Analisis Klusterisasi Stunting Pada Balita Menggunakan Algoritma K-Medoids Untuk Mengidentifikasi Faktor Dominan

Leonardo Saragih; Nanda Sabrina Pasaribu; Novi Karlianti Harefa; Tajrin Tajrin

doi:10.30865/jurikom.v12i3.8713

Authors

Leonardo Saragih Universitas Prima Indonesia, Medan
Nanda Sabrina Pasaribu Universitas Prima Indonesia, Medan
Novi Karlianti Harefa Universitas Prima Indonesia, Medan
Tajrin Tajrin Universitas Prima Indonesia, Medan

DOI:

https://doi.org/10.30865/jurikom.v12i3.8713

Keywords:

Stunting Cluster, Toddler, K-Medoids Algorithm, Identification of Dominant Factors

Abstract

Indonesia has a very rich biodiversity, including various medicinal plants that are highly financially beneficial and health-promoting. Among these medicinal plants, temulawak and turmeric are the two most popular rhizomes widely used in traditional medicine as well as the herbal industry. However, because the shape and color of these two plants are very similar, it is often difficult to distinguish between them, especially for laypeople and new industry workers. This research developed an Android-based application that can effectively and accurately distinguish between temulawak and turmeric to address this issue. For this application, the Convolutional Neural Network (CNN) architecture of the VGG-16 model is used along with the Tsukamoto fuzzy method as an additional layer. The trials conducted on the developed model using test data showed an accuracy rate of 0.97, a recall value of 0.98, and an F1 score of 0.97. Meanwhile, the blackbox testing shows that this application functions stably without technical issues, making it ready for use. Additionally, blackbox testing shows that the system can function stably without any issues, making it suitable for real-world use.

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