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All Journal Journal of Information Systems and Informatics International Journal of Education and Learning
Ita Aristia Saida
Nahdlatul Ulama Sunan Giri University
Computer Science & IT Education Mathematics Other

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Implementation of the Project-Based Assignment Method for Making Eco Print Totebags to Improve Student Creativity in SBdP Learning Diajeng Fatimatuz Zahro; Ita Aristia Saida
International Journal of Education and Learning Vol. 2 No. 1 (2026): International Journal of Education and Learning
Publisher : Badan Usaha Milik Desa Berkaho Pungpungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64084/ijel.v2i1.181

Abstract

Cultural Arts and Crafts (SBdP) learning in elementary schools plays an important role in developing students' creativity through meaningful practical activities. The reality in the field shows that the art learning process often still focuses on explaining theory, so students' opportunities to explore and develop creative ideas are not yet optimal. This study aims to describe the implementation of the project-based method of making eco print tote bags, the process of developing students' creativity, as well as the impact of applying this method on students' creativity in SBdP learning at MI Az-Zahro Panunggalan. This research uses a qualitative approach with a case study type of research. Data collection techniques were conducted through observation, interviews, and documentation involving teachers and students in SBdP learning activities. Data analysis was carried out through the stages of data reduction, data presentation, and drawing conclusions. Research results indicate that the application of the project task method through eco-print tote bag making activities is able to create more active, collaborative, and creative learning. Students are directly involved in the process of exploring natural materials, designing motifs, as well as practicing the creation of artworks that promote the development of creative thinking skills. In addition, project activities also increase self-confidence, interest in learning, and the ability to collaborate among students in the learning process.
Optimization of Sleep Disorder Classification Using ANN with Multi-Method Feature Selection Devi Nova Kharisma; Ifnu Wisma Dwi Prastya; Ita Aristia Saida
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1473

Abstract

Sleep disorders are health problems that can affect quality of life and have the potential to increase the risk of various chronic diseases. Therefore, a computational approach is needed to accurately and efficiently classify sleep disorders. The ANN model used has a two-layer hidden architecture with 128 and 64 neurons, respectively, and uses the ReLU activation function, equipped with a dropout layer to reduce overfitting. Three neurons with a softmax activation function make up the output layer, which produces probabilities for every class. To improve model performance, three feature selection methods were compared, namely Chi-Square, Information Gain, and Pearson Correlation. The test results showed that the ANN model without feature selection produced an accuracy of 89.3%. After feature selection, the model's performance improved significantly. The Chi-Square method produced 8 selected features with the highest accuracy of 97.3%, followed by Information Gain with 5 features and an accuracy of 97.3%, and Pearson Correlation with 3 features and an accuracy of 88.0%. The results of this study demonstrate that selecting appropriate features can significantly enhance an ANN's ability to categorize sleep problems. The proposed approach is expected to be a reference in the development of a more accurate sleep disorder diagnostic aid system.
Co-Authors Devi Nova Kharisma Diajeng Fatimatuz Zahro Ifnu Wisma Dwi Prastya