Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal International Journal of Research and Applied Technology (INJURATECH)
Soegoto, Bobi Kurniawan
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Development of A Mobile-Based Document Summarization Application Utilizing Optical Character Recognition (OCR) Laoli, Damai Saputra; Soegoto, Bobi Kurniawan
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 1 (2025): Vol 5 No 1 (2025)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Advances in mobile technology have driven the development of various applications that enhance efficiency in information processing. This study discusses the development of a mobile-based document summarization application that utilizes Optical Character Recognition (OCR) technology to extract text from physical documents and images. As opposed to other summarization software that uses OCR, this tool has a lighter design tailored for mobile users such that it becomes viable for students and professionals who desire instant summaries readily available. The application process of the software entails taking a snap of the document, extracting text through an OCR process, and generating summaries using an NLP-based Application Programming Interface (API). Evaluation results indicate that the application registered an average extraction accuracy of 95% for text and provided short and contextually correct summaries. Such results indicate the novelty and efficacy of the proposed approach in improving mobile information management productivity and efficiency
Pest Detection Application Development Android Based Diseases of Potato Plants Sutisna, Fajar Pirman; Soegoto, Bobi Kurniawan
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 1 (2025): Vol 5 No 1 (2025)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Potato (Solanum tuberosum L.) is one of major food crops with high economic value in Indonesia. But, the productivity of cardamom is generally constrained due to the attack of pests and diseases which results in quantitative as well as qualitative losses. Often, farmers are not able to quickly and accurately diagnose pests or diseases, thereby delaying control measures. The objective of this study is to create an Android application for the identification and classification of pests and diseases in potatoes, based on Teachable Machine's capabilities. The mobile phone-based application records the leaf images of potato by using a smartphone camera and processes them with a classification model, returning detection results and providing the control strategy. Their development lifecycle follows the Waterfall model, which includes communication, planning, design, construction and implementation stages. Experiments were conducted to compare the detection rate, response time, and ease of use. The results show that the application can recognize several types of pests and diseases with satisfactory accuracy and responsiveness, providing a practical tool for farmers to perform early detection and apply appropriate control measures
Co-Authors Laoli, Damai Saputra Sutisna, Fajar Pirman