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All Journal International Journal of Health, Engineering and Technology
Ismail Abdurrozzaq Zulkarnain
Muhammadiyah University of Ponorogo
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Dentistry Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Application Of The K-Means Clustering Method In Grouping Goat Productivity In A Web-Based Monitoring System Hafizh Trisna Indarto; Ismail Abdurrozzaq Zulkarnain; Arin Yuli Astuti
International Journal of Health Engineering and Technology Vol. 5 No. 4 (2026): In Press
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v5i3.1143

Abstract

Monitoring goat productivity at Pawit Mulya Farm Pacitan was previously hampered by manual data management and the lack of systematic productivity grouping. This study aims to develop a web-based monitoring system by implementing K-Means Clustering based on body weight, birth rate, and milk production. The study used a system development approach with the Waterfall method. The study population consisted of approximately 230 goats, while the sample consisted of productivity data that met the research variables. Data collection was carried out through observation, interviews, and literature studies. Analysis used Euclidean Distance, centroid updates, convergence testing, and Silhouette Score. The results of the study produced three productivity clusters: low, medium, and high, with a Silhouette Score of 0.3312, indicating sufficient clustering quality. White Box testing produced five valid independent paths with a 100% success rate. The system can be used as a means of monitoring and grouping productivity in a structured manner, although separation between clusters still needs to be optimized.
Co-Authors Arin Yuli Astuti Hafizh Trisna Indarto