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All Journal EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Informatika dan Rekayasa Perangkat Lunak Arcitech: Journal of Computer Science and Artificial Intelligence Jurnal Ilmiah Informatika dan Ilmu Komputer Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Jurnal Media Jawadwipa
Nuroji Nuroji
Universitas Muhammadiyah Prof. DR. HAMKA
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Library & Information Science

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Analisis Sentimen Pengguna Aplikasi Byond BSI Pada Google Play Store Menggunakan Algoritma SVM Dan Random Forest Firzatullah, Firdaus Naifah; Nuroji, Nuroji
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/6vtc4567

Abstract

The development of digital technology has encouraged banks to provide application-based financial services, one of which is BYOND by BSI, which carries the concept of Islamic banking. However, various technical obstacles such as service disruptions and application errors in using this application have caused dissatisfaction among users. Therefore, sentiment analysis is needed to understand user responses comprehensively. This study aims to classify user sentiment towards the BYOND by BSI application by utilizing the Support Vector Machine (SVM) and Random Forest algorithms. The data used are 35,000 user reviews collected from the Google Play Store through crawling techniques, then automatically labeled using a rule-based method based on rating values. The analysis process was carried out using the SEMMA approach, which includes the stages of text cleaning, word weighting using TF-IDF, and dividing the data into 80% training data and 20% test data. The test results showed that the SVM algorithm had the best performance with an accuracy of 93.16%, while Random Forest obtained an accuracy of 90.33%. The majority of the analyzed reviews showed negative sentiment. These findings are expected to provide input in improving the quality of the BYOND by BSI application service.
Perancangan Sistem Presensi Wajah (SIWAJA) Berbasis Internet of Things dengan Notifikasi Telegram Muhammad Bagas Adi Pangestu; Nuroji, Nuroji
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/88ctdw53

Abstract

Manual student attendance administration is prone to human error, inefficient, and hinders communication between schools and parents. This study aims to develop the Face Presence System (SIWAJA), an innovative solution integrating face recognition technology and the Internet of Things (IoT) to provide live attendance notifications to parents via Telegram. A key technological advantage of this system is the implementation of the YOLOv8 algorithm, which is emphasized for its high precision in face detection. The development method used is the prototype model, which includes stages of requirements identification, design, implementation, and evaluation. The system was built using an Orange Pi 5 Pro, the Python programming language with the OpenCV library, and the YOLOv8 algorithm for face detection. The research results show that the SIWAJA system was successfully developed and functions as expected, where the IoT-based design supports potential scalability for broader implementation. Black Box Testing validated all main functionalities, from presence-taking to notification delivery. The face detection model showed highly reliable performance with a precision (P) value of 0.97, recall (R) of 0.99, and mAP@.5 of 0.99. In conclusion, SIWAJA proves to be an effective and accurate solution for modernizing student attendance management and enhancing real-time parental involvement, offering significant contributions to the application of IoT in education.
Co-Authors Alim, Endi Sjaiful Alita, Debby Anhari, Tirta Fadillah, Bagas Firzatullah, Firdaus Naifah Harlian Navi Isnain, Auliya Rahman M. Asep Rizkiawan Muhammad Bagas Adi Pangestu Pasaribu, A. Ferico Octaviansyah Sobari, Bahar Taufiq Martiwansyah Very Hendra Saputra Yusuf Widsono, Maulana