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All Journal Journal of Research and Publication Innovation Journal of Information Systems and Business Technology
Daffa Alif Ruriyanto
Universitas Pamulang
Computer Science & IT Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Analisis dan Perancangan Sistem Informasi Manajemen Inventori Berbasis Website Menggunakan Standar ISO/IEC 25010 (Studi Kasus: PT Teknologi Informatika Solusindo) Raihanullah Raihanullah; Daffa Alif Ruriyanto; Chairul Anwar
Journal of Information Systems and Business Technology Vol 2 No 3 (2026): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

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Abstract

Inventory management at PT Teknologi Informatika Solusindo continues to face practical challenges, largely due to processes that are not yet fully integrated into a digital system. The continued reliance on manual and semi-computerized recording leads to inconsistencies in data, difficulties in asset tracking, and a higher likelihood of errors or data loss. These conditions directly affect operational performance and reduce the effectiveness of decision-making. In response to these issues, this study focuses on designing a web-based inventory information system, preceded by an in-depth identification of user requirements. System development is carried out iteratively using the Prototype approach to ensure adaptability to real user needs. The design also refers to the ISO/IEC 25010 standard to ensure software quality in terms of functionality, reliability, and usability. The resulting system is expected to improve data quality, enhance inventory management effectiveness, and provide more accurate and accessible information to support better decision-making.
ANALISIS SENTIMEN ULASAN PUBLIK PADA X MENGGUNAKAN NAIVE BAYES UNTUK MENINGKATKAN KUALITAS LAYANAN TRANSJAKARTA Daffa Alif Ruriyanto; Fauzan Abhip Raya; Reffiano Siswoyo
Journal of Research and Publication Innovation Vol 4 No 1 (2026): JANUARY
Publisher : Journal of Research and Publication Innovation

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Abstract

As the largest public transportation system in Jakarta, TransJakarta frequently becomes a topic of discussion on Twitter due to various user experiences ranging from satisfaction to service-related complaints. The abundance of public opinions provides an opportunity to apply machine learning–based sentiment analysis as a faster, more objective, and measurable method for evaluating service quality. This study employs the Naive Bayes algorithm to classify tweet sentiments into positive, negative, and neutral categories. Data were collected through a crawling process using keywords related to TransJakarta, then processed through several stages including tokenization, text cleaning, stopword removal, and stemming to produce analysis-ready data. Several service aspects discussed most frequently include bus arrival punctuality, travel comfort, and fleet conditions. The analysis results indicate that the Naive Bayes model can accurately identify public sentiment patterns in near real-time, enabling the detection of opinion trends across different service dimensions. These findings demonstrate that Naive Bayes–based sentiment analysis can serve as an effective tool for monitoring public perception and provide a strong foundation for TransJakarta in formulating strategies to improve service quality.
Co-Authors Chairul Anwar Fauzan Abhip Raya Raihanullah Raihanullah Reffiano Siswoyo