Implementation of object detection in the guess the picture game feature on the english online course website with Ml5.js
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
Downloads
References
[1] Evans Fuad, Regiolina Hayami, and A. Kharisma, “Evaluasi Usabilitas Website E-Learning Umri Terhadap Mahasiswa Umri Menggunakan Metode Usability Testing,” J. CoSciTech (Computer Sci. Inf. Technol., vol. 2, no. 2, pp. 74–82, 2021, doi: 10.37859/coscitech.v2i2.3029.
[2] K. Friendly Jihad Taqwana, Ivana Lucia Kharisma, “Perancangan Aplikasi Website Kursus Bahasa Inggris Online Dengan Metode Waterfall,” pp. 46–56, 2023.
[3] B. Basori and D. Y. Cobena, “Pengembangan Media Berbasis Mind map untuk Meningkatkan Pemahaman Siswa pada Pelajaran Teknik Pengolahan Video,” Elinvo (Electronics, Informatics, Vocat. Educ., vol. 4, no. 2, pp. 97–105, 2019, doi: 10.21831/elinvo.v4i2.18434.
[4] Y. Efendi, T. Tashid, H. Yenni, U. Rio, and R. Muzawi, “Redesign Web Sekolah Metode User Centered Design,” Build. Informatics, Technol. Sci., vol. 3, no. 3, pp. 317–324, 2021, doi: 10.47065/bits.v3i3.1098.
[5] Norhayati, “Rancangan RANCANGAN APLIKASI READING COMPREHENSION BERBASIS WEB,” J. CoSciTech (Computer Sci. Inf. Technol., vol. 3, no. 3, pp. 331–340, 2022, doi: 10.37859/coscitech.v3i3.4308.
[6] I. G. T. Suryawan, I. G. A. A. A. Satyawati, I. W. A. Purnama, and I. M. D. P. Arsana, “Evaluasi Dan Redesign Website Menggunakan System Usability Scale Dan Automated Software Testing,” JST (Jurnal Sains dan Teknol., vol. 11, no. 1, pp. 18–28, 2022, doi: 10.23887/jstundiksha.v11i1.40785.
[7] C. Anwar, “Deteksi Objek Berbasis Web Menggunakan Tensorflow Js dan Coco Dataset pada Framework React Js,” J. Nas. Komputasi dan Teknol. Inf., vol. 5, no. 6, pp. 1008–1015, 2022, doi: 10.32672/jnkti.v5i6.5464.
[8] Yining, “ml5.js: Friendly Machine Learning for the Web - by Yining Shi (New York University, RunwayML),” 2020, [Online]. Available: https://www.w3.org/2020/06/machine-learning-workshop/talks/ml5_js_friendly_machine_learning_for_the_web.html
[9] P. D. Arnesia, N. A. Pratama, and F. Sjafrina, “Aplikasi Artificial Intelligence Untuk Mendeteksi Objek Berbasis Web Menggunakan Library Tensorflow Js, React Js Dan Coco Dataset,” JSiI (Jurnal Sist. Informasi), vol. 9, no. 1, pp. 62–69, 2022, doi: 10.30656/jsii.v9i1.4243.
[10] A. J. Dufan J. P. Manajang, Sherwin R.U.A., “Implementasi Framework Tensorflow Object Detection Dalam Mengklasifikasi Jenis Kendaraan Bermotor,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 8, no. 4, pp. 1821–1831, 2021, doi: 10.35957/jatisi.v8i4.1269.
[11] . Z., F. Arnia, and R. Muharar, “Deteksi Pemalsuan Citra dengan Teknik Copy-Move Menggunakan Metode Ordinal Measure dari Koefisien Discrete Cosine Transform,” J. Nas. Tek. Elektro, vol. 5, no. 2, p. 165, 2016, doi: 10.25077/jnte.v5n2.230.2016.
[12] C. Anwar, “Deteksi Objek Berbasis Web Menggunakan Tensorflow Js dan Coco Dataset pada Framework React Js,” J. Nas. Komputasi dan Teknol. Inf., vol. 5, no. 6, pp. 1008–1015, 2022, doi: 10.32672/jnkti.v5i6.5464.
Abstract views: 52 , 
pdf (Bahasa Indonesia) downloads: 27
