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Be Wise on the Internet in the Digital Era Feri Alpiyasin; Rini Risanti; Yomanius Untung; Dylan Hafizh Ramdany; M Fahmi Aditia; M Adika Burhanuddin; Rafi Iqbal Maulana; Wahyuni Syifa Aliyya; Nasywa Ambarwati; Najhan Taswiyah Hasanudin; Ibnu Raihan Raindra A; Bagaskara Saputra D; Manan Prasetya; Andika Maulana Yusuf
Jurnal Pengabdian Masyarakat: Bisnis dan Iptek (JPMBISTEK) Vol. 2 No. 2 (2025): Jurnal Pengabdian Masyarakat: Bisnis dan Iptek (JPMBISTEK)
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/p895c453

Abstract

Prudent internet use in the digital age seeks to mitigate the imprudent actions of adolescent internet users. The primary concerns identified encompass insufficient understanding of mental health dangers, the proliferation of misinformation, and internet addiction. This community service initiative utilizes a socialization approach comprising steps such as a pre-test, a material presentation, a post-test, and an implementation evaluation. Findings from this community service initiative reveal that people in Karanganyar and Astanaanyar who participated in the digital literacy workshop demonstrated enhanced comprehension of safe and responsible internet use. In conclusion, digital literacy education equips the community with essential skills to navigate the online realm responsibly, thereby reducing risks and enhancing the benefits of the internet in the digital age.
A Comprehensive Analysis Of Student Feedback On The Curriculum, Lecturers, And Facilities At STMIK Mardira Indonesia Using A Statistical Approach And Machine Learning Natural Language Processing Dwi Winda Fitrika; Yomanius Untung; Yusi Roslina Suciati; Fikri Irawan Abdurahman
Informatics Management, Engineering and Information System Journal Vol. 4 No. 1 (2026): Informatics Management, Engineering and Information System Journal
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Enhancing the quality of higher education necessitates a thorough review of student feedback. Nonetheless, STMIK Mardira Indonesia continues to handle input manually, which challenges its ability to manage substantial amounts of both quantitative and qualitative data effectively. As a result, the institution fails to draw on numerous useful insights from student feedback. This research aims to develop an integrated system that autonomously analyzes student input using statistical and machine-learning methods. The technology displays outcomes via an interactive dashboard to facilitate data-driven decision-making for management. The research employs a hybrid technique, integrating CRISP-DM for data analysis and Machine Learning with the Prototype method for system development. The data analysis encompasses descriptive statistics for quantitative data (Likert scale) and Natural Language Processing (NLP) employing a Linear SVM model for sentiment classification of qualitative data (comments). The research yields a web-based system prototype that effectively consolidates the collection and analysis of student input on the curriculum, instructors, and facilities. The Linear SVM sentiment classification model has outstanding performance, with an accuracy of 95.2% on the test dataset. Moreover, the interactive dashboard effectively illustrates these outcomes through dynamic filtering. Consequently, the integration of statistical and Machine Learning methodologies successfully converts raw feedback into organized insights, equipping STMIK Mardira Indonesia with a reliable instrument to sustainably improve educational service quality.