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All Journal Infotech: Journal of Technology Information DIGINTEL-AI : DIGital INnovation and inTELligence – AI
Ade Davy Wiranata
Teknik Informatika, Universitas Muhammadiyah Prof. DR. HAMKA, Jakarta
Computer Science & IT

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ANALISIS SENTIMEN TERHADAP MINAT MASYARAKAT JAKARTA YANG MEMILIH KENDARAAN UMUM MENGGUNAKAN ALGORITMA NAÏVE BAYES Yogga Tolly Dewanto; Ade Davy Wiranata; Mia Kamayani Sulaeman
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.407

Abstract

The worsening traffic congestion in Jakarta highlights the need to understand public interest in using public transportation. Social media platforms such as X serve as valuable sources of real-time public opinion data. This study aims to analyze the sentiments of Jakarta residents toward public transportation to identify the factors influencing their interest in using it. Data was collected from X and analyzed using the Naïve Bayes algorithm through the RapidMiner application. The analysis was conducted by splitting the dataset into 60% training data and 40% testing data. The results of the study show 203 positive sentiment data, 135 negative sentiment data, and 138 neutral sentiment data. Positive sentiments were mostly associated with affordability and ease of access, while negative sentiments were related to discomfort and lack of punctuality. This research is expected to serve as a reference for policymakers in improving the quality of public transportation services in Jakarta.
Perbandingan Naive Bayes Classifier dan SVM untuk Analisis Sentimen Desain Seragam Atlet Indonesia pada Media Sosial X di Olimpiade Paris 2024 Azizah Salma Nida; Irwansyah; Ade Davy Wiranata; Zuhri Halim
DIGINTEL-AI : DIGital INnovation and inTELligence – AI Vol. 1 No. 2 (2026): April
Publisher : PT Ajira Karya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66217/digintel-ai.v1i2.13

Abstract

The Olympics is an international sporting event held every four years and serves as a platform for countries to showcase their athletic capabilities and national identity. One aspect that attracts public attention is the design of athletes' uniforms, which not only have aesthetic value but also support athletic performance. Differences in public perception of these designs generate various opinions expressed on social media X. This study aims to analyze public sentiment toward the design of Indonesian athletes' uniforms at the Paris 2024 Olympics on social media X and to compare the performance of Naive Bayes Classifier and Support Vector Machine algorithms. The dataset consists of textual data collected from social media X and processed through preprocessing stages and split into training and testing data with an 80:20 ratio. The results show that there are 1,014 positive and 728 negative sentiments. Model evaluation indicates that the Naive Bayes Classifier achieved an accuracy of 80.5%, while the Support Vector Machine achieved 94.2%, outperforming the former. These findings demonstrate that the Support Vector Machine is more effective than the Naive Bayes Classifier for sentiment analysis of social media text data related to the design of Indonesian athletes' uniforms at the Paris 2024 Olympics.
Co-Authors Azizah Salma Nida Irwansyah Mia Kamayani Sulaeman Yogga Tolly Dewanto Zuhri Halim