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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

Implementation of the Hybrid K-Nearest Neighbour Algorithm for Dangdut Music Sub-Genre Classification Tria Hikmah Fratiwi; I Gede Harsemadi; Putu Tjintia Kencana Dewi; Luh Rediasih; M. Alvinnur Filardi; I Dewa Made Dharma Putra Santika
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9702

Abstract

This research focuses on the classification of dangdut sub-genres — classical, rock, and koplo — by collecting 136 songs from Ellya Khadam, Rhoma Irama, and Denny Caknan, each representing distinct eras of dangdut music. From these, 483 music segments of 30 seconds each were extracted and labelled with expert assistance to ensure accuracy. Six spectral features (centroid, skewness, rolloff, kurtosis, spread, and flatness) were computed and stored in a dataset divided into 70% training and 30% testing sets. The Hybrid K-NN algorithm, integrating Genetic Algorithm (GA) to optimize the k parameter, was applied and evaluated through 5-fold cross-validation. GA parameters were set to a population size of 10, 15 generations, 4-bit chromosome length, and 3-fold cross-validation during optimization. Hybrid K-NN achieved the highest accuracy of 74.31% at k=4 with a processing time of 4.86 seconds, outperforming conventional K-NN (68.75% at k=4, 0.04 seconds), Decision Tree (61.11%, 0.42 seconds), and SVM with ECOC (54.86%, 1.99 seconds). The Hybrid K-NN also demonstrated stable performance with an average accuracy of 72.04% and a standard deviation of 2.22 percent, while the average precision, recall, and F1-score were each around 0.72. Confusion matrix analysis revealed frequent misclassification of class 2 as class 1, highlighting a classification challenge. Overall, this research shows that Hybrid K-NN is more effective than the other methods in capturing data patterns, optimizing parameters, and generalizing to unseen data, though at the cost of longer computation time due to GA’s iterative optimization and validation processes.
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 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 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 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 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