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All Journal Gorga : Jurnal Seni Rupa JOIV : International Journal on Informatics Visualization Wimba: Jurnal Komunikasi Visual International Journal of Advanced Science Computing and Engineering
Firosha, Ardian
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Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

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Music Recommendation Based on Facial Expression Using Deep Learning Kurniawan, -; Kurniawan, Tri Basuki; Dewi, Deshinta Arrova; Zakaria, Mohd Zaki; Saringat, Zainuri; Firosha, Ardian
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.3794

Abstract

Music's profound impact on human emotions is essential for creating personalized experiences in entertainment and therapeutic settings. This study introduces a cutting-edge music recommendation system that utilizes facial expression analysis to tailor music suggestions according to the user's emotional state. Our approach integrates a haar-cascade classifier for real-time face detection with a Convolutional Neural Network (CNN) that classifies emotions into seven distinct categories: happiness, sadness, anger, fear, disgust, surprise, and neutrality. This emotionally aware system recommends music tracks corresponding to the user's current emotional condition to enhance mood regulation and overall listener satisfaction. The effectiveness of our system was evaluated through rigorous testing, where the CNN model demonstrated a high degree of accuracy. Notably, the model achieved an overall accuracy of 84.44% in recognizing facial expressions. Precision, recall, and F1 scores consistently exceeded 84%, indicating robust performance across diverse emotional states. These results underscore the system's capability to accurately interpret and respond to complex emotional cues through tailored music suggestions. Integrating advanced deep learning techniques for face and emotion recognition enables our recommendation system to adapt dynamically to the user's emotional fluctuations. This responsiveness ensures a highly personalized music listening experience that reflects the user's feelings and potentially enhances their emotional well-being. By bridging the gap between static user profiles and the dynamic nature of human emotions, our system sets a new standard for personalized technology in music recommendation, promising significant improvements in user engagement and satisfaction.
Exploring Current Methods and Trends in Text Summarization: A Systematic Mapping Study Ahmad Raddi, Muhammad Faris Faisal; Hassan, Rohayanti; Zakaria, Noor Hidayah; Sahid, Mohd Zanes; Omar, Nurul Aswa; Firosha, Ardian
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.1654

Abstract

This paper presents a systematic mapping study of the current methods and trends in text summarization, a challenging task in natural language processing that aims to condense information from one or multiple documents into a concise and coherent summary. The paper focuses on applying text summarization for the Malay language, which has received less attention than other languages. The paper employs a three-phased quality assessment procedure to filter and analyze 27 peer-reviewed publications from seven prominent digital libraries, covering 2016 to 2024. The paper addresses two research questions: (1) What is the extent of research on text summarization, especially for the Malay language and the education domain? and (2) What are the current methods and approaches employed in text summarization, with a focus on addressing specific problems and language contexts? The paper synthesizes and discusses the findings from the literature review and provides insights and recommendations for future research directions in text summarization. The paper contributes to advancing knowledge and understanding of the state-of-the-art techniques and challenges in text summarization, particularly for the Malay language.
Co-Authors - Kurniawan, - Ahmad Raddi, Muhammad Faris Faisal Aldo Erianda, Aldo Asrinaldi Asrinaldi Dewi, Deshinta Arrova Gusman, Taufik Hendra Rotama Kurniawan, Tri Basuki Nissa, Wirda Nurul Aswa Omar, Nurul Aswa PUTRI WAHYUNI Rita Afyenni Rohayanti Hassan, Rohayanti Sahid, Mohd Zanes Saringat, Zainuri Sumema Sumema, Sumema Zakaria, Mohd Zaki Zakaria, Noor Hidayah