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All Journal Jurnal Simetris Jurnal Informatika dan Teknik Elektro Terapan Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) JOIV : International Journal on Informatics Visualization DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Building of Informatics, Technology and Science Technologia: Jurnal Ilmiah JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Indonesian Journal of Electrical Engineering and Computer Science IJIIS: International Journal of Informatics and Information Systems Jurnal Teknik Informatika (JUTIF) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Journal of Multimedia Trend and Technology Jurnal Pengabdian Masyarakat Bangsa Journal of Software Engineering and Information System (SEIS) CSRID Jurnal Bahasa Rupa
Dwi Krisbiantoro, Dwi
STMIK AMIKOM Yogyakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Digital Vital Signs: Decision Trees as Behavioral Tripwires for Adolescent Smartphone Overuse Nafi, Sulthon Fadhlun; Krisbiantoro, Dwi
Journal of Multimedia Trend and Technology Vol. 4 No. 3 (2025): Journal of Multimedia Trend and Technology
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/jmtt.v4i3.97

Abstract

Smartphones are a double-edged sword for teenagers; on the one hand, these devices provide a window to vast knowledge. However, the dark side of smartphones emerges when uncontrolled use is linked to mental health and exposure to negative content. Problematic smartphone use (PSU) occurs in 12–37% of adolescents and has been associated with sleep disturbances, depressive symptoms, and deterioration in academic functioning. Methods: We have trained an interpretable decision tree over a 1,000-participant dataset using stratified 80:20 splitting, class balancing, one-hot encoding, and grid search using cross-validation. Results: The model achieved 85.2% test accuracy (CV mean 85.0% ± 1.5%). Primary predictors were screen time per day (risk for >5.3 h/day associated with 4.3× increased risk), social media exposure (more than >2 h/day), and app variety (more than >5 apps/day). Extractable rules (e.g., >6.5 h screen time ∧ >2 h social media 92% precision for "high" addiction) permit tiered intervention thresholds. Conclusions: An interpretable decision tree provides strong prediction and converts insights into actionable behavioral thresholds for parents, schools, and developers for the purpose of early PSU intervention.
Classification of Hate Speech in TikTok Social Media Comments Using Naive Bayes Algorithm and TF-IDF Weighting Utami , Putri Febi; Krisbiantoro, Dwi; Santiko, Irfan; Riyanto, Andi Dwi
Journal of Multimedia Trend and Technology Vol. 4 No. 3 (2025): Journal of Multimedia Trend and Technology
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/jmtt.v4i3.102

Abstract

This research focuses on the classification of hate speech in Indonesian Tik Tok comments. Tik Tok, as a social media platform with high interaction intensity, generates a large volume of comments with diverse linguistic characteristics, including the use of formal and informal language. This linguistic variation poses challenges in the content moderation process, particularly in automatically identifying hate speech. The research dataset is secondary data obtained by combining public datasets and scraped Tik Tok comments, with an initial total of 5,698 comments. The collected data represent general user comments with variations in formal and informal language. To improve data quality, pre-processing stages were carried out including text cleaning, tokenization, normalization, stop-word removal, and stemming. After pre-processing, 4,542 comments were obtained that were suitable for use in the modeling process. Experimental results show that the Multinomial Naïve Bayes model with TF-IDF weighting is able to classify hate speech with high performance. Model accuracy reached 93% before parameter optimization and increased to 95% after hyperparameter tuning with an alpha value of 0.5. The confusion matrix results show a relatively low misclassification rate, although the class distribution in the dataset still shows imbalance. The findings of this study indicate that the Multinomial Naïve Bayes approach is effective in recognizing linguistic patterns of hate speech in Indonesian TikTok comments, including text with informal language characteristics.
PERANCANGAN SISTEM INFORMASI POSYANDU BERBASIS WEBSITE SEBAGAI IMPLEMENTASI E-GOVERNMENT DESA MENGGUNAKAN DESIGN THINKING Firmani, Eka; Krisbiantoro, Dwi; Wulandari, Oca Meilika
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 2 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i2.11521

