J-Icon : Jurnal Komputer dan Informatika
Vol 11 No 1 (2023): Maret 2023


Clarissa Elfira Amos Pah (Unknown)
Juan Rizky Mannuel Ledoh (Unknown)

Article Info

Publish Date
31 Mar 2023


A qualified workforce in a company is an essential asset to support the company's business goals. As a company grows, companies begin to understand patterns of qualified employees to be recruited and retained. This pattern is then used as employee recruitment criteria. However, as the number of applicants increases, companies become overwhelmed in assessing and comparing one prospective employee with another, as a result, the employee recruitment process becomes longer. One of the companies experiencing this problem is a Konsultan Teknik Informasi (KTI) Company which is the object of this research. The company, founded in 2008, has experienced an average increase in employee recruitment of 48% annually and a moderate increase in employee turnover of 11% annually. Of course, the number of applicants evaluated for acceptance will be more significant than those accepted for work. Therefore, this KTI company needs a decision support method that can quickly help select employees based on predetermined criteria and rank prospective employees who best meet the criteria. The decision support method proposed by the researcher is the Fuzzy Tsukamoto method. Fuzzy Tsukamoto is used because it can accommodate experts' opinions by making membership functions and rule base matrix. Each input value obtained from the prospective employee data is mapped in the membership functions and rule base matrix through a fuzzification process. This is then defuzzification to produce an output value that can be used to rank prospective employees. Tests carried out on three prospective employee data obtained crisp output values of 6.70, 6.58, and 6.42, respectively, with the largest value being the highest rank.

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Journal Info





Computer Science & IT


J-ICON : Jurnal Komputer dan Informatika focuses on the areas of computer sciences, artificial intelligence and expert systems, machine learning, information technology and computation, internet of things, mobile e-business, e-commerce, business intelligence, intelligent decision support systems, ...