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All Journal Tanra : Jurnal Desain Komunikasi Visual Fakultas Seni dan Desain Universitas Negeri Makassar Equilibrium: Jurnal Pendidikan JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Jurnal Mantik Journal of Music Science, Technology, and Industry (JOMSTI) Indonesian Journal of Data and Science JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Journal of Digital Law and Policy Jurnal Krisnadana Journal of Social Work and Empowerment
Ni Kadek Nita Noviani Pande
Institut Bisnis Dan Teknologi Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Classification of Gamelan Selonding Music Using Convolutional Neural Network Ni Putu Diah Pradnya Savitri; Anak Agung Gde Bagus Ariana; Ni Kadek Nita Noviani Pande; I Made Dwi Putra Asana; I Gusti Agung Indrawan
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.358

Abstract

Introduction: Balinese Selonding gamelan is an endangered sacred repertoire, and automatic recognition of its musical pieces can support documentation and preservation. Method: This study investigates the automatic classification of Selonding gamelan music using a Convolutional Neural Network (CNN). The dataset consists of 10 traditional Selonding compositions. Recordings were segmented into fixed 15-second excerpts, converted to WAV, normalized, and transformed into time–frequency features using two approaches: Mel-Frequency Cepstral Coefficients (MFCC) and Constant-Q Transform (CQT). A CNN-based classifier was trained and evaluated using 5-fold cross-validation for each feature representation. Results: The MFCC-based model achieved stable high performance, with mean accuracy of 94.67% (±2.11%), mean precision of 94.97% (±1.90%), mean recall of 94.67% (±2.11%), and mean F1-score of 94.63% (±2.12%) across folds. In contrast, the CQT-based model performed notably worse, reaching only 58.04% mean accuracy and 53.28% mean F1-score, with large variance across folds. These results indicate that MFCC features capture the discriminative timbral characteristics of Selonding more effectively than CQT under the current experimental setting. Conclusion: Overall, the findings show that a CNN trained on MFCC features can reliably distinguish Selonding compositions using only short (15-second) audio segments, despite limited data. This suggests that deep learning is a feasible strategy for indexing, retrieval, and long-term preservation of Balinese gamelan repertoires.
Digital Preservation of Balinese Heritage through Educational Game: A Case Study of Perang Pandan Tradition Komang Redy Winatha; Ni Kadek Nita Noviani Pande; Ni Kadek Dwi Dina Oktaviani
Jurnal Krisnadana Vol 5 No 2 (2026): Jurnal Krisnadana- January 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/krisnadana.v5i2.993

Abstract

Tradition is a series of long-established customs that have been continuously practiced, playing a significant role in the life of a community within a country, culture, time period, or religion. The Perang Pandan tradition is one of the unique cultural heritages of Tenganan Pegringsingan Village, Bali, embodying values of bravery and reverence for Lord Indra. This study aims to develop an Android-based Perang Pandan game by implementing the Finite State Machine (FSM) method to systematically manage character behavior and game mechanics. FSM was chosen for its advantages in controlling transitions between states—such as attacking, defending, and moving—creating an interactive and realistic gameplay experience. The game development process followed several stages: analysis, design, implementation, and testing. Black-box testing results indicate that the game runs smoothly on Android devices and successfully conveys traditional elements through engaging visuals and gameplay. Additionally, the User Experience Questionnaire (UEQ) testing revealed high scores in attractiveness, ease of use, and efficiency, highlighting the game's effectiveness in providing an enjoyable and educational experience.
Co-Authors Anak Agung Gde Bagus Ariana Aniek Suryanti Kusuma Aristamy, I Gusti Ayu Agung Mas Asana, I Made Dwi Putra Ayu Gde Chrisna Udayanie Ayu Gede Willdahlia Christina Purnama Yanti Desak Made Dwi Utami Putra Devi Valentino Waas I Gusti Agung Indrawan Ida Bagus Putrayasa Ika Amellia Rizanty Komang Redy Winatha Meinarni, Ni Putu Suci Ngakan Putu Darma Yasa Ni Kadek Dwi Dina Oktaviani Ni Luh Ade Dinda Dharma Yanti Ni Luh Wiwik Sri Rahayu Ginantra Ni Made Putri Widiantari Ni Made Suci Ariantini Ni Putu Diah Pradnya Savitri Nyoman Artana Prof. Dr. I Made Sutama,M.Pd . Putra, Putu Satria Udyana Winatha, Komang Redy