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All Journal Sains Data Jurnal Studi Matematika dan Teknologi RAGAM: Journal of Statistics and Its Application Jurnal Pengabdian Cita Masyarakat
Fajar Widianto
Universitas Pamulang
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences

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Digital Literacy Education: The Utilization of Information Technology in Social Media Among Students of SMP Negeri 2 Mekar Baru, Tangerang Regency Ramadhan Ibrahim; Fajar Widianto; Edward Felix Satria Sridana; Jonatan Reky Tasyam; Muhamad Nawawi; Agung Budi Susanto; Winarni
Jurnal Pengabdian Cita Masyarakat Vol. 1 No. 4 (2026): Jurnal Pengabdian Cita Masyarakat (JPCM)
Publisher : Yayasan Cerdas Pedia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65101/jpcm.v1i4.259

Abstract

The rapid transition towards Society 5.0 exposes adolescents to significant cyber risks, necessitating comprehensive digital literacy education. This community service aimed to enhance digital resilience and ethical social media utilization among students at SMP Negeri 2 Mekar Baru. Utilizing a Participatory Action Research approach combined with experiential learning, the intervention engaged 23 randomly selected students in an interactive workshop. The program uniquely integrated generative artificial intelligence tools, specifically NotebookLM for critical data validation, Pippit AI for ethical visual transformation, and Suno AI for affective musical creation. Results demonstrated a highly significant transformation in student behavior, shifting their paradigm from passive technology consumers to proactive, responsible digital content creators. This integration of advanced technological instruments proved exceptionally effective in building systemic cyber resilience, fostering critical thinking, strengthening data privacy awareness, and preparing youth for complex future digital challenges within modern educational ecosystems to ensure sustainable community empowerment and absolute technological safety.
Analisis Model Algoritma K-Means Clustering untuk Pengelompokan Prestasi Berdasarkan Nilai Pengetahuan Siswa (Studi Kasus SMP Negeri 2 Mekar Baru) Fajar Widianto; Alfaiko Janita
Sains Data Jurnal Studi Matematika dan Teknologi Vol 4, No 1: January - June 2026
Publisher : Institut Nurul Islam Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52620/sainsdata.v4i1.347

Abstract

Perkembangan teknologi memberikan dampak nyata hari ini. Khususnya dunia pendidikan dalam melakukan penilaian siswa, mengevaluasi keberhasilan proses pembelajaran di sekolah. Namun, pengelompokan prestasi berdasarkan nilai pengetahuan seringkali masih dilakukan secara manual sehingga kurang efektif dan kurang mampu memberikan gambaran pola akademik secara menyeluruh. Tujuan dari penelitian ini untuk menganalisis penerapan model algoritma K-Means clustering dalam mengelompokkan prestasi siswa berdasarkan nilai pengetahuan di SMP Negeri 2 Mekar Baru. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan teknik data mining. Data nilai pengetahuan siswa diolah melalui tahapan preprocessing, penentuan jumlah cluster (k), proses iterasi K-Means, serta mengevaluasi hasil pengelompokan. Hasil yang didapat menunjukkan bahwa algoritma K-Means mampu melakukan  pengelompokan siswa ke dalam beberapa kategori prestasi, seperti tinggi, sedang maupun rendah, secara objektif berdasarkan kedekatan nilai centroid. Kesimpulannya, penerapan K-Means efektif membantu pihak sekolah dalam memetakan prestasi siswa sebagai dasar pengambilan keputusan adapun kebaruan dalam penelitian ini terletak pada penerapan model clustering sebagai sistem pendukung evaluasi prestasi berbasis data di tingkat SMP.
IMPLEMENTATION OF THE MULTILINGUAL SENTIMENT METHOD IN PUBLIC SENTIMENT PERSPECTIVES TOWARD EDUCATION POLICY DIRECTIONS IN INDONESIA Fajar Widianto
RAGAM: Journal of Statistics & Its Application Vol 5, No 2 (2026): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v5i2.18091

Abstract

The current development of information technology has increased the dynamics of public opinion regarding the direction of education policy in Indonesia, which is spread across various digital platforms such as social media and news portals. The linguistic diversity used by the public, including Indonesian, regional languages, and mixed foreign languages, poses a challenge for conventional sentiment analysis, which is generally monolingual. This study aims to implement the Multilingual Sentiment Method to analyze and map public sentiment perspectives toward education policies in Indonesia more comprehensively and accurately. The research methodology encompasses data collection utilizing web scraping and APIs, data preprocessing (cleaning, case folding, tokenization, stopword removal, and normalization), automatic labeling, and the application of Natural Language Processing (NLP) using multilingual pre-trained models. Model performance evaluation is conducted using accuracy, distribution, precision, and prediction metrics. Data visualization analysis is also performed to illustrate sentiment distribution and emerging issue trends. The results indicate that the multilingual approach successfully improves classification performance compared to monolingual methods, particularly in detecting sentiments in mixed-language texts. The distribution of public sentiment is dominated by neutral and positive categories, whereas negative sentiments emerge regarding issues of technical implementation and equitable access to education. In conclusion, the implementation of the Multilingual Sentiment Method is effective in providing real-time mapping of public opinion, thereby supporting the formulation of education policies that are more responsive and data-driven.
Co-Authors Agung Budi Susanto Alfaiko Janita Edward Felix Satria Sridana Jonatan Reky Tasyam Muhamad Nawawi Ramadhan Ibrahim Winarni