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All Journal The Journal of Information Technology, Computer Science, and Electrical Engineering
Andysah Putera Utama Siahaan
Universitas Pembangunan Panca Budi, Indonesia

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Analysis of User Age Predictions in Public Satisfaction Surveys at Public Service Malls Using Decision Tree C4.5 Andysah Putera Utama Siahaan; Ami Abdul Jabar; Nelviony Parhusip; Maida Indrayani; Sipra Barutu
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.v1i2.58

Abstract

This research analyzes the prediction of user age in the community satisfaction survey at the Public Service Mall (PSM) in Medan using the C4.5 Decision Tree algorithm. The primary objective of the study is to understand the demographic profile of users so that service managers can tailor their approaches to meet the needs of each age group. The data used includes 14,836 respondents with relevant demographic attributes. The analysis begins with data collection and preprocessing. The modeling results indicate that the Decision Tree model is effective in classifying users into age categories, including Late Senior, Early Senior, Middle Aged Adult, Young Adult, Late Teen, Early Teen, Child, and Toddler. The findings reveal a significant concentration in the Young Adult and Early Senior groups, indicating the need for adjustments in public services. The resulting recommendations aim to enhance service responsiveness to demographic needs and improve user satisfaction as well as the effectiveness of service strategies in the future.
Analysis of Property Tax Payment Compliance Classification in Tebing Tinggi City Using the C4.5 Decision Tree Algorithm Andysah Putera Utama Siahaan; Sulis Sutiono; Sugeng Pranoto; Sarifudin; Risca Sri Mentari
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.v1i2.59

Abstract

This research analyzes property tax payment compliance in Tebing Tinggi City using the C4.5 Decision Tree algorithm. With the rapid advancement of data mining technology, this analysis utilizes classification techniques to identify compliance patterns based on property tax payment data. The research methodology involves data collection, preprocessing, and building the Decision Tree model using RapidMiner. The results indicate that the Decision Tree model can effectively predict compliance levels based on attributes such as Total_Payment and Total_Bill. Individuals with higher payment and bill values tend to be compliant, while those with lower values show less compliance. These findings provide insights for authorities to design more effective strategies to improve tax compliance and identify areas that require special attention in Tebing Tinggi City.
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.
Co-Authors Ami Abdul Jabar Maida Indrayani Muhammad Indra Nelviony Parhusip Risca Sri Mentari Sarifudin Sipra Barutu Sugeng Pranoto Sulis Sutiono