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ANALISIS PERBANDINGAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS [PDF]
Media Statistika, 2015 Fuzzy C-Means (FCM) is one of the most frequently used clustering method. However FCM has some disadvantages such as number of clusters to be prespecified and partition matrix to be randomly initiated which makes clustering result becomes inconsistent ...
Baiq Nurul Haqiqi, Robert Kurniawan
doaj +6 more sources
Clustering of COVID-19 data for knowledge discovery using c-means and fuzzy c-means [PDF]
Results in Physics, 2021 In this work, the partitioning clustering of COVID-19 data using c-Means (cM) and Fuzy c-Means (Fc-M) algorithms is carried out. Based on the data available from January 2020 with respect to location, i.e., longitude and latitude of the globe, the ...
Asif Afzal +6 more
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Clustering models for hospitals in Jakarta using fuzzy c-means and k-means. [PDF]
Procedia Comput Sci, 2023 After facing the COVID-19 pandemic, national and local governments in Indonesia realized a gap in the distribution of health care and human health practitioners.
Setiawan KE +3 more
europepmc +2 more sources
PENERAPAN FUZZY C-MEANS UNTUK PENGELOMPOKKAN TINGKAT KUALITAS PENDIDIKAN DI JAWA TIMUR
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, 2023 Salah satu faktor yang menentukan apakah perkembangan manusia itu positif atau negatif adalah pendidikan. Khususnya Provinsi Jawa Timur yang memiliki angka kesenjangan mutu pendidikan antar daerah dan Lembaga.
Nurissaidah Ulinnuha +1 more
doaj +3 more sources
SEGMENTASI CITRA MENGGUNAKAN ALGORITMA FUZZY c-MEANS (FCM) DAN SPATIAL FUZZY c-MEANS (sFCM)
Kubik, 2017 Pengolahan citra merupakan salah satu aplikasi yang dimanfaatkan dalam kehidupan. Salah satu kajian pengolahan citra adalah segmentasi. Segmentasi citra dilakukan dengan banyak pendekatan, diantaranya pedekatan klastering.
Qonita Ummi Safitri +2 more
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Revisiting Possibilistic Fuzzy C-Means Clustering Using the Majorization-Minimization Method [PDF]
EntropyPossibilistic fuzzy c-means (PFCM) clustering is a kind of hybrid clustering method based on fuzzy c-means (FCM) and possibilistic c-means (PCM), which not only has the stability of FCM but also partly inherits the robustness of PCM.
Yuxue Chen, Shuisheng Zhou
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Automatic Genetic Fuzzy c-Means
Journal of Intelligent Systems, 2018 Fuzzy c-means is an efficient algorithm that is amply used for data clustering. Nonetheless, when using this algorithm, the designer faces two crucial choices: choosing the optimal number of clusters and initializing the cluster centers.
Jebari Khalid +2 more
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Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms [PDF]
Advances in Fuzzy Systems, 2015 Intuitionistic fuzzy sets (IFSs) provide mathematical framework based on fuzzy sets to describe vagueness in data. It finds interesting and promising applications in different domains. Here, we develop an intuitionistic fuzzy possibilistic C means (IFPCM)
Arindam Chaudhuri
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BarekengCluster analysis involves the methodical categorization of data based on the degree of similarity within each group to group data with similar characteristics. This study focuses on classifying poverty data across Indonesian provinces.
Dian Kurniasari +4 more
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Weighted-covariance factor fuzzy C-means clustering [PDF]
2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2015 In this paper, we propose a factor weighted fuzzy c-means clustering algorithm. Based on the inverse of a covariance factor, which assesses the collinearity between the centers and samples, this factor takes also into account the compactness of the ...
Bertrand, Isabelle +4 more
core +6 more sources