IMPLEMENTASI CLUSTERING UNTUK MENENTUKAN STATUS STUNTING BALITA DENGAN K-MEANS

Dhesman, Dhian Veronica and Karnila, Sri (2023) IMPLEMENTASI CLUSTERING UNTUK MENENTUKAN STATUS STUNTING BALITA DENGAN K-MEANS. Skripsi thesis, Institut Informatika dan Bisnis Darmajaya.

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ABSTRACT.pdf
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Abstract

Stunting is still a significant problem in Indonesia. Indonesian nutritional status research asked that the number of toddlers who have a stunting based on BB/TB is 24.4%. Toddlers are said to be stunted when they experience slowed growth, and are susceptible to infectious diseases, and and healthy toddlers can be seen from their height and weight according to their age, being cheerful and responsive. Currently, stunting data still cannot provide an overview of the nutritional status of toddlers, so it is important to conduct research to determine the nutritional status of toddlers to get a model that can be used as information about how much stunting data there is, especially in Langkapura health centers. This research uses one of the methods available in data mining, namely K-means clustering, to categorize the nutritional status of toddlers. This research who will be grouped into 2 clusters, namely cluster 1 for stunting and cluster 2 for good (normal) nutrition. Research results show that there are 56% of normal toddlers and the remaining 44% are stunted. This can be used as a basis for a prevention model.

Item Type: Thesis (Skripsi)
Subjects: Ilmu Komputer
eSkripsi
Divisions: Skripsi/TA & PKPM/KP - Fakultas Ilmu Komputer > Sistem Informasi
Depositing User: Mrs Dhian Veronica Dhesman
Date Deposited: 07 Feb 2024 04:28
Last Modified: 07 Feb 2024 04:28
URI: http://repo.darmajaya.ac.id/id/eprint/14714

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