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All Journal Jurnal Informatika dan Teknik Elektro Terapan Sinkron : Jurnal dan Penelitian Teknik Informatika Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Jurnal Teknologi Komputer dan Sistem Informasi Journal of Research in Business, Economics, and Education INFOKUM Journal of Industrial Engineering & Management Research (JIEMAR) Journal of Community Service and Engagement Akasia: Artikel Ilmiah Sistem Informasi Akuntansi Jurnal Minfo Polgan (JMP) Jurnal Akuntansi Dan Bisnis Indonesia (JABISI) Joong-Ki : Jurnal Pengabdian Masyarakat Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Akuntansi dan Manajemen Bisnis (JAMAN) Jurnal Abdi Masyarakat Multidisiplin Digital Transformation Technology (Digitech) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Multidisiplin Sahombu Nanggroe: Journal Of Scholarly Service Nanggroe: Journal of Scholarly Service Joong-Ki Jurnal Pengabdian Kepada Masyarakat Kalam Joong-Ki Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN) JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Jurnal Komputer, Informasi dan Teknologi
Euis Widanengsih
Universitas Bina Sarana Informatika
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Spam Message Classification Using the Naïve Bayes Algorithm Based on RapidMiner Muhamad Yusup; Mochamad Isham Fadillah; Rifky Adinanta Fauzanie; Risca Lusiana Pratiwi; Rani Irma Handayani; Euis Widanengsih
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1811

Abstract

This study implements the Naïve Bayes algorithm for classifying spam and non-spam (ham) messages using the RapidMiner Studio platform. The dataset used was obtained from the SMS Spam Collection Dataset on the Kaggle platform, which consists of 5,759 messages with a distribution of 4,075 ham messages and 1,291 spam messages. The research stages included text pre-processing, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The experimental results showed that the Naïve Bayes model achieved an accuracy of 89.64% with a precision of 56.93%, a recall of 100%, and an F1-score of 72.56%. The research findings indicate that the Naïve Bayes algorithm is effective in detecting spam messages with adequate accuracy, and prove that RapidMiner is an efficient tool for implementing machine learning methods in text classification.
Analisis Nilai Gizi Makanan Berbasis Machine Learning Pendekatan Unsupervised untuk Penentuan Status Gizi Sehat Bagoes Pangestu; Muhammad Annajmuts Tsaqib; Fatih Al Farizi; Risca Lusiana Pratiwi; Euis Widanengsih
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 2 (2025): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i2.3230

Abstract

This study aims to analyze and classify various food items based on their nutritional content using an unsupervised learning approach, specifically the K-Means Clustering algorithm. The increasing complexity of nutritional data requires effective data-driven methods to support accurate and efficient analysis. This research utilizes K-Means to group food items into distinct clusters according to their energy, fat, carbohydrate, protein, and fiber levels. The clustering process successfully identified three main groups that represent different nutritional characteristics. Cluster 1 consists of high-energy and high-fat foods suitable for individuals with high physical activity. Cluster 0 includes balanced-nutrition foods recommended for daily consumption, while Cluster 2 contains low-calorie and high-fiber foods ideal for weight control or diet programs. The results demonstrate that K-Means is effective in simplifying complex nutritional data and providing clear classifications for practical use. This study highlights the potential of machine learning as a valuable tool in nutritional analysis and digital health innovation. The application of this method can support the development of intelligent nutrition-based applications that help individuals manage healthy diets more effectively and contribute to promoting public awareness of balanced nutrition.
Penerapan Metode Scrum Pada Sistem Informasi Akuntansi Toko Alat Olahraga Widanengsih, Euis; Suwanto, Suwanto; Agustini, Fajar
Akasia: Artikel Ilmiah Sistem Informasi Akuntansi Vol 6 No 1 (2026): Artikel Ilmiah Sistem Informasi Akuntansi (AKASIA) - April 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/akasia.v6i1.10119

Abstract

Accounting management in sporting goods stores often faces challenges such as inefficient manual recording, error-proneness, and delays in presenting financial reports. This situation impacts suboptimal managerial decision-making. This study aims to apply the Scrum method to develop an accounting information system capable of improving the effectiveness of recording and presenting financial reports. The research method uses the Scrum framework approach, with the stages of product backlog, sprint planning, daily scrum, sprint review, and sprint retrospective. Each stage is implemented iteratively to adapt to user needs and minimize the risk of errors. The results show that the application of the Scrum method results in an accounting information system that is more structured, flexible, and tailored to the store's operational needs. This system simplifies the process of recording transactions, managing inventory, and preparing financial reports quickly and accurately. Thus, the system is able to support more informed decision-making for sporting goods store management
Co-Authors AA Sudharmawan, AA Abdul Khoir Amalia Fitriyani Aryo Tunjung Kusumo Aryo Tunjung Kusumo Bagoes Pangestu Desi Nursarifah Fajar Agustini Fatih Al Farizi Gathot Pujo Sanyoto, Gathot Pujo Henny Destiana Hernando, Alvin Ishak Komarudin Kevin Ananda Maas Kurniadi, Win Kusumo, Aryo Tunjung Maisyaroh Maisyaroh Martua Hami Siregar Mochamad Isham Fadillah Muhamad Arifin Ilhan Muhamad Yusup Muhammad Annajmuts Tsaqib Munawaroh, Enggar Tyastiwi Pratiwi, Risca Lusiana Rahman Faisal Rani Irma Handayani Rani Irma Handayani Rani Irma Handayani, Rani Irma Rifky Adinanta Fauzanie Risca Lusiana Pratiwi Risca Lusiana Pratiwi Rizki Darmawan Suwanto Suwanto Win Kurniadi Win Kurniadi Yusuf Yusuf Yusuf Yusuf Yusuf Yut, Immanuel Vico