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All Journal Harmonia: Journal of Research and Education Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science ILKOM Jurnal Ilmiah Journal of Applied Data Sciences Science in Information Technology Letters International Journal of Robotics and Control Systems International journal of education and learning Applied Engineering and Technology Bulletin of Social Informatics Theory and Application
Utama, Agung Bella Putra
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Arts Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Social Sciences

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Journal : Harmonia: Journal of Research and Education

 1 
Modelling Naïve Bayes for Tembang Macapat Classification Wibawa, Aji Prasetya; Ningtyas, Yana; Atmaja, Nimas Hadi; Zaeni, Ilham Ari Elbaith; Utama, Agung Bella Putra; Dwiyanto, Felix Andika; Nafalski, Andrew
Harmonia: Journal of Arts Research and Education Vol 22, No 1 (2022): June 2022
Publisher : Department of Drama, Dance and Music, FBS, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/harmonia.v22i1.34776

Abstract

The tembang macapat can be classified using its cultural concepts of guru lagu, guru wilangan, and guru gatra. People may face difficulties recognizing certain songs based on the established rules. This study aims to build classification models of tembang macapat using a simple yet powerful Naïve  Bayes classifier. The Naive Bayes can generate high-accuracy values from sparse data. This study modifies the concept of Guru Lagu by retrieving the last vowel of each line. At the same time, guru wilangan’s guidelines are amended by counting the number of all characters (Model 2) rather than calculating the number of syllables (Model 1). The data source is serat wulangreh with 11 types of tembang macapat, namely maskumambang, mijil, sinom, durma, asmaradana, kinanthi, pucung, gambuh, pangkur, dandhanggula, and megatruh. The k-fold cross-validation is used to evaluate the performance of 88 data. The result shows that the proposed Model 1 performs better than Model 2 in macapat classification. This promising method opens the potential of using a data mining classification engine as cultural teaching and preservation media.
Co-Authors Aji Prasetya Wibawa Akbari, Ade Kurnia Ganesh Andri Pranolo Anik Nur Handayani Atmaja, Nimas Hadi Ba, Abdoul Fatakhou Bambang Widi Pratolo Chuttur, Mohammad Yasser Citra, Hana Rachma Dwiyanto, Felix Andika Eddy Sutadji Fadhilla, Akhmad Fanny Ghosh , Urvi Hariyono Hariyono Haviluddin Haviluddin Haviluddin, - Hery Widijanto Izdihar, Zahra Nabila Kurniawati, Fitriana Lauretta, Giovanny Cyntia Leonel Hernandez, Leonel Mao, Yingchi Muhammad, Abdullahi Uwaisu Nabila, Khurin Nafalski, Andrew Naufal, Ayyub Ningtyas, Yana Noviani, Erina Fika Nurhalifah, Siti Paramarta, Andien Khansa’a Iffat Purnomo Purnomo Putri , Nastiti Susetyo Fanany Putri, Nastiti Susetyo Fanany Ramadhan, Sany Putra Rizqini, Fajriwati Qoyyum Saputra, Irzan Tri Setyaputri, Faradini Usha Shakti, Maharsa Caraka Shiddiqy, Jabar Ash Sucahyo, Cornaldo Beliarding Trahutomo, Dinnuhoni Triono, Alfiansyah Putra Pertama Uriu, Wako Utomo Pujianto Widiharso , Prasetya Yandratama, Hengky Zaeni, Ilham Ari Elbaith Zhou, Xiaofeng