{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T04:44:01Z","timestamp":1785818641244,"version":"3.56.0"},"reference-count":0,"publisher":"State University of Malang (UM)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowledge Engineering and Data Science"],"abstract":"<jats:p>This study rigorously evaluates machine learning models for classifying culturally significant Javanese Wuku texts from the \u201cKeagamaan atau Spiritual\u201d category, a domain challenged by unique linguistic nuances and limited digitized resources. We compared Support Vector Machine (SVM), Na\u00efve Bayes, and Convolutional Neural Network (CNN) on texts from five pivotal Wuku types (Sinta, Galungan, Kuningan, Sungsang, Warigalit) sourced from sastra.org, aiming to identify the most effective computational approach. The dataset comprises N = 1419 documents (T = 751.290 tokens), with per-class document counts reported for all five Wuku types. Our evaluation uses accuracy, precision, recall, F1-score, and Area Under the Curve (AUC) under repeated stratified 5-fold cross-validation (10 repeats; 50 runs) to ensure robust estimates. CNN achieved the best performance with Accuracy = 0.92 \u00b1 [SD], Macro-F1 = 0.90 \u00b1 [SD], and AUC = 0.93 \u00b1 [SD], outperforming SVM (Accuracy: 0.87; F1-score: 0.84) and Na\u00efve Bayes (Accuracy: 0.82; F1-score: 0.78). The results underscore CNN\u2019s strong effectiveness for nuanced, context-rich text classification, offering a vital contribution to cultural heritage preservation and advancing Natural Language Processing (NLP) for under-resourced languages. From a knowledge-engineering perspective, predicted Wuku labels can serve as structured metadata to support computational indexing and retrieval of Wuku narratives in cultural information systems. Methodologically, our CNN is a lightweight, small-corpus design that uses tuned regularization (dropout\/early stopping) and multi-scale convolution to capture culturally salient n-gram cues, rather than relying on a fixed default TextCNN configuration. Future work involves expanding the dataset and exploring advanced deep learning architectures.<\/jats:p>","DOI":"10.17977\/um018v8i12025p104-117","type":"journal-article","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:48:28Z","timestamp":1770745708000},"page":"104-117","source":"Crossref","is-referenced-by-count":0,"title":["A Comparative Study of Machine Learning Models for Javanese Wuku Classification: Exploring SVM, Na\u00efve Bayes, and CNN for Cultural Texts"],"prefix":"10.17977","volume":"8","author":[{"given":"Danang Arbian","family":"Sulistyo","sequence":"first","affiliation":[{"name":"Institut Teknologi dan Bisnis Asia Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aji","family":"Prasetya Wibawa","sequence":"additional","affiliation":[{"name":"State University of Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Didik Dwi","family":"Prasetya","sequence":"additional","affiliation":[{"name":"State University of Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fadhli Almu'iini","family":"Ahda","sequence":"additional","affiliation":[{"name":"Institut Teknologi dan Bisnis Asia Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agung Bella Putra","family":"Utama","sequence":"additional","affiliation":[{"name":"State University of Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7463","published-online":{"date-parts":[[2025,1,1]]},"container-title":["Knowledge Engineering and Data Science"],"original-title":[],"language":"en","deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T03:45:15Z","timestamp":1785815115000},"score":1,"resource":{"primary":{"URL":"https:\/\/citeus.um.ac.id\/keds\/vol8\/iss1\/7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,1,1]]}},"URL":"https:\/\/doi.org\/10.17977\/um018v8i12025p104-117","relation":{},"ISSN":["2597-4637"],"issn-type":[{"value":"2597-4637","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,1]]}}}