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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 JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 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 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 Economics, Econometrics & Finance Education Energy 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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Journal : Journal of Multimedia Trend and Technology

 1 
Analysis of the Quality of the “Nu-Jek” Website on User Satisfaction Using the Webqual 4.0 Model Fauziyah, Rahma Sari; Krisbiantoro, Dwi
Journal of Multimedia Trend and Technology Vol. 4 No. 1 (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.v4i1.85

Abstract

Nu-Jek is one of the rapidly growing e-commerce in the online buying and selling market. One of the mobile-based Marketplaces officially entered Indonesia in 2019. Nu-Jek has quite complete features, it can even book buses and hotel reservations. However, there are reports of problems with the missing chat feature, which can affect the quality of interaction. Then about the redesign of the UX and chat features for Nujek noted several usability issues on the main page of the application and the booking section. The study also proposed a new design to fix this problem. The purpose of this study is to analyze the quality of the Nu-Jek website using the Webqual 4.0 method with the variables usability, information quality, service interaction and their effect on user satisfaction both partially and simultaneously. The method used to analyze website quality is the WebQual 4.0 method. The results obtained in this study partially usability has a significant effect on user satisfaction. Information quality partially has a significant effect on user satisfaction. Then partially service interaction has a significant effect on user satisfaction. Simultaneously the variables usability, information quality, service interaction have a significant effect on user satisfaction.
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.
Co-Authors Abdul Aziz Achsan, Charir Maulana Adam Prayogo Kuncoro Afiana, Fiby Nur Ali, Siti Sehah 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 Firmanysah, Ismail Alfi Hermawan, Sabana Nur Rizki Imtiyaz, Azmi Irfan Santiko Jayawarsa, A.A. Ketut Lusiana, Trimo Apri 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