixtures. Conclusion: STP Octane Booster combined with high-octane fuel positively improved combustion quality and engine performance. These findings suggest that commercially available octane boosters can serve as a cost-effective approach to optimizing fuel efficiency in small motorcycle engines.
Copyright (c) 2026 Darmulia Darmulia, Obet Ranteallo https://creativecommons.org/licenses/by-sa/4.0
Sustainable Competitive Advantage in the Class C Hospital Industry: A Qualitative Study of Strategic Factors in the Tapal Kuda Region of East Java
Background: The healthcare industry is rapidly changing due to technological advancement, policy reform, rising patient expectations, and institutional competition. Class C hospitals in regional areas such as the Tapal Kuda region of East Java face challenges in sustaining competitiveness amid limited resources and dynamic healthcare demands. However, studies on sustainable competitive advantage in the Class C Hospital remain limited. Objective: This study aims to analyze the strategic factors influencing sustainable competitive advantage in Class C hospitals in the Tapal Kuda region of East Java. Methods: This study used a qualitative, descriptive-exploratory approach. Data were collected through semi-structured interviews with eight key informants from four Class C hospitals, including hospital directors, heads of medical services, nursing managers, and healthcare administrators. Field observations and institutional document reviews were also conducted. Informants were selected through purposive sampling, and data were analyzed thematically through data reduction, data display, interpretation, and conclusion drawing. Results: The findings identified six strategic dimensions influencing sustainable competitive advantage: digital transformation, technological innovation, organizational resilience, adaptive leadership, human resource competence, and a patient-centered organizational culture. Electronic medical records and telemedicine were identified as important tools for improving service efficiency, while regional socioeconomic disparities, limited specialist availability, and infrastructure gaps constrained hospital competitiveness. Conclusion: Sustainable competitive advantage in Class C hospitals is multidimensional and depends on organizational adaptability, innovation capability, strategic flexibility, and contextual responsiveness. Hospitals that integrate technology, develop competent human resources, and implement patient-centered services are more likely to achieve long-term sustainability and competitiveness.
Copyright (c) 2026 Siti Asiyah Anggraeni, Fendy Suhariadi, Fiona Niska Dinda Nadia https://creativecommons.org/licenses/by-sa/4.0
Cost and Time Efficiency Comparison of RISHA and Conventional Construction for Type 36 Post-Disaster Housing in Rua Village, Ternate
Background: The increasing demand for rapid, affordable, and reliable housing has encouraged innovation in construction methods, including the RISHA modular system. However, its cost and time efficiency compared with conventional construction remain debated, especially in post-disaster and remote areas. Objective: This study aims to compare the construction costs and implementation time of the RISHA (Rumah Instan Sederhana Sehat) modular construction method and the conventional construction method for a Type 36 single-story house. Methods: This research employed a comparative quantitative approach. Data analysis included: (1) calculating work volume for each work category, (2) conducting unit price analysis based on the Ministry of Public Works and Housing’s Standard Unit Price Analysis (Analisis Harga Satuan Pekerjaan, AHSP) and Regional Standard Unit Prices (Harga Satuan Pokok Kegiatan, HSPK), (3) preparing the Cost Budget Plan (Rencana Anggaran Biaya, RAB), and (4) calculating implementation time using the work coefficient method. Results: The results show that the RISHA method required a total cost of IDR 167,918,089.00 and an implementation duration of 56 working days, or 8 weeks. Meanwhile, the conventional method incurred a cost of IDR 172,562,093.00 and required 75 working days, or 11 weeks. Thus, RISHA construction provided cost savings of 2.69% and time efficiency of 25% compared with the conventional method. Although the cost of the RISHA superstructure was higher due to the use of precast components, significant savings in foundation and wall work, along with an accelerated construction timeline, made RISHA a more efficient overall alternative. Conclusion: Therefore, it can be concluded that the RISHA method offers advantages in cost and time efficiency for constructing a simple Type 36 house in the context of this study.
