Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal The Journal of Information Technology, Computer Science, and Electrical Engineering
Muhammad Indra
Universitas Pembangunan Panca Budi, Indonesia

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

Found 3 Documents
Search

 1 
Analysis of Age and Gender Classification Using Decision Tree Model in the Context of Nursing Homes Andysah Putera Utama Siahaan; Muhammad Indra
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 2 (2024): June-September 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i2.61

Abstract

By leveraging Data Mining technology, specifically the Decision Tree algorithm, this study focuses on clustering data based on age and gender to enhance the efficiency and personalization of services in nursing homes. The data used spans from January 2024 to April 2024, encompassing 333 rows that have been processed for classification purposes. The developed Decision Tree model accurately separates the data based on age, with results showing the gender distribution within each age group. These findings indicate that the Decision Tree algorithm is effective in identifying gender based on specific age boundaries, which can be applied to improve the quality and effectiveness of nursing home services. The analysis provides valuable insights for better planning and management of social services, making this approach relevant for demographic data management in nursing homes.
Analysis of Room Allocation Based on Age in Nursing Homes Using the C4.5 Decision Tree Method Zulham Sitorus; Muhammad Indra
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 2 (2024): June-September 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i2.64

Abstract

This study analyzes the effectiveness of the C4.5 Decision Tree algorithm in managing room allocation in nursing homes based on the residents' ages. Using a dataset of 333 entries, which includes age and room names, the study aims to determine the most suitable room placements. The analysis process involves preprocessing the data to simplify the dataset, followed by the application of the C4.5 Decision Tree model using the RapidMiner platform. The results indicate that the algorithm effectively classifies residents into room names such as Jambu, Nenas, Jeruk, and others based on their age. These findings provide insights into how age influences room placement in nursing homes and enable more optimal facility management. The study also recommends considering additional factors in further analyses to enhance the accuracy of resident placement.
Analysis of Nursing Home Residents' Identity Completeness Classification Using the Decision Tree Algorithm Muhammad Indra; Darmeli Nasution
Journal of Information Technology, computer science and Electrical Engineering Vol. 1 No. 2 (2024): June-September 2024
Publisher : Yayasan Sinergi Multidimensi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jitcse.v1i2.65

Abstract

This study evaluates the effectiveness of the Decision Tree algorithm in classifying the completeness of nursing home residents' identities based on age. The data used includes identity information from 333 residents, encompassing both Family Cards and Identity Cards (KTP). By applying the Decision Tree C4.5 algorithm, the data is classified into the categories of Incomplete, Sufficiently Complete, and Complete. The analysis results indicate that older residents tend to have less complete identities compared to younger residents. These findings highlight the effectiveness of the Decision Tree algorithm in identifying patterns within identity data, facilitating service planning and administrative management in the nursing home, and ensuring regulatory compliance. This research provides a foundation for improving identity management systems and can be used to optimize administration and protection in nursing homes.
Co-Authors Andysah Putera Utama Siahaan Darmeli Nasution Zulham Sitorus