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Journal : METIK JURNAL

Klasterisasi Prevalensi Stunting Menggunakan K-Prototype pada Data Campuran Marsandy, Aldwin Falah Hasan; Hayati, Memi Nor; Fauziyah, Meirinda
METIK JURNAL Vol 8 No 2 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i2.824

Abstract

Cluster analysis is a statistical method for grouping objects based on the similar characteristics of each object. One of the algorithms used in cluster analysis is K-Prototype, which was developed to handle mixed data, namely numerical and categorical data. The validation method used to determine the optimal number of clusters in K-Prototype cluster analysis is the Elbow method. The aim of the research is to determine the optimal number of clusters and optimal cluster results on the prevalence of stunting and indicators that influence the prevalence of stunting in Indonesia in 2022. The results of the research show that the optimal number of clusters produced is 4 clusters, using the Elbow graph the WCSS (Within Cluster Sum Square) value is obtained. optimal is 65.83. Cluster 1 consists of 2 provinces, cluster 2 consists of 7 provinces, cluster 3 consists of 10 provinces, and cluster 4 consists of 15 provinces.
Klasterisasi Prevalensi Stunting Menggunakan K-Prototype pada Data Campuran Marsandy, Aldwin Falah Hasan; Hayati, Memi Nor; Fauziyah, Meirinda
METIK JURNAL (AKREDITASI SINTA 3) Vol. 8 No. 2 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i2.824

Abstract

Cluster analysis is a statistical method for grouping objects based on the similar characteristics of each object. One of the algorithms used in cluster analysis is K-Prototype, which was developed to handle mixed data, namely numerical and categorical data. The validation method used to determine the optimal number of clusters in K-Prototype cluster analysis is the Elbow method. The aim of the research is to determine the optimal number of clusters and optimal cluster results on the prevalence of stunting and indicators that influence the prevalence of stunting in Indonesia in 2022. The results of the research show that the optimal number of clusters produced is 4 clusters, using the Elbow graph the WCSS (Within Cluster Sum Square) value is obtained. optimal is 65.83. Cluster 1 consists of 2 provinces, cluster 2 consists of 7 provinces, cluster 3 consists of 10 provinces, and cluster 4 consists of 15 provinces.
Co-Authors - Purhadi Abda Abda Alifta Ainurrochmah Anak Agung Gede Sugianthara Andi M. Ade Satriya Anjani Anjani Annabaa Aulia, Muzizah Asnita, Asnita Astuti, Putri Sri Cahyaningsih, Ariyanti Candra Dewi, Ni Luh Ayu Casuarina, Indah Putri Damayanti, Elok Dani, Andrea Tri Rian Darnah Deviyana Nurmin Dewi, Isma Diani, Milda Alfitri Fatma wati Fauzia, Rina Fauziyah, Meirinda Fidia Deny Tisna Amijaya Goenjatoro, Rito Hadisti, Zahrah Dhafina Hadistii, Zahrah Dhafiinia Hidayatullah, Aji Syarif Ibrahim, Rizky Nur Ika Purnamasari Ika Purnamasari Ika Puspita, Ika Julnita Bidangan Karima, Nabila Al Khasanah, Lisa Dwi Nurul Krisna Rendi Awalludin Lestari, Nur Aini Ayu Lupinda, Indah Cahyani M. Fathurahman Mahmuda, Siti Marsandy, Aldwin Falah Hasan Meiliyani Siringoringo Messakh, Gerald Claudio Mochammad Imron Awalludin Nabilla, Maghrisa Ayu Nana Nirwana Nanda Arista Rizki Nida, Khairun Ningsih, Eva Lestari Nohe, Darnah Andi Nur Annisa Fitri Nur Azizah Nurmin, Deviyana Oroh, Chiko Zet Paradilla, Yunda Sasha Pratiwi, Reni Purhadi - Putri Ayu Dwi Lestari, Putri Ayu Dwi Putri, Nurlia Sucianti Rahmah, Putri Aulia Rahmaulidyah, Fatihah Noor Ramadani, Kartika Rito Goejantoro, Rito Safitri, Ranita Nur Sari, Devi Nur Endah Sa’diyah, Lita Vindiyatus Sembiring, Rinawati Sifriyani, Sifriyani Sinaga, Julia Oriana Siringoringo, Meiliyani Soraya, Raihana Suerni, Widya - Surya Prangga Suyitno Suyitno Suyitno Suyitno Suyitno Suyono, Ari Krisna Syamsiar, Syamsiar Syaripuddin Syaripuddin Utami, Riska Putri Wahyuni, Nanda Anggun Yuki Novia Nasution, Yuki Novia Yuniarti, Desi