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All Journal The Indonesian Journal of Computer Science
Tri Sundara, Tri
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Deteksi Penyakit Tanaman Padi Berbasis Android Melalui Pemanfaatan Teachable Machine Saputra, Heru; Stephane, Ilfa; Sundara, Tri; Bahri, Aulia Hidayatul
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3643

Abstract

Padi adalah tanaman pangan utama di banyak negara, termasuk Indonesia, dan pertumbuhannya sangat dipengaruhi oleh faktor lingkungan dan kualitas tanah. Namun, petani sering menghadapi tantangan dalam mengelola Organisme Pengganggu Tanaman (OPT) yang dapat merusak tanaman dan mengurangi produktivitas. Untuk membantu petani mengatasi tantangan ini, penelitian ini memanfaatkan Teachable Machine, sebuah aplikasi berbasis web untuk mendeteksi penyakit pada daun padi. Penelitian ini menggunakan dataset dari Kaggle dan melatih model dengan gambar daun padi yang terinfeksi. Hasilnya menunjukkan bahwa aplikasi ini efektif dalam mendeteksi penyakit daun padi dan dapat membantu petani dalam mengidentifikasi dan menangani hama pada tanaman padi mereka. Namun, efektivitas aplikasi ini sangat bergantung pada kualitas dan jumlah data yang digunakan untuk melatih model
Scrum Implementation in Development of Online Research Application Sundara, Tri; Setiawan, Dilly; Subkhan, Farid; Kautsar, Fitrah Rahmat
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3072

Abstract

Researchers often need a way to obtain research data through an online survey. Therefore a web-based online research application could be developed to address these needs. By using Scrum methodology, the online research application was then developed in which some challenges were found such as consistency of logic between developers in a team, relationships between different user modules, and shared debugging, among others. The challenges could be addressed by compliance with Scrum best practices and standards.
Utilizing Machine Learning and Cloud Services to Improve Disaster Information Systems Arief, Lathifah; Sundara, Tri
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3090

Abstract

Cloud services have enabled various information system developments. In this paper, we explore the use of Amazon Sagemaker cloud services and AWS Data Exchange in disaster information systems. We proposed cloud architecture for a disaster information system and found some of the datasets provided on AWS Data Exchange could be leveraged for such system.
Co-Authors Bahri, Aulia Hidayatul Ilfa Stephane Indradewa, Rhian Kautsar, Fitrah Rahmat Lathifah Arief, Lathifah Setiawan, Dilly Subkhan, Farid