PENENTUAN TALENTA KARYAWAN BERDASARKAN MENGGUNAKAN KONSEP DATA MINING

Abstract

The human resources competency is one aspect that most affect company performances. Knowing its competence will help the decision maker to place the right man on the right place. However it can be done by analyzing the human talent. One of the conventional method that common to use is C4.5 algorithm. Conventional C4.5 method uses data crisp. In this study, it used a linguistic term as an input data because the talent test expressed using the language (linguistic term) and it is a set of data in fuzzy form. To generate the input data in the form of fuzzy was done by fuzzify the data preprocessing and further preprocessing of data results will be used for the construction of decision trees using C4.5 algorithm is then the process is called fuzzy C4.5. The result of this research is that the number of linguistic terms of attribute effect directly and significantly to system accuracy. The accuracy of Fuzzy C4.5 algorithm with 5 linguistic terms (90.1099%) is less than Fuzzy C4.5 accuracy with 3 linguistic terms (96.7033%). Fuzzy C4.5 accuracy with 3 linguistic terms has the same accuracy with conventional C4.5 (96.7033%), so we can use as an alternative solution to build classification of employee talent in PNB.