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All Journal ELSE (Elementary School Education Journal) : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar JOURNAL OF APPLIED INFORMATICS AND COMPUTING JSiI (Jurnal Sistem Informasi) Journal of Information Systems and Informatics Neo Teknika: Jurnal Ilmiah Teknologi International Journal of Advances in Data and Information Systems MEANS (Media Informasi Analisa dan Sistem) Jurnal UNITEK Journal La Multiapp Jurnal Pengabdian Masyarakat (ABDIRA) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Mandiri IT Jurnal Locus Penelitian dan Pengabdian Jurnal Algoritma Jurnal Masyarakat Madani Indonesia Indonesian Journal of Community Empowerment (IJCE) "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Informatika dan Kesehatan INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer
Sri Mujiyono
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Sentiment Analysis of the Free Nutritious Meal Program on Twitter Using Naive Bayes and IndoBERT-Based Labeling Manao, Mikel Frewinta; Mujiyono, Sri
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1345

Abstract

The Free Nutritious Meal Program is a government initiative aimed at improving the nutritional status of primary school children in Indonesia. However, its implementation has generated diverse public reactions on the X/Twitter platform, making systematic sentiment analysis essential for policy evaluation. This study analyzes public sentiment using two labeling approaches—translation-based TextBlob and IndoBERT contextual labeling—combined with Naïve Bayes and Linear SVC classifiers.  A total of 2,903 Indonesian-language tweets were collected, preprocessed, and classified to compare the performance impact of each labeling method. The evaluation was conducted using accuracy, precision, recall, and macro F1-score. Sentiment distribution under IndoBERT indicates a predominance of negative and neutral opinions, particularly related to budget concerns, implementation quality, and food distribution issues. This study is subject to several limitations. The dataset size (2,903 tweets) and restricted temporal window may limit the generalizability of findings to long-term public discourse. The analysis also relies on a single social media platform (X/Twitter), excluding perspectives from other platforms such as Instagram or TikTok. Moreover, although IndoBERT improves contextual understanding, transformer-based labeling still may not fully capture sarcasm or highly colloquial expressions. Despite these limitations, the study demonstrates the effectiveness of combining Indonesian transformer models with conventional classifiers to support data-driven policy evaluation.
A DECISION SUPPORT SYSTEM FOR DETERMINING THE BEST EMPLOYEE PERFORMANCE EVALUATION USING THE ANALYTICAL HIERARCHY PROCESS (AHP) METHOD Polinus Gulo; Sri Mujiyono
Jurnal Sistem Informasi Vol. 13 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/hsza5003

Abstract

Employee performance appraisal plays a critical role in organizational decision-making, particularly in determining promotions, bonuses, and competency development. Conventional manual evaluation methods are often subjective, inconsistent, and lack systematic validation. While prior studies have applied multi-criteria decision-making methods in decision support systems (DSS) for employee evaluation, a critical gap remains: most existing systems omit consistency testing, use incomplete weighting procedures, or lack end-to-end system implementation—undermining the reliability of their outputs. To address this gap, this study proposes a novel DSS that integrates a complete Analytical Hierarchy Process (AHP) procedure, including pairwise comparison, normalization, priority weight calculation, and consistency validation, within a fully operational web-based system developed using the SDLC Waterfall model at PT Sam Sam Jaya Garments. Data were collected through observation and interviews to define evaluation criteria and system requirements. The results reveal that Discipline holds the highest weight (0.4391), followed by Target Achievement (0.2661) and Honesty (0.1507), with a Consistency Ratio (CR) of 0.029, confirming reliable judgments. The system successfully ranked ten employees, identifying Cahya Annsyiah as the top performer with a final score of 0.39116. The key contribution of this study lies in its end-to-end integration of AHP with consistency validation into a deployable DSS, directly addressing the methodological shortcomings identified in previous research and enhancing objectivity, accuracy, and transparency in employee performance evaluation.   Keywords: Decision Support System, Analytical Hierarchy Process, Employee Performance Evaluation, AHP, SDLC Waterfall
Co-Authors Abdul Rohman Abdul Rohman Ade Pratama Ade Pratama Afif Faisal Yasin Amalia, Alifah Anton Anton Aripin, Ahmad Nurul Dewanto, Bernadus Ela Suryani Fahrizal Alfian Dante fifi maqfiroh Fiktina Vifri Ismiriyam Galih Agil Febri Hidayatullah Hani Latifah Heni Setyowati Hesti Yunitiara Rizqi Ilham, Dimas Muhammad Iwan Setiawan Wibisono Kartika Yuni Purwanti Khafid, Ahmad Noor Lisa Virdinarti Putra Manao, Mikel Frewinta Nafi, Tri Maula Novan Syaiful Nugroho, Aventura Suryo Nugroho, Ivan Pangestu, Andi Polinus Gulo Puput Amanda Rasyid Purnamasari, Yessy Sabilla Sanjaya, Ucta Pradema Suamanda Ika Novichasari Syarifudin, Nanang Irfan Wahyu Kristiningrum Widayati Widayati Yeni Fitri Afidah Zulmi Roestika Rini