Copyright (c) 2026 Rais D. Hi Yusuf, Joni Hermanto, Muhammad Yusri Abdul Gani https://creativecommons.org/licenses/by-sa/4.0
Failure Mechanism Analysis of 253MA Vortex Finder in A CFB Boiler Under High-Temperature Erosion and Refractory Deposit Exposure
Background: Circulating fluidized bed (CFB) boilers are widely applied in coal-fired power plants due to their fuel flexibility and low emissions. The vortex finder, a key cyclone component, separates solid particles from flue gas and is prone to wear under high-temperature, erosive conditions. Objective: This study aims to identify failure characteristics, analyze the causes, and explain the failure mechanism of a 253MA vortex finder in a 2 × 100 MW CFB boiler at PLTU Sebalang after 6,548 operating hours at 850–950°C. Methods: A multi-method approach was employed, including visual inspection, positive material identification (PMI), tensile testing, microhardness testing, optical microscopy, scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and X-ray diffraction (XRD) analysis to assess mechanical and microstructural degradation. Results: The vortex finder exhibited plastic deformation, material thinning, and deposition of foreign refractory material. Tensile strength decreased from 723.89 MPa to 677.84 MPa (6.36%), elongation decreased from 58% to 53%, and hardness decreased from 218.84 HV to 210.21 HV. Microstructural changes included grain coarsening and carbide precipitation, while SEM-EDS revealed surface roughening, early microcrack initiation, and compositional changes indicative of high-temperature oxidation. XRD confirmed that the deposits consisted of alumina–silica refractory material. Conclusion: Failure resulted from a synergistic mechanism involving high-velocity particle erosion, refractory deposit accumulation, and progressive microstructural degradation. Crack initiation and propagation ultimately led to structural failure. Recommendations include implementing erosion control measures, maintaining refractory linings, applying more erosion-resistant coatings or alternative materials, and adopting condition-based inspection strategies to enhance component reliability.
Copyright (c) 2026 Martua Haposan Echo Sihite, Kusmono Kusmono https://creativecommons.org/licenses/by-sa/4.0
An Integrated XGBoost-PSO Framework for Automated Cyber Risk Identification Based on ISO/IEC 27005:2022
Background: The main problem in cybersecurity risk management is that the risk identification process remains manual, time-consuming, and difficult to connect with technical detection results, business contexts, and information security standards. Objective: This study aims to develop a cybersecurity risk identification and management system based on the integration of machine learning and ontology using the ISO/IEC 27005:2022 approach. Methods: This study employed the Design Science Research (DSR) approach to design the Cyber Risk Intelligent System (CRIS). The system integrated machine learning algorithms, feature optimization, model interpretability, and cyber risk ontology. The classification model was developed using XGBoost with Particle Swarm Optimization (PSO)-based feature selection and was evaluated using accuracy, precision, recall, and F1-score metrics. Furthermore, an ISO/IEC 27005:2022-based ontology was used to map threats, vulnerabilities, impacts, and security control recommendations based on ISO/IEC 27002. Results: The results showed that the combination of XGBoost and PSO provided the best classification performance compared with other methods, achieving an F1-score of 0.9672, precision of 0.9661, recall of 0.9684, accuracy of 96.48%, and an ROC-AUC of 0.9891. The implementation of SHAP successfully improved model interpretability by identifying the dominant features that influenced cyber threat prediction. Ontology integration also enabled the risk identification and recommendation process to be carried out automatically, consistently, and in alignment with international standards. Conclusion: This study contributes to the development of an adaptive and structured cyber risk decision-support system that supports the automation of information security risk management in digital organizational environments.
Copyright (c) 2026 Diaz Samba Prayogi, Agung Triayudi https://creativecommons.org/licenses/by-sa/4.0
Scenario-Based Risk and Control Formulation for Electronic Banking Channels ATM and EDC in Indonesian Commercial Banks
Background: ATMs and EDCs remain critical infrastructure components within Indonesia’s national payment system. However, their extensive utilization exposes commercial banks to various technological, operational, human, physical, and third-party risks. Despite recurring incidents comprehensive studies that formulate ATM and EDC risk scenarios and corresponding control measures within the Indonesian banking context remain limited. Objective: This study formulates risk scenarios and corresponding control measures for ATM and EDC electronic banking channels in Indonesian commercial banks. Methods: A structured literature review was conducted using six academic databases: Google Scholar, ScienceDirect, ResearchGate, Scopus, Wiley Online Library, and MDPI. The identified risks were analyzed using the ISACA Risk IT Framework and mapped to the NIST Cybersecurity Framework (CSF) 2.0 and ISO/IEC 27001:2022 standards. The proposed model was validated by six Subject Matter Experts (SMEs) with expertise in banking operations, IT risk management, information security, and payment systems using a 1–5 Likert scale. Results: The study identified 25 risk scenarios across six categories and formulated 25 consolidated control measures. Each scenario links risk sources or threat actors, risk events, potential impacts, and corresponding controls. The controls were classified as preventive, detective, and corrective measures and mapped across the people, process, and technology dimensions. Expert validation produced an average score of 4.13/5.00 (83%), indicating a high level of acceptance. Conclusion: As a proposed model derived from a systematic literature review and expert validation, this study provides a structured reference framework for risk management practitioners and policymakers in Indonesian commercial banking institutions.
