Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal Indonesian Applied Physics Letters Journal of Educational Engineering and Environment Science and Technology: Jurnal Pengabdian Masyarakat
Imron, Arizal Mujibtamana Nanda
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Indonesian Applied Physics Letters

 1 
The Implementation of Channel Area Thresholding in Early Detection System of Acute Respiratory Infection (ARI) Fitri, Zilvanhisna Emka; Imron, Arizal Mujibtamana Nanda
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.55626

Abstract

Acute respiratory infections (ARI) are infectious diseases that affect both children and adults, particularly in the context of climate change. Bacteria are one of the causes of ARI. According to the government, the discovery of the bacteria that cause ARI is an indicator of successful management of infectious diseases. The current obstacle is the limited number of medical analysts, which results in longer microscopic examination times and requires a high level of objectivity. Therefore, a system for the early detection of ARI-causing bacteria was developed using digital image processing techniques, specifically channel area thresholding as one of the segmentation methods. This research employs four shape features for bacterial classification: the number of bacterial colonies, area, perimeter, and shape. The Naí¯ve Bayes intelligent system method is used for the classification process. The system had an accuracy rate of 86.84% in the classification of four types of bacteria: S. aureus, S. pneumoniae, C. diphteriae and M. tuberculosis
Co-Authors Abdul Madjid Fitri, Zilvanhisna Emka Hasan, Baharuddin Zamzami, Muhammad Viqih