ANALISIS PREDIKSI KELUARGA BERESIKO STUNTING MENGGUNAKAN METODE NAÏVE BAYES DAN SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE (SMOTE)

Rizky Yaomal Malik, . (2024) ANALISIS PREDIKSI KELUARGA BERESIKO STUNTING MENGGUNAKAN METODE NAÏVE BAYES DAN SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE (SMOTE). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Stunting is a problem that is being focused on. The handling of stunting cases has been carried out since 2018 through the National Strategy for Accelerating Stunting Prevention program. The year 2024 is the end of this program, but according to the Indonesian Nutrition Status Survey Handbook 2022 the stunting prevalence rate in 2022 is still at 21.6% with a target of 14% in 2024. One way to handle stunting is to focus on reducing stunting cases and preventing additional stunting cases. Prevention of stunting cases can be done by collecting data and monitoring families at risk of stunting. So that with this prevention stage, the prevalence of stunting can decrease. Determination of a family at risk of stunting cannot be determined arbitrarily because it has factors that make a family at risk of stunting. The results of this study Naïve Bayes algorithm can predict the criteria for families at risk of stunting accurately and has high accuracy. Synthetic Minority Oversampling Technique (SMOTE) plays an important role in this because SMOTE can synthesize data on minority variables so that previously unbalanced data becomes balanced. The evaluation results of the Naïve Bayes model equipped with SMOTE have an accuracy score of 98%.

Item Type: Thesis (Skripsi)
Additional Information: No.Panggil: 2010512081 Pembimbing 1: Ika Nurlaili Isnainiyah, S.Kom., M.Sc Pembimbing 2: Catur Nugrahaeni, S.Kom., M.Kom Penguji 1: Ruth Mariana Bunga Wadu, S.Kom., M.M.S.I. Penguji 2: Sarika, S.Kom., M.Kom.
Uncontrolled Keywords: Stunting, Stunting Risk Family, Naïve Bayes, SMOTE
Subjects: R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: RIZKY YAOMAL MALIK
Date Deposited: 09 Sep 2024 04:30
Last Modified: 09 Sep 2024 04:30
URI: http://repository.upnvj.ac.id/id/eprint/31581

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