Penerapan Metode Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) dalam Penerimaan Siswa Baru
- Yeni Setiani Universitas Gunadarma, Jakarta, Indonesia
-
Sanwani Sanwani
*
Universitas Nusa Mandiri, Jakarta,
Indonesia
- Nurul Aini Universitas Budi Darma, Medan, Indonesia
- Lidya Puspita Dewi Universitas Budi Darma, Medan, Indonesia
- Mesran Mesran Universitas Budi Darma, Medan, Indonesia (*) Corresponding Author
Abstract
Acceptance of new students is a school activity that occurs every year, even in the middle of the teaching year. This activity is the first step to improve the quality of education, namely choosing the quality of students. In general, the process of admitting new students is still done manually, namely by recording student data and the student selection exam schedule to the student data that has been accepted. This is one of the problems every year that can hinder the work of teachers and even school staff. Therefore, we need the right system to be used in schools so that it can assist in the acceptance of new students. One system that is able to solve these problems is the Decision Support System (SPK). . SPK aims to provide information, guide, provide predictions and direct users of information so they can make better decisions. In implementing the SPK, ranking methods are used so that the results obtained are more effective, such as the Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) Method. The Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method where it is expected that the normalization process in calculating the value of new student admissions. The Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method is a method which has a calculation level using minimum calculations and is very simple and practical for applied to the system. The Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method has a high level of flexibility and convenience on separating the subjective part that comes from an assessment process into the decision weighting criteria using several decision-making attributes. The final result showed that Angga Rifai Zul Fiqri ranked first with a final preference score of 1.0522, which was the highest among all candidates.
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