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All Journal Jurnal Kridatama Sains dan Teknologi Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara)
Kumarahadi, Brigitta Melati
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences

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PENERAPAN METODE HIERARCHICAL CLUSTERING UNTUK PENGELOMPOKAN KOTA/KABUPATEN DI INDONESIA BERDASARKAN INDIKATOR KEMISKINAN Kumarahadi, Brigitta Melati; Pratiwi, Hasih; Subanti, Sri
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 11, No 2 (2023): Jurnal Tikomsin, Vol. 11, No. 2, Oktober 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v11i2.754

Abstract

In 2024, the government sets a poverty target in Indonesia of 6-7%. Until September 2022, poverty still shows a figure of 9.57%. To achieve the target, it is necessary to determine priority areas so that government policies can be right on target. This study aims to group cities/regencies in Indonesia based on poverty indicators as a solution to obtain priority areas using the clustering method. This method is used to collect data into several groups based on the same criteria. Hierarchical clustering consists of several methods, including agglomerative nesting such as single linkage, complete linkage, average linkage, and Ward linkage, and divisive analysis. The results showed that the agglomerative nesting average linkage method is the better method because it has a greater cophenetic value and silhouette coefficient value, which is 0.90 and 0.71. The clustering results consist of two clusters, cluster 1 contains 493 areas with low poverty and cluster 2 contains 21 areas with high poverty.
Sistem Rekomendasi Makanan Kucing Menggunakan Metode Content-Based Filtering Kumarahadi, Brigitta Melati; Kumarahadi, Yovita Kinanti; Ridhwanullah, Dziky
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1471

Abstract

Cats are popular pets because they have cute behavior and adorable physical appearance. Caring for cats does require extra attention, especially when feeding them. Providing food that suits their needs is very important for optimal growth and preventing various health problems. The cat food recommendation system is the right solution for cat owners to choose food that suits their cat's needs. A recommendation system is a system designed to help users get recommendations for items that are relevant and useful. Content based filtering is a recommendation system that provides suggestions based on user preferences for several items, including age, variant, brand, taste, size and price. The data used is cat food products with the brands Whiskas, Cat Choize, Me-O, and Royal Canin at the Pet Shop Colomadu. The recommendation value is calculated based on the cosine similarity value between two items. System testing is carried out using functionality testing (blackbox) and validity testing. The results of functionality testing show that the system can function well. The results of validity testing show that the system is valid and can be used appropriately. It can be concluded that the cat food recommendation system using the content-based filtering method can be used to recommend the right cat food
Co-Authors Kumarahadi, Yovita Kinanti pratiwi, hasih Ridhwanullah, Dziky Sri Subanti