Pengelompokkan Titik Wilayah di Provinsi Daerah Istimewa Yogyakarta Berdasarkan Kualitas Udara Menggunakan Algoritma Fuzzy C-Means

Dewi, Aprilia Lutviana; Firmansyah, Adrian; Hirma, Emalia Septiani; Briliyanto, Muhamad Bagus Adji; Fitri, Muti Nurjannah; Nooraeni, Rani

doi:10.24252/msa.v8i2.16745

Cited by 1 publication

(2 citation statements)

References 3 publications

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“…Then, N: research object c: number of clustering Coefficient index partition has range 1 c ≤ PCI ≤ 1. When, approached 1 has optimum clustered or has the best performance clustered for those data set [10].…”

Section: Cluster Validitymentioning

confidence: 99%

“…The previous research using Fuzzy Clustering is [8] that compare the rate of spread of COVID-19 in high-risk countries, there are three clusters and the results of the grouping show that the spread in Spain and Italy is approximately the same. Then, [9] used K-Means Clustering to group districts/cities in Central Java based on COVID-19 cases and [10] using Fuzzy Cluster Means to group the points of the Special Region of Yogyakarta based on data air quality.…”

Section: Introductionmentioning

confidence: 99%

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Clustering of COVID-19 Provinces in Indonesia Using Fuzzy Means Cluster Methods

Karisma,

Arinda,

Widayani

et al. 2023

Advances in Engineering Research

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COVID-19 is a contagious virus that has global pandemic. Indonesia has the highest infected cases of COVID-19 in South-East Asia. The aim of the research is classified provinces in Indonesia using Fuzzy Mean Cluster (FCM) based on positive cases, recovery cases, and death cases of COVID-19. The result using FCM is three clusters. Fist cluster that marked by red zone is DKI Jakarta, third cluster that marked by orange zone is West Java, Central Java, and East Java, second cluster that marked by yellow zone is other provinces in Indonesia. Validity of FCM using Partition Coefficient Index (PCI) is 95,36%. It means that using three clusters is the most optimal.

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Section: Cluster Validitymentioning

confidence: 99%