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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Mathematics, Computation and Statistics (JMATHCOS)
Fadillah, Wahyu Nur
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Implementasi Partitioning Around Medoids Pada Visualisasi Penyebaran Penyakit DBD di Sumatera Utara Fadillah, Wahyu Nur; Rangkuti, Yulita Molliq; Karo, Ichwanul Muslim
Journal of Mathematics, Computations and Statistics Vol. 6 No. 2 (2023): Volume 06 Nomor 02 (Oktober 2023)
Publisher : Jurusan Matematika FMIPA UNM

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Abstract

This research aims to develop a Geographic Information System (GIS) using the PartitioningAround Medoids (PAM) method in mapping dengue hemorrhagic fever (DHF) cases in North SumatraProvince. DHF has symptoms of high fever, bleeding, and a high mortality rate if not treated quickly.Therefore, mapping DHF cases is very important in efforts to tackle and prevent this disease. The PAMmethod was used in this study to cluster the DHF case data based on similar characteristics. The firstcluster consists of 18 districts/municipalities is a low cluster, the second cluster consists of 3districts/municipalities is a high cluster, and the third cluster consists of 3 districts/municipalities is amedium cluster. The implementation of PAM is done by using the Minkwoski distance calculation methodwhere the application of the distance will be tested with the Silhouette Index on several numbers of clusters.The best number of clusters for PAM implementation is 3 clusters with a Silhouette Index value of 0.5275.
ANALYZING THE EFFECT OF SIMILARITY FUNCTIONS ON PARTITIONING AROUND MEDOIDS ALGORITHM FOR MAPPING DHF DISEASE IN NORTH SUMATRA Fadillah, Wahyu Nur; Rangkuti, Yulita Molliq; Karo Karo, Ichwanul Muslim
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0413-0426

Abstract

Dengue hemorrhagic fever (DHF) is an acute febrile illness caused by a virus through the Aedes mosquito. North Sumatra is among the three provinces with the highest incidence and mortality rates in Indonesia. Mapping of DHF cases is very important in efforts to control and prevent the disease. The Partitioning Around Medoid (PAM) algorithm is commonly used to cluster DHF cases. The idea of PAM is a clustering algorithm with a similarity-based approach to grouping objects in one cluster. There are two main focuses in the research: mapping regencies/cities based on dengue case information and analyzing the performance of several similarity functions. The dataset includes variables of incidence rate (IR), case fatality rate (CFR), larva-free rate (ABJ), and population, obtained from the North Sumatra Provincial Health Office and the Central Statistics Agency (BPS). The analysis showed that three clusters were formed in North Sumatra Province. The first cluster includes regencies/cities such as Langkat, Deli Serdang, Karo, Simalungun, Dairi, Samosir, Humbahas, North Labuhan Batu, North Padang Lawas, South Labuhan Batu, Padang Sidempuan, Nias, South Nias, North Nias, and Sibolga. The second cluster consists of regencies/cities such as Medan, Binjai, Sedang Berdagai, Tebing Tinggi, Batubara, Asahan, Tanjung Balai, Labuhan Batu, Toba, North Tapanuli, Central Tapanuli, Gunungsitoli, and West Nias. The third cluster includes the regencies of South Tapanuli and Mandailing Natal. In addition, an evaluation was conducted using the Silhouette Index to measure the quality of the clustering. Based on the comparison using distance methods (Euclidean distance, Manhattan distance, Minkowski distance, and Chebyshev distance), the highest Silhouette Index value was obtained using Chebyshev distance, which amounted to 0.527554. This value indicates reasonable cluster quality. Thus, this study contributes to the mapping of DHF cases in North Sumatra Province and can be the basis for decision-making in overcoming the disease.
Co-Authors Ichwanul Muslim Karo Karo Yulita Molliq Rangkuti