Copyright (c) 2026 Navya Kirana Safitri, Sinung Suakanto, Basuki Rahmad https://creativecommons.org/licenses/by-sa/4.0
Capacitor Bank Placement Enhancement Using Grey Wolf Algorithm for Reducing Harmonics in Low-Voltage Radial Distribution Networks
Background: Low-voltage distribution systems are increasingly affected by harmonic distortion due to nonlinear loads, leading to power losses, reduced efficiency, and poor power quality. Capacitor banks are commonly used for reactive power compensation; however, improper placement may worsen harmonic conditions due to resonance effects. Objective: This study aims to optimize capacitor bank placement in a low-voltage radial distribution system while improving power quality and minimizing harmonic distortion using the Grey Wolf Optimizer (GWO). Method: A quantitative, simulation-based approach was applied using a 12-bus radial distribution model of an integrated laboratory system. Power flow analysis was conducted using the Backward/Forward Sweep (BFS) method, while optimization of capacitor placement and sizing was performed using the Grey Wolf Optimizer (GWO), considering multi-objective criteria including power loss, total harmonic distortion of current (THDI), total harmonic distortion of voltage (THDV), and power factor. Result: The proposed GWO allocated a total of 1000 kVAr across selected buses, resulting in a 4.41% reduction in active power loss, a decrease in THDV from 6.181% to 1.517%, and an improvement in power factor to unity (1.0 pu). However, THDI remained at 18.71%, exceeding IEEE 519-2014 limits, indicating the need for additional harmonic filtering solutions. Conclusion: The Grey Wolf Optimizer (GWO) is effective for optimizing capacitor placement and improving voltage-related power quality. However, additional harmonic mitigation techniques are required to comprehensively address current distortion.
Copyright (c) 2026 Happy Aprillia, Oik Rizki Septianto, Barokatun Hasanah, Suratno Suratno https://creativecommons.org/licenses/by-sa/4.0
Dinamika Hidrologi Sistem Sungai Tawang-Kapuas dan Implikasinya terhadap Kebijakan Konservasi Lanskap Danau Sentarum
Latar belakang: Lanskap Daerah Tangkapan Air Danau Sentarum memiliki peran strategis dalam menjaga stabilitas hidrologi di Kalimantan Barat melalui fungsinya dalam mengatur aliran air yang masuk ke Sungai Kapuas. Tujuan: Penelitian ini bertujuan menganalisis variasi temporal debit Sungai Tawang sebagai saluran utama yang menghubungkan sistem danau Danau Sentarum dengan Sungai Kapuas sepanjang tahun 2024. Metode: Pengukuran debit sesaat dilakukan setiap minggu pada dua titik pemantauan tetap menggunakan metode velocity-area. Kecepatan aliran permukaan dan profil kedalaman diukur pada sepuluh subseksi setiap transek, kemudian kecepatan permukaan dikonversi menjadi kecepatan rata-rata menggunakan faktor koreksi 0,85. Hasil: Hasil penelitian menunjukkan bahwa debit sesaat mingguan Sungai Tawang berfluktuasi antara 163,9 hingga 793,6 m³/detik dengan rata-rata 483,9 m³/detik, sedangkan debit sesaat Sungai Kapuas berkisar antara 711,0 hingga 2.536,4 m³/detik dengan rata-rata 1.311,1 m³/detik. Meskipun kontribusi rata-rata debit mingguan Sungai Tawang terhadap debit Sungai Kapuas sebesar 36,3% masih sejalan dengan estimasi Klepper (1994) yang berkisar antara 30–50%, penelitian ini mengungkap variabilitas temporal yang lebih dinamis, dengan kontribusi yang berfluktuasi antara 12,7–64,1%. Selain itu, ditemukan fenomena aliran dua arah (reverse flow), yaitu aliran dari Sungai Kapuas menuju Sungai Tawang, dengan debit masuk berkisar antara 45,7 hingga 438,0 m³/detik. Kesimpulan: Variasi kontribusi debit Sungai Tawang terhadap Sungai Kapuas yang lebih dinamis dibandingkan laporan sebelumnya mengindikasikan potensi perubahan dinamika hidrologi di lanskap Danau Sentarum. Temuan ini menjadi dasar penting bagi evaluasi daya dukung lingkungan dan penyusunan strategi konservasi adaptif untuk menjaga stabilitas hidrologi jangka panjang.
