Sistem Deteksi Dini Stunting Pada Balita Menggunakan Teknik Klasifikasi Dengan Algoritma C4.5 Sebagai Upaya Penekan Angka Kasus Stunting Di Puskesmas Sumberjambe Kabupaten Jember
Abstract
Stunting is a condition of impaired growth in toddlers caused by chronic malnutrition, characterized by a height that is not appropriate for their age. According to SSGI 2022 data, Jember Regency has the highest stunting rate in East Java at 34.9%, exceeding the WHO standard (<20%). This study aims to design and develop an early detection system for stunting in toddlers at Sumberjambe Public Health Center using the C4.5 algorithm method. The type of research used is quantitative research with a data mining approach using the C4.5 algorithm and the prototyping method. The object of this study is secondary data obtained from maternal cohort books and Excel-based nutrition data from Sumberjambe Health Center, which includes data on children categorized as stunted and normal. The initial dataset consisted of 1,798 entries, and after going through a pre-processing stage, 130 clean data entries were obtained and used for analysis. The data mining process resulted in a Confusion Matrix accuracy of 83.33% and produced 34 rules that were used as knowledge for the early stunting detection system. The system was developed using the prototyping method, which includes several stages from initial planning and design to testing and user evaluation. In the construction of prototype stage, the system was built using PHP programming language with the Laravel 10 framework and tested using the black-box testing method. In the deployment, delivery & feedback stage, the system was directly tested by the nutrition team at Sumberjambe Health Center and received very positive responses. Users were satisfied with the appearance and performance of the system, with no revision requests, and fully approved the proposed prototype.
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