Klasifikasi Tingkat Kecanduan Gadget Pada Anak-Anak Menggunakan Algoritma Decision Tree C5.0

The rapid development of information technology has led to an increasing use of gadgets among children from an early age. Gadgets provide benefits in supporting learning processes and entertainment; however, excessive use can cause negative impacts on children’s physical, psychological, and social development, such as decreased learning motivation, mood changes, and reduced social interaction. Therefore, a solution is needed to help detect the level of gadget addiction in children at an early stage. This study aims to develop a classification system for the level of gadget addiction in children using the Decision Tree C5.0 algorithm. The system was developed using 206 questionnaire data on gadget usage behavior, the data were then processed using the Decision Tree C5.0 method to produce classifications of gadget addiction levels. The testing results show that the developed system achieved an accuracy rate of 90,24%, indicating that the Decision Tree C5.0 algorithm is capable of performing classification effectively. Therefore, this system is considered to have good performance and can be used as a supporting tool for parents and related parties in automatically detecting the level of gadget addiction in children.