https://penerbitgoodwood.com/index.php/jisted <p align="justify">Jurnal Ilmu Siber dan Teknologi Digital (JISTED) is a national, open-access and peer-reviewed journal welcoming high-quality manuscripts of original articles, reports and literature reviews in the field of software engineering and information technology. Jurnal Ilmu Siber dan Teknologi Digital (JISTED) aims to mediate the fresh ideas of researchers and practitioners to accelerate technology and cyber development.</p> Penerbit Goodwood en-US Jurnal Ilmu Siber dan Teknologi Digital 2986-7312 <p>Authors who publish with this journal agree to the following terms:</p> <ol> <li class="show">Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="http://creativecommons.org/licenses/by-sa/4.0/" target="_blank" rel="noopener">Creative Commons Attribution License (CC BY-SA 4.0)</a> that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.</li> <li class="show">Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.</li> <li class="show">Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.</li> </ol> https://penerbitgoodwood.com/index.php/jisted/article/view/5547 <p><strong>Purpose: </strong>This study aims to develop a web-based system that classifies research articles using the Random Forest algorithm to address mismatches between article content and journal scope.</p> <p><strong>Methodology/approach: </strong>The research employed the SDLC Waterfall model, with data sourced from 560 articles published by Goodwood Publishing (2019–2024) across four categories. Text preprocessing included case folding, stopword removal, stemming, and tokenization, with TF-IDF applied for feature extraction. Random Forest was trained with 80% training data and 20% testing data.</p> <p><strong>Results/findings: </strong>The model achieved 91% accuracy, with high precision and recall across all categories. The system was successfully implemented as a web-based application, providing instant classification and journal recommendations.</p> <p><strong>Limitations: </strong>The dataset was limited to one publisher and only Random Forest was applied, which may restrict the generalizability of findings.</p> <p><strong>Contribution: </strong>This study contributes to the application of machine learning in scholarly publishing, offering a practical solution for editors to streamline article selection and improve efficiency.</p> Fiqqi Ahludzikri Riko Herwanto Abdul Aziz RZ Isnandar Agus Suhendro Yusuf Irianto Copyright (c) 2025 Fiqqi Ahludzikri, Riko Herwanto, Abdul Aziz RZ , Isnandar Agus, Suhendro Yusuf Irianto https://creativecommons.org/licenses/by-sa/4.0 2025-11-20 2025-11-20 4 1 15 31 10.35912/jisted.v4i1.5547 https://penerbitgoodwood.com/index.php/jisted/article/view/5906 <p><strong>Purpose: </strong>This study aims to develop an Android-based sales application for Rosella Tea as a digital innovation, addressing the need for efficient marketing and sales management among Women Farmers Groups (KWT) in East Ambarawa Village, Lampung.</p> <p><strong>Methodology/approach: </strong>The research utilizes the System Development Life Cycle (SDLC) method, with stages including needs analysis, system design using Unified Modeling Language (UML), coding with Java, and data storage via Firebase.</p> <p><strong>Results/findings: </strong>The developed application successfully operates on Android devices, presenting products informatively and enabling real-time transactions and sales management. It enhances marketing efficiency and expands the market reach for Rosella Tea, improving transaction processes between sellers and buyers.</p> <p><strong>Conlusion:</strong> The Android-based application serves as an innovative solution to promote Rosella Tea digitally, offering better sales management, expanding market access, and increasing business efficiency for women farmers.</p> <p><strong>Limitations: </strong>The study did not explore the full range of features needed, such as integration with various payment methods and e-commerce platforms.</p> <p><strong>Contribution: </strong>The application provides a digital pathway for Women Farmers Groups to manage and promote local products, contributing to their economic empowerment and aligning with government initiatives to support MSMEs' digitalization.</p> Lusia Septia Eka Esti Rahayu Marlia Sari Muhammad Junaidi Copyright (c) 2026 Lusia Septia Eka Esti Rahayu, Marlia Sari, Muhammad Junaidi https://creativecommons.org/licenses/by-sa/4.0 2025-11-20 2025-11-20 4 1 1 14 10.35912/jisted.v4i1.5906