SREDO: MEDIA PEMBELAJARAN BAHASA INGGRIS DENGAN FITUR OBJECT DETECTION DAN SPEECH RECOGNITION

Authors

  • Arif Setiawan Universitas Muhammadiyah Surakarta
  • Dwi Yuliandika Saputra Universitas Muhammadiyah Surakarta

DOI:

https://doi.org/10.31000/jika.v7i4.8385

Abstract

Media pembelajaran dengan fitur object detection dan speech recognition merupakan salah satu inovasi dalam melaksanakan proses pembelajaran. Penelitian ini memiliki tujuan meningkatkan semangat siswa dalam  pembelajaran serta menambah inovasi baru sebagai sarana media pembelajaran di Sekolah Dasar dengan menggunakan aplikasi SREDO. Metode penelitian yang digunakan yaitu Research and Development (R&D) dengan model pengembangan 4D (Define, Desain, Development & Disseminate). SREDO merupakan aplikasi media pembelajaran yang digunakan untuk pengenalan nama buah dalam bahasa inggris melalui suara siswa maupun bisa juga melalui scan foto buah secara langsung. Media ini dikembangkan dengan menggunakan software MIT App Inventor dan Google Speech.  Penelitian ini melibatkan serangkaian evaluasi untuk menguji fungsionalitas, kompatibilitas, dan validitas. Uji fungsionalitas dilakukan melalui pengujian blackbox dengan tingkat keberhasilan 100%. Uji kompatibilitas dengan Firebase Test Lab pada lima perangkat berbeda menunjukkan tingkat keberhasilan 100%. Evaluasi oleh ahli media dilakukan oleh tiga ahli dengan hasil 87% menandakan validitas dan kesesuaian media tersebut. Evaluasi oleh ahli materi yang melibatkan seorang guru bahasa Inggris menghasilkan nilai 89% menandakan kesesuaian media tersebut dengan tujuan pembelajaran. Evaluasi oleh 33 siswa, menggunakan (SUS) menghasilkan nilai rata-rata 84,09, yang mengindikasikan tingkat kegunaan yang sangat baik dan dapat diterima. Secara keseluruhan, aplikasi media SREDO yang telah dikembangkan terbukti sangat cocok dan efektif untuk pengenalan buah dalam bahasa Inggris di Sekolah Dasar.

References

Agustin, I. N. N., & Supriyanto, A. (2020). Permasalahan Pendidikan Di Indonesia. Seminar Nasional Arah Manajemen Sekolah Pada Masa Dan Pasca Pandemi Covid-19.

Alajrami, M. A., & Abu-Naser, S. S. (2019). Type of Tomato Classification Using Deep Learning. 3(12), 5.

Christian, Y., & Olwin, O. (2022). Perancangan dan Pengembangan Website Sekolah di SMA Katolik Yos Sudarso Menggunakan Metode 4D. National Conference for Community Service Project (NaCosPro), 4(1), 1162–1168.

Dalilah, W. K., & Sya, M. F. (2022). Problematika Berbicara Bahasa Inggris pada Anak Sekolah Dasar. KARIMAH TAUHID, 1(4), 474–480.

Darmawan, E. W., & Suparman, S. (2019). Design of Mathematics Learning Media based on Discovery Learning to Improve Problem Solving Ability. Indonesian Journal on Learning and Advanced Education (IJOLAE), 1(2), 20–28. https://doi.org/10.23917/ijolae.v1i2.7564

Dasmen, R. N., Fatoni, F., Wijaya, A., Tujni, B., & Nabila, S. (2021). Pelatihan uji kegunaan website menggunakan System Usability Scale (SUS). ABSYARA: Jurnal Pengabdian Pada Masyarakat, 2(2), 146–158.

Dobrev, D. (2012). A Definition of Artificial Intelligence (arXiv:1210.1568). arXiv. http://arxiv.org/abs/1210.1568

Fadhilah, Z., & Marpaung, N. L. (2023). Pengenalan Alfabet SIBI Menggunakan Convolutional Neural Network sebagai Media Pembelajaran Bagi Masyarakat Umum. Jurnal Informatika: Jurnal Pengembangan IT, 8(2), 162–168.

Fitri, S. F. N. (2021). Problematika kualitas pendidikan di indonesia. Jurnal Pendidikan Tambusai, 5(1), 1617–1620.

Liesnaningsih, L., Kasoni, D., & Djamaludin, D. (2022). Prototype Robot Penyemprot Disinfektan Dengan Metode Research And Development. JIKA (Jurnal Informatika), 6(2), 135. https://doi.org/10.31000/jika.v6i2.5914

MureÅŸan, H., & Oltean, M. (2021). Fruit recognition from images using deep learning (arXiv:1712.00580). arXiv. http://arxiv.org/abs/1712.00580

Naufal, M. R., Pramono, H. S., & ST, M. C. (2018). Pengembangan Aplikasi Pendeteksi Objek Lingkaran Menggunakan Metode Houghcircle Sebagai Media Pembelajaran Penginderaan Visual Robot. Proceeding The 6th Indonesia Symposium on Robotic Systems and Control (ISRSC), 193–201.

Pasaribu, A. I., Lubis, I. S., & Medriati, R. (2022). Analisis Kebutuhan Pengembangan LKPD Berbasis STEM untuk Melatih Berpikir Kritis Materi Elastisitas dan Hukum Hooke. Jurnal Ilmiah Pendidikan Fisika, 6(3), 486–495.

Putra, A. G., Hasanah, H., & Atina, V. (2018). Aplikasi Mobile Learn English Memanfaatkan Speech Recognition pada Google Voice. Jurnal Ilmiah IT CIDA, 2(2). https://doi.org/10.55635/jic.v2i2.44

Syarifuddin, I. (2019). PENGEMBANGAN APLIKASI PENDETEKSI OBJEK BERSEGI MENGGUNAKAN METODE CONTOUR SEBAGAI MEDIA PEMBELAJARAN PENGINDERAAN VISUAL ROBOT. Jurnal Pendidikan Teknik Mekatronika, 9(1).

Tarigan, R. S. (2022). KEBERMANFAATAN TEKNOLOGI SISTEM INFORMASI PADA DUNIA PENDIDIKAN DI INDONESIA.

Tegeh, I. M., Simamora, A. H., & Dwipayana, K. (2019). Pengembangan Media Video Pembelajaran Dengan Model Pengembangan 4D Pada Mata Pelajaran Agama Hindu. Mimbar Ilmu, 24(2), 158–166.

Wibisono, F., & Pramudita, D. A. (2023). Smart geometry object detection: Flat shape recognition learning media based on artificial intelligence. AIP Conference Proceedings, 2727(1).

Downloads

Published

2023-11-22

Issue

Vol. 7 No. 4 (2023): JIKA (Jurnal Informatika)

Section

Articles

License

License and Copyright Agreement

In submitting the manuscript to the journal, the authors certify that:

  • They are authorized by their co-authors to enter into these arrangements.
  • That it is not under consideration for publication elsewhere,
  • That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
  • They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
  • They agree to the following license and copyright agreement.

Copyright

Authors who publish with International Journal of Advances in Intelligent Informatics agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal. 
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

Licensing for Data Publication

International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:

Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.

Open Data and Software Publishing and Sharing

The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.

Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.

Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.