The Implementation of Decision Support System in Recruiting Prospectives Employees at SMK Telkom Malang Using Fuzzy Tsukamoto Method
Bias Damiasa, Pashatania Fitri Indah Lestari, Anik Nur Handayani
Available Online January 2019.
- https://doi.org/10.2991/icovet-18.2019.58How to use a DOI?
- Decision Support System, Recruitment, Fuzzy Tsukamoto
- Vocational graduates are expected to fill job vacancies according to the needs of the business / industry. With the increasingly fierce labor market competition, graduates from Vocational High Schools are expected to not only have competency but also excellent soft skills in order to have a great chance of being accepted to work in the desired industry. PT. Visionet Internasional is one of the companies that from year to year always conducts recruitment process for prospective employees from 12th grade students at SMK Telkom Malang. The number of students willing to participate in the program which are not balanced with the number of staff and the short amount of time to select prospective employees is feared to affect the final results of recruitment. To get the expected results, a decision support system was developed to provide recommendations for PT Visionet in accepting or rejecting prospective candidates. This system is web based and applies the Fuzzy Tsukamoto algorithm. The Spearman Correlation test used to compare the results from system and experts shows a high level of accuracy, with rs value 0.739394.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Bias Damiasa AU - Pashatania Fitri Indah Lestari AU - Anik Nur Handayani PY - 2019/01 DA - 2019/01 TI - The Implementation of Decision Support System in Recruiting Prospectives Employees at SMK Telkom Malang Using Fuzzy Tsukamoto Method BT - 2nd International Conference on Vocational Education and Training (ICOVET 2018) PB - Atlantis Press SP - 239 EP - 245 SN - 2352-5398 UR - https://doi.org/10.2991/icovet-18.2019.58 DO - https://doi.org/10.2991/icovet-18.2019.58 ID - Damiasa2019/01 ER -