Jihad Taqwana, Friendly
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Implementasi deteksi objek pada fitur permainan tebak gambar di website kursus online bahasa inggris dengan Ml5.js Jihad Taqwana, Friendly; Lucia Kharisma, Ivana; Kamdan, Kamdan
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.6314

Abstract

This research aims to improve the user experience in learning English on the Hanna Hersop online course website by proposing the addition of a picture guessing game feature equipped with object detection. Hanna Hersop is an English Course and Training Institute (LKP), providing English language learning materials offline and online. The research results show that adding the image guessing game feature with object detection significantly improves the users' learning experience. The object detection function in the picture guessing game not only provides additional challenges in learning, but also provides a more interesting interactive experience. This picture guessing game utilizes M15.js as a JavaScript machine learning library which provides access to ML algorithms in the browser built on Tensorflow.js and JavaScript, CSS, HTML as a framework for designing picture guessing games on websites. The results of this research provide valuable insights for developers and organizers of online English courses, as well as contributing to further understanding of how digital technologies, in particular object detection, can be used effectively to improve the quality of learning. that way course participants can gain additional benefits in understanding and practicing English, creating an innovative and effective learning environment. The integration of object detection in the picture guessing game feature is an innovative solution in creating a more interesting and effective learning environment