Decision support system for determining best job vacancies with Edas algorithm.

Indonesia Central Bureau of Statistics February 2020's data showed us that there were 6.88 million Indonesian citizens who were still unemployed. One of the factors that cause unemployment is the difficulty to find job vacancies that are suitable for job seekers' skills. Generally, job seekers will find job vacancies that offer a good salary and many facilities. But, often they forget to consider the required qualifications and decide the best job vacancies for themselves based on intuition only. This is quite natural considering the limited human cognitive ability. But, decision-making that relies on only intuition alone can cause fatal consequences. Especially considering number of job vacancies is quite limited. Therefore, we can develop a decision support system to help job seekers to find job vacancies that offer the best facilities and still consider the required qualifications. Decision support system is expected to provides the best job vacancies recommendations based on criteria weight that was obtained from a survey of 100 job seekers. Criteria used to evaluate job vacancies data are salary, number of employees, number of the offered facility, number of mandatory skills, and minimum work experience. EDAS (Evaluation based on Distance from Average Solution) method is chosen to be implemented in this decision support system. EDAS method uses two measuring distances to evaluate every job vacancies data, specifically Positive Distance from Average (PDA) and Negative Distance from Average (NDA). After conducting several tests on the system by using the manual calculation method and black-box testing method, it can be concluded that the developed decision support system can give job vacancies recommendations for users. [ABSTRACT FROM AUTHOR]