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All Journal Jurnal Dinamika Informatika (JDI) Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK)
Savana Putra Aditama
Universitas Negeri Surabaya
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering

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Komparasi Algoritma Naive Bayes dan Support Vector Machine pada Analisis Sentimen Komentar Instagram Laga El Clásico Barcelona vs Real Madrid Muhammad Irvan Maulana; Savana Putra Aditama; Harun Al Rosyid
Jurnal Dinamika Informatika Vol. 15 No. 1 (2026): Vol. 15 No. 1 (2026)
Publisher : Program Studi Informatika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jdi.v15i1.432

Abstract

The rapid development of information and communication technology has driven social media to become a primary platform for users to express opinions on various events, including prestigious football matches such as El Clásico between Barcelona and Real Madrid. The high level of interaction among Instagram users generates a large volume of comments with unstructured text characteristics and diverse sentiments, making automatic sentiment analysis necessary to understand public opinion trends. This study aims to analyze the sentiment of Instagram user comments related to the El Clásico match by comparing the Naive Bayes and Support Vector Machine (SVM) algorithms. The dataset consists of 1,526 comments with an imbalanced sentiment class distribution. The research stages include text preprocessing, term weighting using Term Frequency–Inverse Document Frequency (TF-IDF), and sentiment classification. The experimental results show that the SVM algorithm outperforms Naive Bayes, achieving an accuracy of 62.88% and a weighted F1-score of 0.62, while Naive Bayes achieves an accuracy of 59.53% and a weighted F1-score of 0.52. These results indicate that SVM is more effective in handling high-dimensional data and imbalanced class distributions in social media sentiment analysis.
Pengembangan Media Pembelajaran Berbasis Website "Jagat Kawruh" Menggunakan Model Problem Based Learning Pada Mata Pelajaran Informatika Savana Putra Aditama; Rindu Puspita Wibawa; I Gusti Lanang Putra Eka Prismana; Mohammad Wildan Habibi
Jurnal Ilmu Ekonomi, Pendidikan dan Teknik Vol. 3 No. 5 (2026): IDENTIK - September
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/identik.v3i5.1761

Abstract

Monotonous Computer Systems learning in vocational high schools often causes student boredom and hinders collaboration monitoring. To address this, this study developed the "Jagat Kawruh" educational website integrating Problem Based Learning (PBL) and gamification. Utilizing the Research and Development (R&D) ADDIE model, the media features an interactive maze game quiz to boost motivation. The trial involved 36 tenth-grade Software Engineering students at SMKN 2 Buduran. Expert validations confirmed the product is highly valid (media 87.22%, material 95.45%, teaching module 94.58%, evaluation 94.44%). Effectiveness tests revealed a significant improvement in conceptual understanding (Paired Sample t-Test p < 0.001) with an N-Gain of 0.49 (moderate). Furthermore, the User Experience Questionnaire (UEQ) results showed positive evaluations, peaking in the Stimulation scale (1.81/Excellent). In conclusion, "Jagat Kawruh" is proven valid, practical, and effective in facilitating interactive and independent PBL learning.  
Co-Authors Harun Al Rosyid I Gusti Lanang Putra Eka Prismana Mohammad Wildan Habibi Muhammad Irvan Maulana Rindu Puspita Wibawa