ANALISIS KINERJA ALGORITMA CLUSTERING FUZZY TSUKAMOTO DENGAN FUZZY C-MEANS
ABSTRACT: Efforts to evaluate
employees in the work is to assess the performance of each employee. For it has
been formulated assessment is based upon work objectives according to the
position or job title, and by weighting against six indicators into three
groups. The number of data values and indicators to be used will certainly lead
to difficulties in implementation, not effective and less objective. Therefore
we need a clustering process more optimal assessment. This study aims to
analyze the performance of FCM algorithm implemented on employee performance
evaluation PT. Bank Syariah Mandiri into 3 clusters. Some of the steps that
must be performed before clustering, first performed pretreatment, namely data
cleaning and data transformation for further clustering using the algorithm.
The results of the calculations used to analyze the performance of the
algorithm with FCM Tsukamoto. Compatibility calculation value data by Tsukamoto
algorithm is pretty good and for the FCM algorithm is Very Good. FCM algorithm
can be used in the assessment of grouping data based on the three criteria of
assessment.
Penulis: Iin Parlina, Herman
Mawengkang, Syahril Efendi
Kode Jurnal: jptinformatikadd170425