Abstract

Posyandu as a community-based health service still faces problems in data management carried out manually using conventional books, causing data to be prone to loss, unintegrated, and limited access to health information for the community. This condition hinders the effectiveness of health services for toddlers and the elderly at the village level. This study aims to design and develop a website-based Smart Health Village information system as an implementation of e-government at the village level using the Design Thinking approach. The Design Thinking method is applied through five stages, namely Empathize, Define, Ideate, Prototype, and Test, which enables system development based on the actual needs of users. The system development involved three posyandu cadres and six residents as informants. The resulting system has three user roles, namely Admin, Village Apparatus, and Residents, with main features including toddler and elderly data management, health examination recording, posyandu activity scheduling, and reports that can be exported to PDF format. System testing was carried out using the Black Box Testing method with twelve testing scenarios which showed that all functional features of the system ran as expected. With this system, it is hoped that posyandu health services can potentially improve service efficiency digitally, accurately, and sustainably as a concrete manifestation of e-government implementation at the village level.
PERANCANGAN WEBSITE MONITORING POSYANDU UNTUK DETEKSI DINI STUNTING DAN RESIKO PENYAKIT LANSIA Wulandari, Oca Meilika; Firmani, Eka; Krisbiantoro, Dwi
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 2 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i2.11531

Abstract

Healthcare service management at the village level is often hindered by manual and non-integrated recording systems, which limit early detection of health risks. This study aims to design a SmartHealth Village website using the Next.js framework to digitally monitor the health status of toddlers and the elderly, employing a Research and Development (R&D) method with a Waterfall model, conducted at Posyandu Desa Teluk, Purwokerto Selatan, Banyumas. Data were collected through observation and interviews with 9 informants consisting of 3 Posyandu cadres, 3 residents, and 3 village officials. The system automates the calculation of toddlers' nutritional status (stunting) based on WHO Z-Score standards and classifies hypertension and diabetes risk in the elderly based on JNC VII and Kemenkes RI (2020) guidelines. The website provides multi-level access for admin cadres, residents, and village officials, supported by a chatbot feature as a health education assistant. Functional testing using black-box testing showed that all 11 main features ran successfully. Performance evaluation indicated that data search time decreased from ±5–10 minutes to ±2–5 seconds, report generation time decreased from ±2–3 days to ±10–15 seconds, and calculation error rate decreased from ±10% to less than 1%, demonstrating that this platform is an efficient solution for transforming village-level healthcare management into a more transparent and responsive system.
Co-Authors Abdul Aziz Achsan, Charir Maulana Adam Prayogo Kuncoro Amrillah, Sigit Fathu Andi Dwi Riyanto Andriyanto, Sabdo Bagus Baihaqi, Wiga Maulana Baihaqi, Wiga Maulana Cahyani Candrakasih, Maria Angelina Cantika, Nourma Islam Dewi Emha Taufiq Luthfi Falah, Ilfa Jawahiril Fandy Setyo Utomo Fauziyah, Rahma Sari Firmani, Eka Firmanysah, Ismail Alfi Hermawan, Sabana Nur Rizki Imtiyaz, Azmi Irfan Santiko Jayawarsa, A.A. Ketut M. Suyanto, M. Mohammad Imron Muaziz, Imam Mustofa, Dinar Nafi, Sulthon Fadhlun Nur Wachid Adi Prasetya Nuraini , Rema Sekar Pratama, Irfan Pratama, Yudha Pungkas Subarkah Putra, Akbar Andhika Rahmah, Anisa Aulia Riyanto Riyanto Sarmini Sarmini Setiawan, Ito Setiyoko, Sigit Setyaningsih, Gustin Sitaresmi Wahyu Handani, Sitaresmi Wahyu Tarwoto, Tarwoto Uswatun Hasanah Utami , Putri Febi Via Alfilaeni Waluyo, Retno Wanti, Linda Perdana Wulandari, Oca Meilika