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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Management of Information System Journal
Aditya Arya Respati
Universitas Nusantara PGRI Kediri
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science Other

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Evaluasi Kesuksesan Sistem TokSort Pada UMKM Devline Store Menggunakan Model DeLone dan McLean Aditya Arya Respati; Erna Danianti; Aidina Ristyawan
Management of Information System Journal Vol 4 No 3: Juli 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/mis.v4i3.2785

Abstract

Manual order data management in small and medium enterprises may cause work delays, recording errors, and difficulties in monitoring order completion. This study evaluates the success of TokSort as a mobile-based information system for processing Comma Separated Values (CSV) order data at Devline Store using an adapted DeLone and McLean IS Success Model. A descriptive quantitative approach with an evaluative case study framing was applied. The respondents were 11 internal TokSort users directly involved in order data management, so total sampling was used. Data were collected through a Likert-scale questionnaire and observation, then analyzed using mean values, validity testing, reliability testing, and exploratory Spearman Rank correlation. The results show that all variables were classified as good: system quality 3.42, information quality 3.64, use 3.86, user satisfaction 3.59, and net benefits 3.73. Spearman Rank results indicate positive and significant relationships among the tested variables. These findings show that TokSort is considered successful in supporting order data processing, grouping, and monitoring based on internal users’ perceptions. However, system stability and the ability to reduce order processing errors still require improvement. This study contributes an empirical evaluation of an internal SME operational information system based on CSV file processing.
Aplikasi Deteksi Berita Hoaks Berbahasa Indonesia Menggunakan IndoBERT dan Streamlit Mochamad Abdul Azis; Aditya Arya Respati
JSI: Jurnal Sistem Informasi (E-Journal) Vol 18 No 1 (2026): JSI: Jurnal Sistem Informasi (E-Journal)
Publisher : Jurusan Sistem Informasi Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/jsi.v18i1.355

Abstract

This study aimed to develop a hoax news detection application in the Indonesian language using the IndoBERT model, implemented through the Streamlit platform. The increasing spread of false information in Indonesia serves as the main motivation behind the development of this system. The classification model was trained using a partial fine-tuning strategy, where most of the early encoder layers were frozen while the top layers and classifier head were retrained. The dataset consisted of 24,658 preprocessed and summarized news entries using the T5-base model, with the main features being the combination of headlines and summarized content. The best-performing model achieved an accuracy of 97.81%, precision of 98.31%, recall of 97.56%, F1-score of 97.74%, and an ROC AUC score of 0.996. The selected model was then integrated into a Streamlit-based application, enabling users to input news text and receive real-time classification results of “Hoax” or “Not Hoax” along with the confidence score. The application was designed with a simple and user-friendly interface and aimed to assist general users in verifying information independently. The results demonstrate that the combination of IndoBERT and Streamlit is effective for building an accurate and practical hoax detection system.
Co-Authors Aidina Ristyawan Erna Danianti Mochamad Abdul Azis