Tanjung, Muhammad Furqan (2025) Implementasi Metode Klasifikasi K-Nearest Neighbor untuk Mengklasifikasikan Capaian Kinerja Perbaikan Gizi di Kabupaten Padang Pariaman. Skripsi thesis, UIN Imam Bonjol Padang.
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Abstract
Nutrition is a major issue currently facing Indonesia. Nutrition problems affect intelligence, immune system strength, and the health of toddlers. One of the causes of malnutrition is insufficient intake of nutritious food. Efforts to improve nutrition are continuously made through various initiatives, and the progress is measured by evaluating whether the nutrition improvement performance has met the target, in order to determine if the efforts have been successful. The aim of this study is to classify the nutrition improvement performance achievements in Padang Pariaman Regency using the k-Nearest Neighbor method. Based on the data analysis from 2022, the optimal value of k was found to be k = 1 with an accuracy percentage of 96.47%, meaning the model is quite effective at classifying the nutrition improvement performance data of villages/sub-districts in Padang Pariaman Regency. The accuracy calculated through the confusion matrix also shows that the model is highly effective in classification, with a 100% accuracy rate, indicating that the prediction results align with the actual data. Both recall and precision metrics also show the same outcome. The analysis of the 2023 data reveals that in 2023, there are 28 villages/sub-districts that have not yet optimally addressed the issue of malnutrition.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Stunting, Nutrition, k-Nearest Neighbor, Optimal k, Data Mining |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains dan Teknologi > Prodi Sistem Informasi |
| Depositing User: | Ruang Baca FST |
| Date Deposited: | 07 Mar 2025 02:19 |
| Last Modified: | 07 Mar 2025 04:43 |
| URI: | http://repository.uinib.ac.id/id/eprint/25040 |
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