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All Journal Jurnal Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Telematika : Jurnal Informatika dan Teknologi Informasi International Journal of Advances in Intelligent Informatics JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science ILKOM Jurnal Ilmiah WIDYA LAKSANA Buletin Ilmiah Sarjana Teknik Elektro SABDAMAS Majalah Kesehatan Indonesia Science in Information Technology Letters International Journal of Robotics and Control Systems Applied Engineering and Technology Bulletin of Social Informatics Theory and Application Journal of Artificial Intelligence in Architecture Journal of Business and Information System
Andri Pranolo
Universitas Ahmad Dahlan
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
A Comprehensive Visualization for Music Education and Artificial Intelligence Sularso, Sularso; Wadiyo, Wadiyo; Cahyono, Agus; Suharto, Suharto; Pranolo, Andri
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2500

Abstract

Artificial intelligence (AI) has revolutionized traditional methods and improved decision-making and automation. AI has also been used to enhance teaching methods, student learning, and research in music education. This study will examine literature on music education and AI. This study aims to investigate significant themes, trends, and achievements in this burgeoning discipline. This study will examine scholarly articles, conference papers, and other relevant literature to explore AI's applications, issues, and future in music education. Machine learning, natural language processing, computer vision, and deep learning are utilized in music education. These techniques are used in music composition, performance evaluation, instructional support, and individualized learning. Adaptive training, real-time feedback, and intelligent music production demonstrate the transformative potential of AI. This study will illuminate the obstacles AI faces in music education. Ethical considerations, data privacy, algorithmic bias, and human competence must be thoroughly investigated. In addition, the analysis would identify knowledge deficits for future research and development. This research could assist educators, researchers, and policymakers utilize AI in music education by conducting a comprehensive literature review. This work can assist in the development of AI-based instruments, the improvement of pedagogy, and the promotion of music education.
Attention Mechanism with Kalman Smoothing Improved Long Short-Term Memory Mechanism for Obesity Weight Forecasting Pranolo, Andri; Utami, Nurul Putrie; Anasyua, Fairuz Khairunnisa
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.4633

Abstract

This study aims to evaluate and compare the performance of several variants of Long Short-Term Memory (LSTM) based models in predicting obesity weight data. The main contribution of this research was to perform an extensive assessment of the effectiveness of LSTM-based models, including the combination of Attention-LSTM with Kalman Smoothing (KS), using two different data normalization methods (Z-score and Min-Max). This research used a publicly available dataset on obesity levels based on eating habits and physical condition, available at the UCI Machine Learning Repository. The models evaluated include the standard LSTM, Attention-LSTM, KS-LSTM, and the proposed KS-Attention-LSTM. The evaluation is conducted using the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The results showed that the proposed KS-Attention-LSTM model with Min-Max normalization achieved the lowest MAPE (0.28372) and the highest R² (0.79527) among the models. This suggests that the proposed model offers advantages in terms of prediction accuracy and has a good ability to handle data variations. Therefore, the KS-Attention-LSTM model with Min-Max normalization is strongly recommended for practical implementation, particularly for time-series data prediction in the health sector. This research is beneficial and contributes an effective alternative model that improves prediction accuracy, supports decision-making in the health sector, and enriches forecasting methods. 
Co-Authors ., Suparman AA Sudharmawan, AA Abdalla, Modawy Adam Ali Achmad Fanany Onnilita Gaffar Adhi Prahara Adhi Prahara Adhi Susanto Afief Akmal Afiqa, Nurul Agung Bella Putra Utama Agus Cahyono Agus Dianto Agus Salim Aji Prasetya Wibawa Akbari, Ade Kurnia Ganesh Albas, Juan Alin Khaliduzzaman Anasyua, Fairuz Khairunnisa Andiko Putro Suryotomo Anton Satria Prabuwono Anton Satria Prabuwono Anton Yudhana Azhari, Ahmad Azlan, Faris Farhan Ba, Abdoul Fatakhou Bambang Widi Pratolo Camargo, Jair Dani Fadillah Daniel Happy Putra Drezewski, Rafal Drezewski, Rafał Elhindi, Mohamed Fachrul Kurniawan Fadhilla, Akhmad Fanny Felix Andika Dwiyanto Firdaus, Nalendra Firdaus, Nalendra Putra Ghazali, Ahmad Badaruddin Hanafi Hanafi Hariyanti, Nunik Heni Pujiastuti Heri Pramono Hoz, César De La Husnul Khotimah Ismail, Amelia Ritahani Japkowicz, Nathalie Kaswijanti, Wilis Khadir, Mohammed Tarek Khaliduzzaman, Alin Leonel Hernandez Leonel Hernandez, Leonel Mao, Yingchi Mirghani, Abdelhameed Mokhtar, Nur Azizah Mohammad Muhammad, Abdullahi Uwaisu Nanang Fitriana Kurniawan Nathalie Japkowicz Nisa, Syed Qamrun Noormaizan, Khairul Akmal Nor Amalina Abdul Rahim Nuril Anwar Nuril Anwar, Nuril Nuryana, Zalik Omar, Abdalwahab Omer, Abduelrahman Adam Onie Yudho Sundoro Paramarta, Andien Khansa’a Iffat Prayitno Prayitno Putra, Agung Bella Utama Putra, Seno Aji Rafal Drezewski Rafał Dreżewski Roman Voliansky Saifullah, Shoffan Sarina Sulaiman Sarina Sulaiman Seno Aji Putra Setyaputri, Faradini Usha Snani, Aissa Sri Winiarti Suharto Suharto Sularso Sularso, Sularso Suparman Supriadi Supriadi Taqwa Hariguna Tedy Setyadi Tri Andi, Tri Triono, Alfiansyah Putra Pertama Uriu, Wako Utama, Agung Bella Putra Utami, Nurul Putrie Wadiyo Wadiyo Wilis Kaswijanti Yingchi Mao Yingchi Mao Yingchi Mao Yingchi Mao Zhou, Xiaofeng