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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Informatika CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT INTECOMS: Journal of Information Technology and Computer Science Dewa Ruci : Jurnal Pengkajian dan Penciptaan Seni ARSY : Jurnal Aplikasi Riset kepada Masyarakat Journal of Informatics Management and Information Technology Mejuajua SAINSTEK The Indonesian Journal of Computer Science Jurnal Informatika
Rizky Wandri
Universitas Islam Riau
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Other

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Design of the 'Abdimas' Marketplace System: A Digital Platform for PKM Collaboration (Version 0.0) Fadhilah, M Rizki; Wandri, Rizky; Fadhilla, Mutia; Gunawan, Dwi Fiqri; Labellapansa, Ause; Gunawan, Hendra
SISTEMASI Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5545

Abstract

Community Service (Pengabdian kepada Masyarakat or PkM) is one of the three core responsibilities (Tridharma) of higher education in Indonesia, alongside education and research. However, many lecturers especially those new to academia face difficulties in identifying suitable community partners. This study addresses that issue through the design of a digital platform called “Abdimas”, intended to function as a marketplace system for matching lecturers with PkM partners. Applying the Design Thinking methodology, focusing on the conceptual and architectural design of the “Abdimas” platform, this study implemented a user-centered design approach. Data from interviews with lecturers, partners, and university administrators were analyzed using thematic analysis to identify core requirements. Based on these findings, the system was designed to support lecturer registration, partner discovery, and need-based matching. Senior lecturers are also supported in exploring new, underserved areas, while partners can publicly express their needs to attract suitable academic collaborators. University administrators can monitor the distribution of PkM activities over time to ensure equity and effectiveness. Unlike existing administrative platforms that often function as one-way reporting tools, the “Abdimas” marketplace introduces a bidirectional matching mechanism that allows partners to actively broadcast their specific community needs, bridging the information gap for lecturers. The system design includes use case diagrams, UI/UX prototypes, an Entity Relationship Diagram (ERD), and blackbox test scenarios to validate functionality. Although still in the design phase (Version 0.0), “Abdimas” has the potential to scale beyond academic users by supporting Corporate Social Responsibility (CSR) initiatives and facilitating student-level community services. This research contributes a structured and scalable system design to improve collaboration and outreach in community service programs within higher education.
Sentiment Analysis of #Saverafah Hashtag on TikTok Using Naive Bayes and Decision Tree Methods Pirsingki, Nisa; Wandri, Rizky
Jurnal Informatika Vol. 12 No. 1 (2025): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/informatika.v12i1.12256

Abstract

Social media facilitates user communication, both in positive, negative and neutral aspects. Tiktok is a popular platform that allows users to stay up to date on the latest news, including the major conflict between Palestine and Israel. In this war, many Palestinian civilians, including children and the elderly, became victims, and are currently trying to flee to Rafah to seek protection. The objective of this study is to evaluate public sentiment regarding the news of Palestinian refugees en route to Rafah. To achieve this purpose, we will examine 2982 comments on TikTok relating to the hashtag #SaveRafah, which will be the data to be trained. Prior to classification, the data will undergo a preprocessing process and TF-IDF weighting. The two classification methods will be compared to ascertain the most accurate approach. Because the data at the labeling stage has a larger percentage of positive data 90.7%, this study will employ the technique SMOTE to address class imbalance in the data set. The results showed that the Naive Bayes Multinomial method with the application of SMOTE produced an accuracy of 85.43%, a precision of 86.22%, a recall of 85.43%, and an f1-score of 85.53%. Meanwhile, the Decision Tree C4.5 method with the application of SMOTE produced an accuracy of 94.23%, a precision of 94.58%, a recall of 94.23%, and an f1-score of 94.22%. Based on the evaluation results, the best method for sentiment analysis of the hashtag #SaveRafah is Decision Tree C4.5.
Co-Authors ANDRI KURNIAWAN Arbi Haza Nasution, Arbi Haza Ause Labellapansa, Ause Bima Kristian Pranoto Daulay, Suandi Des Suryani Fadhilah, M Rizki Fadhilla, Mutia Fhelia Zahwa Fiqri Qurniawan, Dwi Fitriani Gunawan, Dwi Fiqri Hafiza Oktasia Nasution Hanafiah, Anggi HENDRA GUNAWAN B11211055 Jerika Mardafora M. Rizki Fadhilah Masnur Masnur Mohamad Yatim, Maizatul Hayati Muhammad Akbar Almuttaqin Mutia Fadhilla Nur, Nuriman M Oktasia Nasution, Hafiza Oktaviaani, Rizka Pandini, Pandini Pangestu, Firly Bagdja Pirsingki, Nisa Poppy Camenia Jamil Rachmat Setiawan, Panji Ranggi Ade Febrian Rizdqi Akbar Ramadhan Rizka Oktaviaani Sapitri Sapitri, Sapitri Sari, Putri Indah Setiawan, Panji Rachmat Syefriani Syefriani syefriani Syefriani, Syefriani Therecya Silitonga Yudhi Arta Yudhi Arta Yudhi Arta, Yudhi Zaini Ali Zulfhan Azmal