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All Journal TEKNIK INFORMATIKA Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter JIK Jurnal Ilmu Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding SNATIKA Vol 01 (2011) Sinkron : Jurnal dan Penelitian Teknik Informatika Applied Information System and Management Technomedia Journal Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences Loghat Arabi: Jurnal Bahasa Arab & Pendidikan Bahasa Arab International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Blockchain Frontier Technology (BFRONT) Journal of Current Research in Blockchain International Journal Research on Metaverse
Yusuf Abdurachman
UIN Syarif Hidayatullah Jakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Implementation of Data Mining with Naive Bayes Algorithm for Eligibility Classification of Basic Food Aid Recipients Yamato Shino; Yusuf Durachman; Nana Sutisna
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 2 No. 2 (2022): October
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v2i2.114

Abstract

One of the primary issues that the government of a nation concentrates on is poverty. The provision of precise and focused data on poverty is a crucial component of the Poverty Reduction Strategy. One technique for classifying data is Naïve Bayes. The aid manager will subsequently use the categorization findings to inform judgments about categorizing and determining who should get basic food assistance. Predictions for those who get basic food assistance fall into two categories: eligible and ineligible. Sample data from the hamlet of XYZ used as the basis for the forecast. In this study, a web-based application is used to construct and assess the Naïve Bayes method. The accuracy for 135 training data, 40 test data, and seven characteristics employed generates 86 percent accuracy, 85 percent recall, and 88 percent precision according to the assessment findings using the confusion matrix.
Large Language Models for Intelligent Decision Support in Inventory and Supply Chain Operations: A Systematic Literature Review Yusuf Durachman; Eva Khudzaeva; Naura Aulia
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1540

Abstract

Generative Artificial Intelligence (GenAI), particularly large language models (LLMs), is increasingly explored to strengthen decision support in supply chain and inventory management by improving interpretability and access to analytics. However, prior work is scattered across optimization, simulation, logistics, and governance discussions, limiting clear system design guidance. This study conducts a Systematic Literature Review (SLR) following PRISMA 2020 across IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, and Google Scholar, yielding 200 records, of which 34 studies were included in qualitative synthesis. Results show that LLMs are predominantly positioned as orchestration and explanatory layers operating alongside structured components such as optimization solvers, simulation engines, and digital twins, rather than as autonomous decision-makers. Governance, organizational readiness, and trust emerge as central considerations for operational deployment. This review provides an evidence map linking LLM roles and integration architectures across supply chain and inventory contexts. While LLMs offer strong augmentation capabilities, direct empirical validation for specific contexts such as web-based inventory systems remains limited; design implications for such systems are derived from the broader corpus, underscoring the need for standardized evaluation benchmarks and targeted empirical studies.
Evaluating User Satisfaction in Institutional Repositories through a Combined WebQual 4.0, EUCS, and Importance–Performance Analysis Approach Putra, Syopiansyah Jaya; Nurazza, Abdullah Fadli; Arham, Zainul; Durachman, Yusuf; Waspodo, Bayu; Khalil, Ismail
Applied Information System and Management (AISM) Vol. 9 No. 1 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i1.46727

Abstract

The repository website of UIN Syarif Hidayatullah Jakarta was designed to provide open access to academic publications produced by students and faculty members. However, it continues to encounter issues concerning interface usability, information accuracy, service personalization, and data access speed. These challenges underscore the necessity for a comprehensive assessment of its quality and the level of user satisfaction. This study aims to identify the key factors influencing user satisfaction, measure overall website performance through the WebQual Index (WQI), and analyze the alignment between user perceptions and expectations using the Importance Performance Analysis (IPA). A quantitative approach was employed, applying the extended WebQual 4.0 model with the inclusion of accuracy and timeliness variables adapted from the End-User Computing Satisfaction (EUCS) framework. Data were collected from 402 undergraduate respondents and analyzed using SPSS through validity, reliability, partial t-tests, and paired sample t-tests. The findings reveal that all independent variables significantly affect user satisfaction, and the website achieved a WQI score of 0.80, indicating a very good quality level. Nevertheless, aspects such as visual appeal and service personalization require improvement. The gap analysis result of 0.35 signifies that current performance has yet to fully meet user expectations. Furthermore, the IPA quadrant mapping provides strategic insights, emphasizing the need to enhance data security and the timeliness of information delivery. This research contributes to both theory and practice by developing an integrated evaluation framework that combines WebQual 4.0, EUCS, and IPA, offering a structured model for assessing user satisfaction within digital academic repositories in higher education institutions.
Co-Authors A'ang Subiyakto Abd. Rahman Ahlan Abd. Rahman Ahlan Rahman Ahlan Abdur Rohim Boy Berawi Abdur Rohim Boy Berawi Adrian Sean Bein Alauddin, Ilham Ali Djamhuri Amri Amri Anif Hanifa Setianingrum, Anif Hanifa Antonius Ivan, Antonius Arini Arini A’ang Subiyakto A’ang Subiyakto Subiyakto Bayu Waspodo Ditha Septiandani Elvi Fetrina Erwin Tobing, Erwin Eva Khudzaeva Evy Nurmiati Fitra Putri Oganda Fitroh Fitroh, Fitroh Harahap, Eka Purnama Himki, Arzo Huda, Muhammad Qomarul Husni Teja Sukmana Irma Yunita Isti Surjandari Prajitno, Isti Surjandari Kamal Yusuf Khalil, Ismail Khodijah Hulliyah Kultsum, Lilik Ummi Lestari Santoso, Nuke Puji Lutfiya, Nur Aqilah M. Qamarul Huda Millah, Shofiyul Mira Kartiwi Mohammed Ali Berawi Muhamad Nur Gunawan Muhamad Yusup Nahdlah Nurul Murhum Nahry Nahry Nana Sutisna Nashikha, Ainun Naura Aulia Nurazza, Abdullah Fadli Perdana Miraj Pramono, Erry Sigit Rahman Raeyani Kalele Rahman, Abdul Wahab Abdul Ramadhan, Tarisya Shofiyul Millah Supardi Supardi Syopiansyah Jaya Putra Syopiansyah Jaya Putra Taqwa Hariguna Tarisya Ramadhan Teuku Yuri M. Zagloel Tuada, Linura Watini, Srie Wibowo, Wahyu Hendarto Yamato Shino Yelna Yuristiary Zainul Arham