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All Journal International Journal of Electrical and Computer Engineering Tekno : Jurnal Teknologi Elektro dan Kejuruan Teknologi dan Kejuruan: Jurnal teknologi, Kejuruan dan Pengajarannya Jurnal Inovasi Teknologi Pendidikan International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Pendas : Jurnah Ilmiah Pendidikan Dasar Cetta: Jurnal Ilmu Pendidikan ILKOM Jurnal Ilmiah at-tamkin: Jurnal Pengabdian kepada Masyarakat SENTIA 2016 SENTIA 2015 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Karinov TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Edunesia : jurnal Ilmiah Pendidikan Letters in Information Technology Education (LITE) Ideguru: Jurnal Karya Ilmiah Guru Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Decode: Jurnal Pendidikan Teknologi Informasi Emerging Information Science and Technology Bulletin of Community Engagement Journal of Education Research Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Journal of Health and Nutrition Research JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal Ekonomi, Bisnis dan Pendidikan (JEBP) Journal of Embedded Systems, Security and Intelligent Systems
Didik Dwi Prasetya
Universitas Negeri Malang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Integration of Social, Organizational, and Technological Factors to Improve the Effectiveness of Environmental Policies in Waste Management in Bima City Sri Sumanti, Endang; Prasetya, Didik Dwi; Patmanthara, Syaad
Emerging Information Science and Technology Vol. 6 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i2.29171

Abstract

Bima City faces serious challenges in waste management, characterized by low service covera- ge (53.16%), limited processing facilities, and low public awareness and participation. This study aims to comprehensively evaluate the waste management system in Bima City and formulate sustainable strate- gies by integrating social, organizational, and technological factors. The research approach is quantitative with Structural Equation Modeling (SEM) analysis of 200 respondents from the community, sanitation workers, and environmental managers. The conceptual model was developed by adapting the Human–Or- ganization–Technology Fit (HOT-Fit) framework and Sustainability Metrics dimensions that include po- licy, participation, community behavior, and infrastructure technology. The results showed that organizational factors and public policy significantly influenced the effectiveness of waste management (β = 0.36; p < 0.001). Community participation was the dominant factor with a di- rect influence on management effectiveness (β = 0.45; p < 0.001), while community behavior acted as a mediator between technology and system effectiveness (β = 0.32; p < 0.001). The Goodness of Fit value showed a statistically appropriate model (CFI = 0.957; TLI = 0.951; RMSEA = 0.039). This study empha- sized the importance of synergy between policy support, social participation, and technological infrastruc- ture in building a sustainable waste management system.
Extracting Value from Minority Voices: Epistemic Validation of Naive Bayes and SMOTE Models for E-Commerce Review Sentiment Analysis Ibrahim, Firmansyah; Prasetya, Didik Dwi; Patmanthara, Syaad
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10275

Abstract

In the e-commerce ecosystem, negative customer reviews, despite often being a numerical minority, represent the most valuable (axiological) business asset for service improvement. However, this value is frequently obscured by the high volume of positive reviews, creating a significant imbalance in the data. This study aims to design and validate a text mining model that is axiologically focused on extracting critical insights from this "minority voice." We applied the Naive Bayes Classifier (NBC) algorithm, augmented with TF-IDF feature weighting, on a dataset of 6,000 reviews from the 'Famous Florist' store. The epistemic challenge of severe data imbalance (5,432 positive vs. 97 negative) was addressed through the methodological intervention of the Synthetic Minority Over-sampling Technique (SMOTE). The model's validity was assessed using 10-Fold Cross-Validation. The epistemic validation results demonstrated the model's validity, achieving an average accuracy of 90%. Crucially, the model achieved a 99% rate for the negative class. This affirms the model's axiological validity: its ability to reliably identify customer complaints (e.g., 'damaged,' 'packaging') and transform raw data into actionable recommendations for improvement.
Paradigma Epistemologis Kompresi Data Teks: Huffman, Arithmetic, dan Neural Language Model Affandi, Luqman; Prasetya, Didik Dwi; Patmanthara, Syaad
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8384

