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All Journal Journal of Information System and Technology (JOINT) Journal of Embedded Systems, Security and Intelligent Systems
Diny Anggriani Adnas
Universitas Sulawesi Barat
Computer Science & IT

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Ensemble-Based Clickbait Detection in Indonesian Online News Dewi Fatmawati Surianto; Diny Anggriani Adnas
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.11251

Abstract

Clickbait has become a pervasive issue in online news media, particularly in the Indonesian digital information ecosystem, where sensational headlines are frequently used to attract user attention at the expense of content accuracy. This phenomenon not only degrades information quality but also contributes to the spread of misinformation. To address this challenge, this study proposes an ensemble-based machine learning approach for detecting clickbait in Indonesian-language news articles by jointly analyzing headlines and full article content. The proposed method employs Term Frequency–Inverse Document Frequency (TF-IDF) feature extraction with extended n-gram configurations to capture both lexical and contextual patterns characteristic of clickbait. Three baseline classifiers, Multinomial Naïve Bayes, Logistic Regression, and Support Vector Machine are integrated into a hard voting ensemble framework to leverage their complementary strengths. The experiments were conducted on the CLICK-ID dataset, consisting of annotated Indonesian news articles, using an 80:20 train–test split. Experimental results demonstrate that the proposed ensemble model outperforms all individual baseline classifiers, achieving an overall accuracy and F1-score of 93%. The ensemble approach shows notable improvements in recall for the clickbait class, indicating its effectiveness in minimizing false negatives. Furthermore, qualitative analysis using word cloud and bigram visualization reveals distinct linguistic patterns between clickbait and non-clickbait articles, supporting the discriminative capability of the extracted features. These findings confirm that combining TF-IDF with ensemble learning provides a robust and effective solution for clickbait detection in Indonesian online news. The proposed model contributes to the development of more reliable content filtering systems and supports efforts to improve information quality in digital media environments.
Implementasi Metode Human-Centered Design (HCD) dalam Transformasi Digital Layanan Adminduk: Redesign Layanan Berbasis WhatsApp ke Portal Terintegrasi (Studi Kasus: Disdukcapil Polewali Mandar) Diny Anggriani Adnas; Uswatun Hasanah; Nur Jayanti Putri S3
Journal of Information System and Technology (JOINT) Vol. 7 No. 1 (2026): Vol. 7 No. 1 (2026): Journal of Information System and Technology (JOINT)
Publisher : Program Sarjana Sistem Informasi, Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/joint.v7i1.12059

Abstract

The digital transformation of population administration (Adminduk) services in Polewali Mandar currently relies heavily on WhatsApp-based service innovations. While accessible, this model creates significant usability issues: unstructured service flows, lacks transparency in status tracking, and places a burden on both users and operators. This research aims to redesign this chat-based service into an efficient, integrated service portal. The method used is Human-Centered Design (HCD). This process involves qualitative analysis to map the User Journey Map and identify critical pain points within the current WhatsApp service flow. These findings will form the basis for designing a high-fidelity prototype of a service portal. The expected outcome is a functional Adminduk portal prototype that demonstrates an intuitive guided flow and transparent status tracking features. This design offers a concrete solution for the digital transformation of Adminduk services to be more accountable and user-centered.
Co-Authors Dewi Fatmawati Surianto Nur Jayanti Putri S3 USWATUN HASANAH