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Using Convolutional Neural Network and Saliency Maps for Cirebon Batik Recognition Aditiya, Yoga; Overbeek, Marlinda Vasty; Pomalingo, Suwito
ULTIMATICS Vol 17 No 1 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i1.4026

Abstract

Cirebon Batik is one of Indonesia's cultural heritages that has its own unique patterns and motifs, reflecting the cultural richness and history of its region of origin. This study aims to address the challenges in classifying the complex motifs of Cirebon Batik by implementing Convolutional Neural Network (CNN) and Saliency Map methods. The three main motifs used are Mega Mendung, Singa Barong, and Keratonan. The dataset was obtained from various online sources and processed using image augmentation techniques. CNN is used to recognize complex visual patterns, while Saliency Map highlights important areas in the image that influence the model's decision. The results show that the developed CNN model achieved an accuracy of 82%, precision of 83%, recall of 82%, and F1-score of 82%. The use of Saliency Map provides better interpretability and enhances the understanding of the classification process
PENGEMBANGAN ALAT UKUR SKALA SELF REGULATED LEARNING PADA MAHASISWA YANG MENGALAMI BURNOUT AKADEMIK Sofa, Puput Nurbani; Andini, Dea Raisa Andini; Dya, Dhea Aprilina; Luthfiah, Khoirunnisa; Fathiarafa, Maritza; Aditiya, Yoga; Ramdani, Zulmi
IBERS : Jurnal Pendidikan Indonesia Bermutu Vol 3 No 1 (2024): IBERS: Jurnal Pendidikan Indonesia Bermutu - Juni 2024
Publisher : Yayasan Indonesia Bermutu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61648/ibers.v3i1.78

Abstract

Self-regulation is a process whereby a person can manage the achievement of their actions, evaluate their success when achieving the target. The purpose of this research is to develop a valid and reliable measurement tool to determine the level of self-regulation in students. There are 41 items given to 459 active students who ever felt physically and emotionally exhausted during college. The method used in this research is quantitative method and reading literature. The sample in this study was obtained using a non-probably sampling method with a purposive sampling technique. The results of this study obtained 16 items which became the final items with the Likert scaling model, supplemented by SPSS analysis. The self-regulated learning scale shows quite good validity 0,829, 0,712, dan 0,787 and reliability values 0.879. So that we get the development of measuring tools that are quite valid and reliable in measuring self-regulated learning in students.