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All Journal Jurnal Masyarakat Informatika Journal of Information Systems Engineering and Business Intelligence
Ashari, Yeva Fadhilah
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Computer Science & IT

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An Ensemble-Based Approach for Detecting Clickbait in Indonesian Online Media Kurniawan, Sandy; Pramayoga, Adhe Setya; Ashari, Yeva Fadhilah
Jurnal Masyarakat Informatika Vol 16, No 1 (2025): May 2025
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.16.1.73115

Abstract

Clickbait headlines are widely used in online media to attract readers through exaggerated or misleading titles, potentially leading to user dissatisfaction and information overload. This study proposes a machine learning approach for detecting clickbait in Indonesian news headlines using classical classification models and ensemble learning. The dataset consists of labeled clickbait and non-clickbait headlines in Bahasa Indonesia, which were processed and represented using TF-IDF vectorization. Three base classifiers, Multinomial Naive Bayes, Logistic Regression, and Support Vector Machine, were integrated using soft voting and stacking ensemble methods. The experimental results indicate that the stacking ensemble model achieved the highest accuracy of 0.7728, while the voting ensemble recorded the best F1-score of 0.7080, outperforming individual classifiers. Despite these gains, the SVM model demonstrated the most substantial decline in accuracy after stopwords removal, dropping by 0.0410. These findings highlight the effectiveness of ensemble learning in enhancing clickbait detection performance and suggest potential for further optimization in model selection and integration strategies.
Factors Influencing the Use of Mobile Social Commerce Application with UTAUT2 Extended Model Hakim, Muhammad Malik; Sonia, Putrisya Novatiara; Aryotejo, Guruh; Adhy, Satriyo; Ashari, Yeva Fadhilah; Alfarisi, Salman
Journal of Information Systems Engineering and Business Intelligence Vol. 10 No. 1 (2024): February
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.10.1.25-37

Abstract

Background: Mobile social commerce is a collection of e-commerce activities accessed via mobile devices and supported by users actively engaging in commercial activities on social media. As a country with a substantial number of social media users, Indonesia has sufficient opportunities to implement mobile social commerce as application for online shopping. Objective: This study aimed to identify the factors influencing the use of mobile social commerce for online shopping, using Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). In this context, some variables were excluded, namely user behavior, price value, and moderating variables (age, gender, and experience). Additional variables considered included price saving orientation (PSO), privacy concerns (PC), social commerce construct (SCC), social support (SS), and trust (TR). Methods: Data were collected by distributing questionnaires to respondents who had used mobile social commerce for shopping, resulting in 320 collected responses. Furthermore, the collected data were analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM) method through SmartPLS 3.3.3 application. Results: The results showed that among the 17 proposed hypotheses, 6 were rejected, while 11 were accepted. Conclusion: In conclusion, the factors influencing the use of mobile social commerce consisted of effort expectancy, habit, hedonic motivation, SCC, SS, and PC. Therefore, future studies should concentrate on exploring the continued intention of users towards mobile social commerce application.   Keywords: Mobile Social Commerce, Privacy Concern, Social Construct, Social Support, UTAUT
Co-Authors Adhe Setya Pramayoga, Adhe Setya Guruh Aryotejo, Guruh Kurniawan, Sandy Muhammad Malik Hakim, Muhammad Malik Salman Alfarisi Satriyo Adhy Sonia, Putrisya Novatiara