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All Journal TEKNIK INFORMATIKA JUTI: Jurnal Ilmiah Teknologi Informasi Teknika: Jurnal Sains dan Teknologi JOIV : International Journal on Informatics Visualization JRSI (Jurnal Rekayasa Sistem dan Industri) Jurnal Pendidikan dan Konseling Jurnal Varian Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat eProceedings of Engineering SmartComp The Indonesian Journal of Computer Science IJoICT (International Journal on Information and Communication Technology) Proceeding of Community Service and Engagement
Dita Pramesti
Telkom University, Bandung
Religion Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Understanding linguistic patterns of depression and anxiety in Indonesian social media text using machine learning classification and topic modeling Dita Pramesti; Hilda Nuraliza
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 24, No. 2, July 2026
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v24i2.a1547

Abstract

The increasing prevalence of mental health disorders such as depression and anxiety calls for effective approaches to analyze psychological expressions in textual data. This study explores the linguistic markers of depression and anxiety in Indonesian social media text through an integrated model of machine learning classification and topic modeling. In contrast to earlier work primarily centered on classification performance, this work emphasizes interpretability through comparative machine learning analysis and LDA-based thematic analysis. Classification determines the expressed condition, LDA determines thematic structures that account for distinguishing patterns beyond accuracy metrics alone. The dataset consisted of 17,096 records collected from Facebook groups, reduced to 7,199 instances after removing neutral labels. TF-IDF-based feature extraction was applied using unigram and bigram representations with a maximum of 5,000 features. A comparative analysis was conducted using six classification algorithms: K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest, Decision Tree, XGBoost, and Naïve Bayes, evaluated under three train-test split scenarios (70:30, 80:20, and 90:10). SMOTE was applied to the training data to address class imbalance. SVM achieved the best performance with an F1-score of 0.903 under an 80:20 split, followed by Naïve Bayes and XGBoost, while KNN performed lowest consistently. LDA topic modeling revealed that depression-related texts were dominated by internal emotional expression, social isolation, and suicidal ideation, whereas anxiety-related texts were characterized by sudden fear, somatic physical symptoms, and social anxiety. These findings suggest that combining classification with topic modeling offers a practical foundation for developing early detection tools and Indonesian-language NLP resources for mental health discourse analysis.
Pelatihan Inovasi Kemasan Produk Berbasis Design Thinking bagi Siswa MA Ibnu Sina Soreang Dita Pramesti; Faishal Mufied Al Anshary; Taufik Nur Adi
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 3 (2026): Mei 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i3.1087

Abstract

Salah satu tantangan yang dihadapi pelajar tingkat menengah adalah keterbatasan wawasan mengenai strategi pengemasan produk yang efektif dan menarik. Kegiatan ini bertujuan meningkatkan pemahaman dan keterampilan siswa MA Ibnu Sina Soreang dalam mengembangkan ide inovatif kemasan produk untuk meningkatkan nilai jual. Topik ini dipilih karena tidak semua siswa akan melanjutkan studi ke perguruan tinggi, sehingga keterampilan kewirausahaan perlu ditanamkan sejak dini. Pendekatan design thinking digunakan untuk mendorong siswa berpikir kreatif, kritis, dan berorientasi pada kebutuhan konsumen dalam merancang kemasan yang memiliki daya tarik visual dan nilai fungsional. Metode pelaksanaan meliputi pemaparan konsep, diskusi interaktif, simulasi praktik, serta pendampingan pengembangan ide kemasan produk. Kegiatan ini berhasil memberikan pemahaman awal mengenai design thinking serta menumbuhkan kesadaran siswa akan pentingnya kewirausahaan sebagai alternatif masa depan.
Co-Authors Aditya Zhafir Dhiaulhaq Alam Rahmatulloh Alfis Salam Azwar Farrel Wirasena Berlian Maulidya Izzati Faishal Mufied Al Anshary Faishal Mufied Al Anshary Fakhrurroja, Hanif Faqih Hamami Fauzan , Daffa Surya Fauzi, Rokhman Fitria Dewi Wulandari Hilda Nuraliza Ilham Perdana Indah Nur Fitri Astuti Intan Akbar Rusmana Irfan Darmawan Karina M., Rahma Kusuma, Kemal Indra M. Rizal Bimantoro Maharani, Anggi Kusuma Maulana Purbaya, Andre Mufti, Afrizal Muhammad Ramadhan, Galih Muhammad Rizal Bimantoro Natasya Kusuma Putri Nur Widiyasono, Nur Pariswara, Endar Poedjimartojo, Naufal Avilandi Pradita Cahyani Pratama, M Fajri Bryan Putri, Natasya Kusuma Rachmadita Andreswari Rahma Karina M. Rahmat Fauzi Riska Yanu Fa’rifah Rusmana, Intan Akbar Taufik Nur Adi Vandha Pradwiyasma Widartha