📅 31 March 2023
DOI: 10.36499/jinrpl.v5i1.7834
Rancangan Sistem Klasifikasi Kekurangan Gizi Balita Dengan Metode K-Nearest Neighbor
Jurnal Informatika dan Rekayasa Perangkat Lunak
Universitas Wahid Hasyim
📄 Abstract
 Malnutrition in toddlers is a serious problem faced by developing countries like Indonesia, and the resulting long-term effects can reduce the intelligence of toddlers. The classification of the nutritional status of children under five is still carried out conventionally in community health centers. The K-Nearest Neighbor algorithm is included in a machine learning algorithm that can be used to classify one of the nutritional status classification problems. K-NN is used as a class determination algorithm for new data to be input according to the format. This research begins with a literature study, then identifies needs, followed by data collection that is planned to be used in the system to be built as well as a reference for making the design and the final stage of system design. This research succeeded in creating a system design using the Unified Model Language (UML), one use case that contains four functional systems, including uploading dataset files, displaying datasets, testing the accuracy of datasets, predicting new data, and designing system interfaces that will make system development easier..
🔖 Keywords
#malnutrition; k-nn; uml; design
ℹ️ Informasi Publikasi
Tanggal Publikasi
31 March 2023
Volume / Nomor / Tahun
Volume 5, Nomor 1, Tahun 2023
📝 HOW TO CITE
Lonang, Syahrani; Yudhana, Anton; Biddinika, Muhammad Kunta, "Rancangan Sistem Klasifikasi Kekurangan Gizi Balita Dengan Metode K-Nearest Neighbor," Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 5, no. 1, Mar. 2023.
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