Copyright (c) 2026 Indra Kumara, Rinekso Soekmadi, Lilik B. Prasetyo, Arzyana Sunkar, Dwi Kusharyono https://creativecommons.org/licenses/by-sa/4.0
Road Safety Study in Accident-Prone Areas on the Gading - Playen and Yogyakarta - Barongan Road Sections
Background: The background of this research stems from the high number of accidents occurring on this road section, which endangers the safety of road users. Objective: This study aims to analyze traffic safety on two road sections with high accident rates, namely the Gading–Playen Road and the Yogyakarta–Barongan Road. Methods: The research methods employed include field surveys, collection of primary and secondary data, and statistical analysis using the CUSUM method and the V/C (volume-to-capacity) ratio. Results: The analysis revealed Gading–Playen Road section has a capacity of 3,354 pcu/hour with a V/C ratio of 0.196, indicating stable traffic conditions, while the Yogyakarta–Barongan Road section has a capacity of 3,444 pcu/hour with a V/C ratio of 0.771, reflecting near-saturated traffic conditions and a higher-risk situation. Z-score analysis of accident data from 2016 to 2019 showed a sharp spike on the Yogyakarta–Barongan section in the third period (z = +1.55), while the Gading–Playen section recorded a significant decline (z = −1.13). Accidents on both sections predominantly involve motorcycle users and male victims aged 16–25 years, and are primarily caused by undisciplined driving behavior. Key recommendations include geometric road improvements, installation of adequate traffic signs, improved road lighting, and strengthened enforcement of traffic regulations. Conclusion: The integration of CUSUM, Z score, and V/C ratio methods provides an effective framework for identifying and assessing traffic accident risks. The findings reveal distinct risk characteristics between road sections, requiring targeted interventions based on geometric conditions, traffic intensity, and behavioral factors.
Copyright (c) 2026 Raafi Widyaputra Yulianyahya, Ghefra Rizkan Gaffara , Ansadilla Niar Sitanggang, Irma Damayantie https://creativecommons.org/licenses/by-sa/4.0
Influence of Socio-Economic Characteristic on Travel Behaviour in Malang City
Background: Rapid urbanization and economic growth in Malang City have significantly influenced urban mobility patterns, increasing dependence on private vehicles and reshaping commuting behavior. Understanding the socio-economic determinants of travel behavior is therefore essential for sustainable transport planning in secondary cities in Indonesia. Objective: This study analyzes the relationship between socio-economic factors (such as age, income, education, occupation, gender, household size, and vehicle ownership) and daily travel behavior in Malang City, including trip frequency, trip purpose, and transport mode choice. Methods: A quantitative cross-sectional design was applied using a structured questionnaire distributed to 200 households selected through non-probability sampling. The data were analyzed using descriptive statistics and stepwise multiple linear regression to examine the effects of socio-economic variables on different dimensions of travel behavior. Results: Education was the only significant predictor of trip frequency (B = 0.081, p < 0.001; R² = 0.140). For trip purpose, the model demonstrated strong explanatory power (R² = 0.610, F = 50.300, p < 0.001), with occupation (β = 0.706, p < 0.001), education (β = 0.132, p = 0.006), and income (β = −0.107, p = 0.021) identified as significant determinants. However, none of the socio-economic variables significantly influenced transport mode choice (R² = 0.010, p = 0.931), indicating that infrastructure conditions and transport service availability may play a more dominant role in determining mode selection. Conclusion: Socio-economic factors influence travel behavior differently across various dimensions. While these factors significantly affect trip frequency and trip purpose, they do not determine transport mode choice.
