Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal ComEngApp : Computer Engineering and Applications Journal Journal of Advanced in Information and Industrial Technology (JAIIT)
Amri Muhaimin
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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

Found 2 Documents
Search

 1 
Spatial Autocorrelation Analysis of East Java Stunting Prevalence Cases in 2023 Trimono; Amri Muhaimin; Ekacitta, Puti Cresti; Ardiani, Ardia Eva
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.689

Abstract

Stunting is one of the chronic nutritional problems occur in East Java. In 2022, the percentage of stunting in East Java reached 19.2% and decreased to 17.7% in 2023. The less significant decrease occurred due to various factors, including malnutrition, poor sanitation, and environmental influences. This study will analyze the spatial influence on the prevalence of stunting in East Java, especially in 2023. The methods used include the Morans Index and the Local Indicator of Spatial Association (LISA). Spatial correlation analysis will help in determining the pattern of regional grouping based on stunting cases. This model works by testing whether the values of a variable at a location are related to the values of the same variable at neighboring locations, with the nature of the relationship being positive (clustering) or negative (dispersion). Using stunting prevalence data in 2023, the Moran Index = 0.3233 was obtained with a Zvalue = -1.0776. This value indicates that there is positive spatial autocorrelation, but is not significant enough. Then, through the Moran Scatterplot analysis, there are indications of regional grouping in four spatial quadrants. The results of the LISA analysis show that there are five cities/regencies included in the High-High cluster (Jember, Probolinggo City, Lumajang, Malang, and Probolinggo), one area in the Low-High cluster (Situbondo), and one area in the Low-Low cluster (Gresik). These findings indicate the existence of a spatial concentration of stunting problems that can be used as a basis for developing appropriate handling strategies by the provincial government based on regions.
Detection of Ventricular Septal Defect in Pediatric Cardiac Ultrasound Videos Using Parasternal View and Faster R-CNN Nasrudin, Muhammad; Shindi Shella May Wara; Amri Muhaimin; Nur Indah Nirmalasari; Mega Rizkya Arfiana
Computer Engineering and Applications Journal Vol. 15 No. 1 (2026)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v15i1.1334

Abstract

Congenital heart disease (CHD), particularly ventricular septal defect (VSD), remains a major contributor to pediatric morbidity, while echocardiographic diagnosis is highly dependent on operator expertise and image quality. This study examines the feasibility of an object-detection-based intelligent imaging framework for localizing VSD in pediatric cardiac ultrasound videos acquired from the parasternal long-axis view. Rather than proposing a novel detection algorithm, this work adopts a system-oriented approach by evaluating the Faster R-CNN framework under practical clinical constraints, including limited annotated data and heterogeneous ultrasound characteristics. Three convolutional neural network backbones such as ResNet50, ResNet101, and Inception-ResNet V2 are comparatively analyzed within a unified detection pipeline. Experimental results indicate that the ResNet101-based model achieves the highest localization performance at an intersection-over-union threshold of 0.5, while ResNet50 provides more consistent precision across stricter localization thresholds. Although false-positive detections are observed in acoustically challenging frames, the proposed framework maintains real-time feasibility at approximately 7–8 frames per second. The findings offer practical insights into accuracy–efficiency trade-offs and backbone selection for the development of clinically aware intelligent echocardiography systems, supporting the application of information and communication technology in pediatric cardiac imaging.
Co-Authors Ardiani, Ardia Eva Mega Rizkya Arfiana Nur Indah Nirmalasari Puti Cresti Ekacitta Shindi Shella May Wara Trimono