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Web-Based E-Procurement Development in Regional-Owned Enterprises (BUMD): An R&D Approach Sutisna, Nandang; Abdul Rahman, Titik Khawa
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1374

Abstract

This study presents the design, development, and evaluation of a web-based e-procurement system tailored to the institutional needs of a Regional-Owned Enterprise (BUMD), with a case implementation at PDAM Tirta Kahuripan. Employing a Research and Development (R&D) methodology and assessed using ISO/IEC 25010 standards, the system integrates six core procurement modules—e-Planning, e-Budgeting, e-Preparation, e-Sourcing, e-Contracting, and e-Inventory—alongside a Vendor Management System (VMS) to enhance procurement transparency and supplier accountability. System testing involved both quantitative and qualitative assessments. Functionality and reliability achieved perfect scores (100%), usability scored 79 based on a System Usability Scale (SUS) survey completed by 20 procurement personnel, and maintainability recorded a moderate index of 82.85 based on PHP Metrics analysis. Efficiency testing using GTMetrix resulted in a Grade C, indicating areas for performance optimization. These findings demonstrate that the system is both technically robust and operationally relevant, offering a replicable model for digital procurement reform in decentralized public institutions. The study contributes to interdisciplinary knowledge across software engineering, public sector management, and procurement governance, with implications for future integration, scalability, and policy adoption in similar institutional contexts.
Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes Wiliani, Ninuk; Abdul Rahman, Titik Khawa; Ramli, Suzaimah
Journal of Applied Research In Computer Science and Information Systems Vol. 2 No. 2 (2024): December 2024
Publisher : PT. BERBAGI TEKNOLOGI SEMESTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61098/jarcis.v2i2.200

Abstract

The growing utilization of solar panels as a renewable energy source requires efficient maintenance solutions to guarantee their best functioning. Identifying and categorizing faults on solar panel surfaces is essential for maintenance, as these defects considerably affect energy output and system efficiency. This study investigates the utilization of statistical feature extraction methods alongside Bernoulli Naive Bayes (BNB) and Gaussian Naive Bayes (GNB) algorithms to categorize different defect types, such as cracks, scratches, spots, and non-defective surfaces, through digital image analysis. Statistical criteria, including recall, specificity, and area under the curve (AUC), are employed to assess model performance. The findings indicate that the GNB algorithm surpasses BNB, with a mean average precision (mAP) of 39.83% with an 85:15 training-test ratio, whereas BNB reaches a maximum mAP of 29.25% at a 90:10 ratio. Nonetheless, both models demonstrate constraints in precision, as indicated by a total AUC of 0.644. This work illustrates the potential of statistical feature extraction approaches for defect classification, while emphasizing the necessity for future improvements to boost the efficacy of feature extraction and classification techniques in practical applications
The Measurement and Evaluation of Information System Success Based on Organizational Hierarchical Culture Haerani, Reni; Abdul Rahman, Titik Khawa; Kamelia, Lia
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this study, the adoption of the Delone & McLean information system success model and its adaptation using the organizational hierarchy culture theory is used to explore the state of information system success and examine the factors that suggest success. This research was conducted at universities in Banten Province, which currently rely on information systems in many ways, especially those related to university management. By measuring the evaluation of the success of information systems and the hierarchical culture in organizations using a model that the researcher built according to the integration of 2 models. The results the measurement of the success of information systems were obtained from distributing questionnaires, there were still 85 (63%) respondents, and 84 (61.3%) were satisfied with the performance of the information system success model. The least squares structural equation modeling analysis (PLS-SEM) was then applied due to the sample size. The previous stage consisted of evaluating the reflective measurement model in evaluating the reliability of internal consistency using Composite Reliability, Reliability indicators, Convergent Validity and Discriminant Validity, finally it was concluded that the success of information system by hierarchical culture integration model in the organization on could be passed on the more complex research terms, especially using samples, and different questionnaires.
Integrating multi-criteria decision making and public sentiment analysis for sustainable urban green space planning S. Kuba, Muhammad Syafaat; Faisal, Muhammad; Nurnawaty, Nurnawaty; Abdul Rahman, Titik Khawa; Syamsuri, Andi Makbul; Hayat, Muhyiddin AM; Bakti, Rizki Yusliana
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.11168

Abstract

Sustainable planning of green open spaces (GOS) requires decision-making models that combine expert evaluation with public input. This study proposes a novel hybrid framework that integrates multi-criteria group decision making (MCGDM) with public sentiment analysis to support community-based and data-driven urban planning. The workflow consists of evaluating 25 community-proposed GOS locations using stepwise weight assessment ratio analysis (SWARA) for criteria weighting and MABAC-BORDA for multi-criteria ranking, resulting in 11 feasible alternatives. To incorporate community perspectives, a term frequency-inverse document frequency-support vector machine (TF-IDF–SVM) classifier was applied to 1500 public comments, where SVM achieved the highest accuracy (0.80–0.96). The integrated approach improves ranking stability, reduces decision ambiguity, and strengthens alignment between expert judgment and community sentiment. This study contributes a transparent, participatory decision-support model that unifies MCGDM and sentiment analysis to enhance the effectiveness of sustainable GOS planning.