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 (Yayasan Sinergi Multidimensi Kreatif, 2024)
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.