Copyright (c) 2026 Taufikkurrahman Taufikkurrahman, Pratikso Pratikso, Kartono Wibowo https://creativecommons.org/licenses/by-sa/4.0
Reconstituting Social License to Operate: TGI's Response to the Grissik–Duri Gas Pipeline Incident
Background: The gas pipeline leak incident on the Grissik–Duri (GD) KP222 line in Selensen, Kemuning District, Indragiri Hilir Regency, Riau, on January 2, 2026, caused a technical, social, and operational crisis that had the potential to affect PT Transportasi Gas Indonesia's (TGI) Social License to Operate (SLO). Objective: This study analyzed how TGI's SLO was reconstituted after the incident by comparing the effectiveness of technical mitigation and social resolution and examining their implications for the company's social legitimacy. Methods: Using a qualitative case study design, the analysis drew on twelve publicly available documents published between January and April 2026, comprising national media reports, sectoral energy news coverage, and government releases selected based on their direct relevance to the incident chronology, response, and recovery. Data were analyzed thematically through data reduction, narrative display, and conclusion drawing, with credibility strengthened through source triangulation. Results: TGI managed the technical crisis by closing the safety valves, extinguishing the fire within approximately 13 hours, restoring operations within six days, and completing pipeline integrity testing before restarting operations. Socially, the company and relevant stakeholders conducted victim assistance, community consultations, and compensation processes. However, technical success and procedural settlements have not guaranteed sustainable public trust recovery. Conclusion: TGI's post-incident SLO position remains closer to vulnerable acceptance than approval. This study extends the application of SLO theory to post-incident energy infrastructure management and emphasizes the need to integrate measurable social indicators into oil and gas crisis-management systems to sustain legitimacy and operational continuity.
Copyright (c) 2026 Sahat Parlindungan Simarmata https://creativecommons.org/licenses/by-sa/4.0
Life Cycle Cost of Eco-Friendly Building Materials in Office Buildings: Supporting GBCI Greenship Certification
Background: Indonesia’s construction sector faces challenges in reducing environmental impacts while maintaining the economic feasibility of projects. Objective: This study aims to analyze the life cycle cost (LCC) of environmentally friendly materials used in office building envelope components and evaluate their contribution to achieving points in the Green Building Council Indonesia (GBCI) Greenship certification system. Methods: A quantitative comparative case study approach was employed on a five-story office building in Jakarta, with an analysis period of 30 years and a discount rate of 8%. The evaluated components included wall systems, concrete structures, and façade glazing, comparing conventional materials with environmentally friendly alternatives such as autoclaved aerated concrete (AAC) blocks, geopolymer concrete, and low-emissivity (low-e) glass. The data were analyzed using the LCC equation and supplemented with sensitivity analyses of discount rates and energy price variations. Results: The results showed that although the initial costs of environmentally friendly materials were 12–18% higher, the total LCC over 30 years was 9.5–9.8% lower than that of conventional materials. The cost break-even point occurred between the 9th and 11th years. Furthermore, the application of these materials contributed six points to the Material Resources and Cycle category in the GBCI Greenship v1.2 rating system. Conclusion: This study concludes that the LCC approach can serve as a basis for rational decision-making to encourage the adoption of green building materials in Indonesia.
Copyright (c) 2026 Asep Suhana, Hetty Fadriani, Handoko Subawi https://creativecommons.org/licenses/by-sa/4.0
Field Data Integrated Vehicle Routing Optimization Using Greedy Allocation, NNH, and 2-Opt for Landfill Waste Collection
Background: Inefficient waste collection practices in urban areas lead to excessive vehicle trips, increased fuel consumption, and unnecessary greenhouse gas emissions. Landfill operations face challenges in route planning because deploying IoT sensors across large and harsh environments is often impractical. Objective: This study proposes a field-data-integrated vehicle routing optimization framework for landfill waste collection that combines greedy allocation, the nearest neighbor heuristic (NNH), and 2-opt local search to minimize travel distance and fuel consumption. Methods: A priority-based capacitated vehicle routing problem (CVRP) model was developed using fill level, waste tonnage, and proximity to the depot as weighted scoring factors within a Design Science Research (DSR) framework, using operational data from 15 landfill drop points in Cakung Barat, East Jakarta. Results: The optimized approach reduced total travel distance by 7.0% and fuel consumption by 7.5% compared with the sequential baseline, while maintaining full service coverage and identical vehicle utilization at 73.2%. A paired t-test confirmed the statistical significance of the improvement (p = 0.038). Conclusion: Field-reported operational data, integrated with multifactor priority scoring and spatial optimization heuristics, provides a practical, cost-effective, and scalable alternative to sensor-based monitoring for landfill waste collection routing.
