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Implementation and Performance Analysis of Mel Frequency Cepstral Coefficient Features in Dangdut Music Sub-Genre Classification I Nyoman Surya Jaya; Tria Hikmah Fratiwi; I Gede Harsemadi; I Dewa Made Dharma Putra Santika; Ni Putu Nanda Maharani; Putu Andiny Julia Putri Rapayana
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12760

Abstract

This study investigates the classification of dangdut music sub-genres using Mel-Frequency Cepstral Coefficients (MFCC) and machine learning approaches. The objective is to evaluate the effectiveness of MFCC in representing audio characteristics and to compare the performance of several classification algorithms, including K-Nearest Neighbor (K-NN), hybrid K-NN optimized with Genetic Algorithm (GA), Support Vector Machine (SVM), and Decision Tree. The dataset consists of 730 audio samples with a duration of 30 seconds each, categorized into three sub-genres: classic dangdut, rock dangdut, and koplo dangdut. The research process includes audio segmentation, extraction of 13 MFCC coefficients, data normalization, train-test splitting (70:30), and performance evaluation using accuracy, precision, recall, F1-score, confusion matrix, and cross-validation. The results indicate that MFCC provides discriminative feature representations, as demonstrated by improved cluster separation in PCA after normalization. Among the evaluated models, hybrid K-NN with GA achieved the highest accuracy of 98.90%, outperforming conventional K-NN, SVM, and Decision Tree. Confusion matrix analysis showed that most samples were correctly classified, with only minor misclassifications between sub-genres sharing similar audio characteristics. Furthermore, consistently high cross-validation accuracies and low standard deviation values confirmed good generalization capability and suggested the absence of significant overfitting. Overall, the findings demonstrate that MFCC is an effective feature for dangdut music sub-genre classification, while normalization and GA-based optimization significantly improve classification performance and model robustness.
Co-Authors A.A Putu Ratih Maha Yoni A.A. Gde Adi Indrawan, A.A. Gde Akmal Ibnu Rosyadi Anak Agung Ngurah Bagus Ananda Kusuma Budaya, I Gede Bintang Arya Dandy Pramana Hostiadi Dedy Panji Agustino Dedy Panji Agustino Dedy Panji Agustino, Dedy Panji Dewa Ayu, Dewa Ayu Mirna Wati Gede Indra Raditya Martha I Dewa Made Dharma Putra Santika I Dewa Made Dharma Putra Santika I Gede Putra Mas Yusadara I Gusti Ayu Desi Saryanti I Gusti Ngurah Darma Paramartha I Gusti Nyoman Triska Subandi, I Gusti Nyoman Triska I Kadek Rudyanto, I Kadek I Komang Dharmendra I Komang Kardiyasa I Komang Rinartha Yasa Negara I Made Adi Krisma Dinata I Made Adi Krisma Dinata I Made Adi Purwantara I Made Darma Susila, I Made Darma I Made Pasek Pradnyana Wijaya I Nyoman Kusuma Wardana I Nyoman Surya Jaya I Putu Adi Wijaya, I Putu I Putu Agus Ardiana, I Putu Agus I Putu Indra Agastya Lupika Jaya, I Putu Indra Agastya I Wayan Ananta Setiabudi I Wayan Gede Lamopia Indah, Hene Nor Kadek Agus Wirawan Luh Gede Surya Kartika Luh Gede Surya Kartika Luh Gede Surya Kartika, Luh Gede Luh Rediasih M. Alvinnur Filardi Made Sudarma Martha, Gede Indra Raditya Muchammad Naseer Ni Kadek Alvin Surya Bagnesa Ni Kadek Sukerti Ni Luh Putu Sintya Budyawati Ni Luh Ratniasih Ni Luh Ratniasih, Ni Luh Ni Made Dewi Purnama Sari Ni Made Dewi Purnama Sari, Ni Made Dewi Ni Putu Nanda Maharani Ni Putu Putri Ayu Wijayanthi Ni Wayan Deriani, Ni Wayan Nyoman Pramaita P, I Gst Agung Ayu Uttami Vishnu Pande Putu Gede Putra Pertama Pande, I Made Suandana Astika Pratama, P.T. Eka Yudhi Putu Andiny Julia Putri Rapayana Putu Sinta Puspadewi, Putu Sinta Putu Tjintia Kencana Dewi Ratih Maha Yoni, A.A. Putu Ricky Aurelius Nutanto Diaz, Ricky Aurelius Ririn Ramadhani, Ririn Satya Tunggul Wijayanto, Satya Tunggul Tria Hikmah Fratiwi Triana Wasitama Putra, Triana Vishnu P, I Gst Agung Ayu Uttami Wulandari, Riza Yusadara, I Gede Putra Mas