Abstract

This study explores text data compression as an epistemological paradigm through a comparative analysis of three fundamental approaches: traditional methods (Huffman Coding + LZW), bit-based methods (Arithmetic Coding), and machine learning approaches (Neural Language Models). Using the Project Gutenberg dataset comprising 15,000 classical literary works with a total size of 8.5 GB and 2.1-billion-word tokens, the evaluation is conducted based on compression ratio, execution time, and memory usage. The results reveal fundamental trade-offs among the paradigms. Traditional methods achieve the fastest execution (8.3 seconds/GB, 482 MB/s, 52 MB) with a compression ratio of 3.2:1. Arithmetic coding attains near-optimal performance (99.5% of the Shannon bound) with a compression ratio of 3.8:1. Neural language models yield the highest compression ratio of 4.6:1 but require substantially higher execution time and memory. The epistemological analysis highlights distinct conceptions of information—mechanistic, mathematically optimal, and semantic-aware—and provides a conceptual framework for developing adaptive compression systems.
Educational Data Mining: Multiple Choice Question Classification in Vocational School Sucipto Sucipto; Didik Dwi Prasetya; Triyanna Widiyaningtyas
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3499

Abstract

Data mining on student learning outcomes in the education sector can overcome this problem. This research aimed to provide a solution for selecting quality multiple choice questions (MCQ) using the results of students’ mid-semester exams in vocational high schools using a Data Mining approach. The research method used was the Cross-Industry Standard Process for Machine Learning (CRISP-ML) model. Steps to assess the accuracy of analyzing the difficulty level of questions based on student profile data and midterm test results. The data used in this research were the findings of basic computer tests on mid-term exams in mathematics disciplines at vocational high schools. This research used several classification algorithms, including SVM, Naive Bayes, Random Forest, Decision Three, Linear Regression, and KNN. The results of evaluating the classification
Student Flowchart Automated Evaluation for Scalable Assessment in Introductory Programming Usman Nurhasan; Didik Dwi Prasetya
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13594

Abstract

This study evaluates the Automated Flowchart Assessment Tool (AFAT) to overcome limitations in semantic sensitivity and layout robustness prevalent in existing tools. Through a quantitative analysis of 312 student submissions, AFAT demonstrated superior diagnostic performance with a Micro-F1 score of 0.92 and substantial inter-rater agreement (Fleiss' Kappa = 0.88), supporting the hypothesis of expert-level accuracy. Key findings reveal that AFAT significantly enhances operational efficiency, reducing evaluation time by 61.2% (averaging 1.87 minutes per flowchart) while decreasing inter-rater variability by 28%. Generalized Linear Model (GLM) analysis confirmed significant time savings, particularly in high-complexity sessions (Wald χ² = 87.44, p < 0.001). Beyond technical efficiency, this research contributes to applied science education by providing a scalable framework for computational science literacy, enabling the rigorous assessment of algorithmic thinking within integrated STEM curricula. These results substantiate AFAT’s potential for large-scale deployment as a robust tool for automated scoring in formal educational settings
Public Sentiment on Indonesia’s Free Nutritious Meal Program: A Mixed-Methods NLP Evaluation Ibrahim, Firmansyah; Prasetya, Didik Dwi; Kaswar, Andi Baso; Pratiwi, Hardyanti
Journal of Health and Nutrition Research Vol. 5 No. 1 (2026)
Publisher : Media Publikasi Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56303/jhnresearch.v5i1.1053

