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All Journal Atmosfer: Jurnal Pendidikan, Bahasa, Sastra, Seni, Budaya, Dan Sosial Humaniora Jurnal Sistem Informasi dan Ilmu Komputer
Apik Banyubasa
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Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media

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Analisis Efektivitas Aplikasi Write it Japanese dalam Meningkatkan Kemampuan Menulis Hiragana dan Katakana bagi Pemula Cindy Valencia; Apik Banyubasa; Hassan Narallah Matauq; R Bramaditya Ario Wirawisesa; Humannisa Rubina Lestari
Atmosfer: Jurnal Pendidikan, Bahasa, Sastra, Seni, Budaya, dan Sosial Humaniora Vol. 3 No. 2 (2025): Jurnal Pendidikan, Bahasa, Sastra, Seni, Budaya, dan Sosial Humaniora
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/atmosfer.v3i2.1416

Abstract

This study aims to analyze the effectiveness of the Write it! Japanese application in improving the ability to write Hiragana and Katakana characters among beginners. The research involved 20 participants with no prior experience in learning Japanese. A pre-test and post-test design was employed, in which participants were asked to write 20 Hiragana and 20 Katakana characters before and after using the application independently for seven consecutive days, for 15 minutes per day. The results showed a significant increase in the average score from 45.05% (pre-test) to 79.05% (post-test), with an average improvement of 34%. The findings indicate that the Write it! Japanese application is effective in facilitating the learning process through stroke order animations, interactive writing practice, and gamified features that enhance motivation. Additionally, the application supports self-directed learning and serves as an efficient and engaging alternative medium for language acquisition. These findings reinforce the importance of integrating technology into foreign language education, particularly in the early stages of learning Japanese kana.
Penerapan Klasifikasi Gambar Buah dalam Aplikasi FruityLens Menggunakan Metode CNN Bagus Hardika; Mahesa Dzikri Kurniawan; Muhammad Adzka; Daffarizqy Prastowiyono; Apik Banyubasa; Gema Parasti Mindara; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4275

Abstract

This research develops a fruit classification system using Convolutional Neural Network (CNN) in the educational application FruityLens, which helps children recognize different types of fruits through image recognition. The application can identify four types of fruits: apple, banana, orange, and watermelon, utilizing an image dataset from open sources. The research methods include dataset collection, image pre-processing, CNN model training, and classification accuracy evaluation. The results indicate that the developed CNN model achieves high accuracy, supporting children's learning about fruits. This implementation is expected to contribute to the advancement of artificial intelligence technology, specifically in the field of fruit object recognition.
Co-Authors Bagus Hardika Cindy Valencia Daffarizqy Prastowiyono Endang Purnama Giri Gema Parasti Mindara Hassan Narallah Matauq Humannisa Rubina Lestari Mahesa Dzikri Kurniawan Muhammad Adzka R Bramaditya Ario Wirawisesa