IMPLEMENTASI DATA MINING ALGORITMA DECISION TREE UNTUK KLASIFIKASI STATUS GIZI BALITA DI KECAMATAN CILEDUG - Siti Bulkisah Bulkisah; Rini Astuti; Agus Bahtiar (Jurnal Ilmiah Informatika Komputer, 2024)
The nutritional intake plays a crucial role in supporting the physical development of toddlers; however, not all toddlers in Ciledug District receive adequate nutrition. The number of toddlers experiencing nutritional status disorders or nutritional problems fluctuates annually, influenced by the fluctuation in the total number of toddlers. Currently, 2.9% of toddlers in Ciledug District are experiencing nutritional status disorders. This study aims to implement a classification process to determine the nutritional status of toddlers in Ciledug District using the decision tree algorithm. The achieved accuracy of the results is 99.18%, with detailed predictive outcomes as follows: 2298 instances correctly predicted as normal nutrition, 23 instances correctly predicted as abnormal nutrition, 2290 instances correctly predicted as abnormal nutrition, and 15 instances correctly predicted as normal nutrition. The classification results based on age indicate that infants aged 2 weeks have normal nutrition, toddlers aged 1 to 11 months exhibit both normal and abnormal nutrition, toddlers aged 12 months have normal nutrition, toddlers aged 13 to 58 months show both normal and abnormal nutrition, and toddlers aged 59 to 61 months have normal nutrition.