Abstract

Large-scale nutrition intervention programs such as the Free Nutritious Meal Program (MBG) are likely to attract considerable attention on social media. While conventional evaluation techniques are often too slow to capture rapidly shifting sentiment, this study seeks to determine how sentiment can be evaluated. More specifically, we aimed to identify the key emerging issues. Methodology: In this study, one approach to examining emerging issues is to use a two-stage workflow in Natural Language Processing (NLP). The first step in sentiment analysis is using a transformer model (Indo-RoBERTa) to assign 'Positive', 'Negative', or 'Neutral' to 3,459 public texts from X (Twitter) social media. Secondly, we focused on 1,130 'Negative' texts. We used topic modeling (BERTopic) on this and identified the most critical clusters of issues to map and their relative importance. Results & Conclusions: Negative sentiment involves multiple factors, to which our model successfully highlighted four of the most impactful areas: (1) Financial concerns and budgetary priorities; (2) Responses to particular media coverage (e.g., Kompas); (3) Political general discourse; and (4) Expectations of particular local issues (education issues in Papua). Conclusion: Compared with the gaps in the program's nutrition components, the economic consequences, budget gaps, inequities, and regional policy deficiencies drew more public interest. Implications: The findings point to a clear need for a differentiated and open approach to communicating public policy. This approach should communicate the nutritional value and the need to align messaging with the public for the geographic and budgetary realities.
Co-Authors Abdul Wafi Achmad Afif Irwansyah Adi Wahyu Wardani Ahmad Fajruddin Syauqi Ahmad Yusuf Setiawan Ainun Nur Baiti Aji P Wibawa Aji Prasetya Wibawa Akbar, Asna Isyarotul Andi Baso Kaswar Andi Baso Kaswar Andika Dwiyanto, Felix Andrew Nafalski Anik Nur Handayani Anjar Dwi Rahmawati Arifiati Fitri Anggraini Aripriharta - Aryo Pinandito Ashar, Muhammad Azhar Ahmad Smaragdina Bagaskoro Biantoro, Yudhi Bintang Romadhon Cakir, Gulsun Kurubacak Denis Eka Cahyani Dwi Widiyasari Dyah Ayu Langening Tyas Ella Amelia Widodo F.ti Ayyu Sayyidul Laily Fadhli Almu’iini Ahda Fadli Hidayat, M. Noer Fatrisna Salsabila, Reni Firdaus, Nabilah Zakiyah Salmaa Gradiyanto Radityo Kusumo Hafid, Ahmad Hairani Hairani Hakkun Elmunsyah Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haq, Salsabila Thifal Nabil Hariyanto Hariyanto Hayashi, Yusuke Heru Wahyu Herwanto Hirashima, Tsukasa I Nyoman Gede Arya Astawa Ibrahim, Firmansyah Ilham Ari Elbaith Zaeni Intan Sulistyaningrum Sakkinah Iskandar Syah, Abdullah Kalifatullah, M. Ajie Khoirul Anwar KHOIRUL ANWAR Kusumo, Gradiyanto Radityo Laily, F.ti Ayyu Sayyidul Lalu Ganda Rady Putra Langlang Gumilar Lismi Animatul Chisbiyah Luqman Affandi Lutfi Budi Ilmawan, Lutfi Budi M. Ajie Kalifatullah Marsono Marsono Marsono Marsono Maskur Maskur Mayadi, Mayadi Mega Oktaviana Moh. Nur Zamzami Moh. Zainul Falah Muhammad Arief Nugroho Muhammad Aris Ichwanto muhammad hafiizh, muhammad Muhammad Jauharul Fuady Muhammad Mushawwir Muhammad Zaki Wiryawan Muhammad Zidni Ridlo Mukhamad Angga Gumilang Muladi Muttaqiyah, Khusnul Nadiah Alma Ratnaduhita Nadindra Dwi Ariyanta Nafalski, Andrew Nanscy Evi Wardani Natalina Wahyu Siswijayanti Nena Erviana Nunung Nurjanah Nur Hidayat, Wahyu Nuryakin, Mokhamad Perkasa, Gigih Prasetya, Luhur Adi Prasetyo, Muchamad Wahyu Pratiwi, Hardyanti Prihandicha, Adiftya Bayu Putro, Maulana Nur Antoro Ratnaduhita, Nadiah Alma Reni Fatrisna Salsabila Reo Wicaksono Ridlo, Muhammad Zidni Rofiudin, Amir Ryan Kurniawan Samodra, Joko Setiadi Cahyono Putro Setiawan, Ahmad Yusuf Setyani, Ida Agus Shafelbilyunazra, Alvalen Sigit Perdana Siti Sendari Sofiya Anggraini Sri Sumanti, Endang Sucipto Sucipto Sucipto Sucipto Sulistyo, Danang Arbian Syaad Patmanthara Syaichul Fitrian Akbar Syamsul Arifin Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tsukasa Hirashima Tsukasa Hirashima Tuwoso Usman Nurhasan Usman Nurhasan Utomo Pujianto Wahfi, Muhammad Fikri Wahyu Sakti Gunawan Irianto Wahyu Styo Pratama Wahyu Tri Handoko Wahyudi, Erlik Prasetyo Wardani, Adi Wahyu Wibawa, Aji P Wibisono Sukmo Wardhono, Wibisono Sukmo Widiyanti Widiyanti, Widiyanti Yana Andayani Yusril Imamuddin Zainul Falah, Moh.