Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers
Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data m...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Informatics Department, Faculty of Computer Science Bina Darma University
2023-12-01
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| Series: | Journal of Information Systems and Informatics |
| Subjects: | |
| Online Access: | https://journal-isi.org/index.php/isi/article/view/586 |
| _version_ | 1797351892189184000 |
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| author | Melissa Indah Fianty Monika Evelin Johan Azka Aulia Mella Margareta Veronica |
| author_facet | Melissa Indah Fianty Monika Evelin Johan Azka Aulia Mella Margareta Veronica |
| author_sort | Melissa Indah Fianty |
| collection | DOAJ |
| description | Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia. |
| first_indexed | 2024-03-08T13:07:16Z |
| format | Article |
| id | doaj.art-5f2fc64d850945cbbadd3491c1c35a49 |
| institution | Directory Open Access Journal |
| issn | 2656-5935 2656-4882 |
| language | English |
| last_indexed | 2024-03-08T13:07:16Z |
| publishDate | 2023-12-01 |
| publisher | Informatics Department, Faculty of Computer Science Bina Darma University |
| record_format | Article |
| series | Journal of Information Systems and Informatics |
| spelling | doaj.art-5f2fc64d850945cbbadd3491c1c35a492024-01-18T15:58:29ZengInformatics Department, Faculty of Computer Science Bina Darma UniversityJournal of Information Systems and Informatics2656-59352656-48822023-12-01541350136210.51519/journalisi.v5i4.586586Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health CentersMelissa Indah Fianty0Monika Evelin Johan1Azka Aulia2Mella Margareta Veronica3Universitas Multimedia NusantaraUniversitas Multimedia NusantaraUniversitas Multimedia NusantaraUniversitas Multimedia NusantaraNutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia.https://journal-isi.org/index.php/isi/article/view/586data miningk-means clusteringmalnutritionnutritional statustoddlers |
| spellingShingle | Melissa Indah Fianty Monika Evelin Johan Azka Aulia Mella Margareta Veronica Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers Journal of Information Systems and Informatics data mining k-means clustering malnutrition nutritional status toddlers |
| title | Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers |
| title_full | Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers |
| title_fullStr | Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers |
| title_full_unstemmed | Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers |
| title_short | Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers |
| title_sort | application of clustering based data mining for the assessment of nutritional status in toddlers at community health centers |
| topic | data mining k-means clustering malnutrition nutritional status toddlers |
| url | https://journal-isi.org/index.php/isi/article/view/586 |
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