Open Access
| Issue |
E3S Web Conf.
Volume 500, 2024
The 1st International Conference on Environment, Green Technology, and Digital Society (INTERCONNECTS 2023)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 7 | |
| Section | Computer Science | |
| DOI | https://doi.org/10.1051/e3sconf/202450001006 | |
| Published online | 11 March 2024 | |
- Quang Dat, T. ; Nguyen Huong Giang, L. ; Thi Tuong Loan, N. ; Van Toan, V. The prevalence of malnutrition based on anthropometry among primary schoolchildren in Binh Dinh province, Vietnam in 2016. AIMS Public Heal. 2018, 5, 203–216, doi:10.3934/publichealth.2018.3.203. [CrossRef] [Google Scholar]
- Wello, E.A. ; Safei, I. ; Juniarty, S. ; Kadir, A. ; Studi, P. ; Dokter, P. ; Kedokteran, F. ; Indonesia, U.M. ; Ilmu, D. ; Masyarakat, K. ; et al. Literature Review Faktor-Faktor yang Mempengaruhi Terjadinya Stunting pada Anak Balita. 2022, 1, 234–240. [Google Scholar]
- Yuwanti, Y. ; Mulyaningrum, F.M. ; Susanti, M.M. Faktor – Faktor Yang Mempengaruhi Stunting Pada Balita Di Kabupaten Grobogan. J. Keperawatan dan Kesehat. Masy. Cendekia Utama 2021, 10, 74, doi:10.31596/jcu.v10i1.704. [CrossRef] [Google Scholar]
- Supariasa Nyoman, I.D. ; Purwaningsih, H. Faktor-Faktor Yang Mempengaruhi Kejadian Stunting pada Balita di Kabupaten Malang. Karta Rahardja, J. Pembang. dan Inov. 2019, 1, 55–64. [Google Scholar]
- Sivanand Dynamics of the Double Burden of Malnutrition and the Changing Nutrition Reality. Physiol. Behav. 2019, 176, 139–148, doi:10.1016/S0140-6736(19)32497-3.Dynamics. [Google Scholar]
- Labolo, M. Government Policy in Handling Stunting and Malnutrition in Children during the COVID-19 Pandemic. Ayer J. 2021, 28, 80–99. [Google Scholar]
- Yuli Mardi Data Mining: Klasifikasi Menggunakan Algoritma C4 . 5 Data mining merupakan bagian dari tahapan proses Knowledge Discovery in Database (KDD) . Jurnal Edik Informatika. J. Edik Inform. 2019, 2, 213–219. [Google Scholar]
- Ula, M. ; Fachrurrazi, S. ; Rizal, R.A. IMPLEMENTATION OF DATA MINING MODELS WITH ALGORITHMS K-NEAREST NEIGHBOR IN MONITORING THE NUTRITIONAL STATUS OF CHILDREN AND STUNTING. 2023, 6, 2–7. [Google Scholar]
- Alghifari, F. ; Juardi, D. Penerapan Data Mining Pada Penjualan Makanan Dan Minuman Menggunakan Metode Algoritma Naïve Bayes. J. Ilm. Inform. 2021, 9, 75–81, doi:10.33884/jif.v9i02.3755. [Google Scholar]
- Abhirami, K. Web usage mining using fuzzy association rule. 1st Int. Conf. Emerg. Trends Eng. Technol. Sci. ICETETS 2016 – Proc. 2016, 7–10, doi:10.1109/ICETETS.2016.7603022. [Google Scholar]
- Sutarno, H.H. ; Latuconsina2, R.; Dinimaharawati3, A. Prediksi Stunting Pada Balita Dengan Menggunakan Algoritma Klasifikasi K-Nearest Neighbors Stunting Prediction in Children Using K-Nearest Neighbors Classification Algorithm. e-Proceeding Eng. 2021, 8, 6657–6661. [Google Scholar]
- Riadi, A. ; Sulaehani, R. Analisis Implementasi Preprocessing Dengan Otsu-Gaussian Pada Pengenalan Wajah. Ilk. J. Ilm. 2019, 11, 200–205, doi:10.33096/ilkom.v11i3.457.200-205. [CrossRef] [Google Scholar]
- Sadhvi Anunaya Data Preprocessing in Data Mining –A Hands On Guide Available online: https://www.analyticsvidhya.com/blog/2021/08/data-preprocessing-in-data-mining-a-hands-on-guide/. [Google Scholar]
- Santoso, M.H. Application of Association Rule Method Using Apriori Algorithm to Find Sales Patterns Case Study of Indomaret Tanjung Anom. Brill. Res. Artif. Intell. 2021, 1, 54–66, doi:10.47709/brilliance.v1i2.1228. [Google Scholar]
- Hasani, R.A. ; Soesanti, I. ; Fauziati, S. Association Rule Pada Point of Sale Swalayan Dengan Market Basket Analysis. Semin. Nas. Dan Apl. Teknol. Di Ind. 2017, 1–7. [Google Scholar]
- Ruswati, R. ; Gufroni, A.I. ; Rianto, R. Associative Analysis Data Mining Pattern Against Traffic Accidents Using Apriori Algorithm. Sci. J. Informatics 2018, 5, 91–104, doi:10.15294/sji.v5i2.16199. [Google Scholar]
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