Copyright (c) 2026 Agnan Zakariya, Suryadiputra Liawatimena https://creativecommons.org/licenses/by-sa/4.0
A Theoretical Framework and 38-Feature Taxonomy for Behavioral Fraud Detection in Digital Banking
Background: Traditional rule-based systems are increasingly inadequate for addressing dynamic financial threats because of their reactive nature and susceptibility to concept drift. At PT XYZ, this vulnerability resulted in a sharp decline in fraud prevention effectiveness, from 90.4% in 2022 to 75.3% in 2025, leaving a critical 24.7% security gap. Objective: This study aimed to develop a behavioral fraud detection framework for digital banking by integrating a 38-feature account-level taxonomy with Isolation Forest, LightGBM, CatBoost, and the Synthetic Minority Over-sampling Technique (SMOTE) to overcome the limitations of legacy rule-based systems. Methods: The study established a proactive theoretical framework using the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to shift from transaction-level monitoring to holistic account-level behavioral profiling. Central to this approach was a 38-feature taxonomy that integrated statistical aggregates, temporal signatures, velocity flags, and volume metrics to map the behavioral “fingerprint” of at-risk accounts. Results: Empirical testing on 402 unique accounts confirmed that the proposed architecture successfully closed the identified 24.7% security gap. Both the LightGBM and CatBoost classifiers achieved a perfect recall score of 1.0000 and an accuracy of 0.9972. LightGBM emerged as the best-performing model, with a receiver operating characteristic area under the curve (ROC AUC) of 0.9996, significantly outperforming traditional logistic regression. Conclusion: The proposed framework effectively improved fraud detection by combining behavioral profiling, hybrid anomaly detection, and balanced ensemble learning. LightGBM and CatBoost achieved 99.72% accuracy, 100% recall, and a 99.96% ROC AUC, demonstrating a practical and explainable approach to proactive digital banking fraud detection.
Copyright (c) 2026 Ardi Darmawan, Thoyyibah T https://creativecommons.org/licenses/by-sa/4.0
Digital Transformation and Operational Performance in Manufacturing: A Systematic Literature Review and Industry-Specific Recommendation Matrix
Background: Digital transformation has become a key driving force in improving operational performance in the global manufacturing industry. Objectives: This study aims to (1) describe the existing empirical evidence regarding the impact of digital transformation on operational performance in the manufacturing industry and (2) provide recommendations for developing appropriate digital transformation strategies based on the characteristics of different manufacturing industry types. Methods: This study employed a qualitative research design using a systematic literature review approach. Following the PRISMA protocol, 17 articles published between 2015 and 2025 were retrieved from Scopus, Web of Science, and Google Scholar. The selected studies were analyzed using thematic synthesis and coded categorization to identify recurring patterns, technological trends, and industry-specific transformation outcomes. Results: All reviewed studies reported positive impacts of digital transformation on operational performance, with Big Data Analytics and Artificial Intelligence emerging as the dominant technologies. Benefits varied across manufacturing sectors. Discrete manufacturing achieved faster and more measurable improvements, whereas process manufacturing sectors, including pharmaceuticals, agri-food, and semiconductors, experienced longer implementation pathways because of regulatory requirements, biological constraints, and human adoption challenges. Among the 17 studies, Big Data Analytics appeared in 13 articles and Artificial Intelligence in 12, confirming their central role in enhancing manufacturing operations. Conclusions: Based on these findings, this study proposes a five-category recommendation matrix for digital transformation strategies tailored to different manufacturing industry characteristics. This matrix represents the study’s primary practical contribution by providing industry-oriented guidance for organizations seeking to optimize operational performance through digital transformation initiatives.
Copyright (c) 2026 Riyanti Hamdani, Wirawan Endro Dwi Radianto, David Sukardi Kodrat https://creativecommons.org/licenses/by-sa/4.0