Implementation of The AHP And MOORA Methods For Admission Selection of Stmik Lecturers

STMIK Syaikh Zainuddin NW Anjani always strives to improve quality or internal quality sustainably as a strategy to be able to compete with other universities. The institution itself realizes that to achieve educational goals and maintain the quality of education and produce good outputs, it requires commitment, strategies, appropriate methods and adequate human resources in the process of achieving it. One way to improve the quality of a university is to select teaching staff or lecturers because the quality of lecturers will greatly determine the high and low quality of a university. Based on the problems that arise, a decision support system is needed that can handle the influence relationship between parameters for the selection process for lecturer acceptance. In this study, the Analytical Hierarchy Process (AHP) method and the MultiObjective Optimization on the Basis of Ratio Analysis (MOORA) method were used to determine alternative priorities for prospective lecturers. The AHP method is used to determine the weight of the criteria, sub-criteria and scoring data, while the MOORA method is used to calculate the final score and ranking.


Introduction
STMIK Syaikh Zainuddin NW Anjani is a private university that was established on June 12, 2006. In realizing the vision and mission of STMIK SZ NW Anjani always strives to improve the quality or internal quality on an ongoing basis as an institutional strategy to be able to compete with other universities. The institution itself realizes that to achieve educational goals and maintain the quality of education and produce good outputs, it requires commitment, strategies, appropriate methods and adequate human resources in the process of achieving it. One way to improve the quality of a university is to select teaching staff or lecturers because the quality of lecturers will greatly determine the high and low quality of a university. The selection process for lecturer admissions at STMIK SZ NW Anjani is still done conventionally, wherein determining the prospective lecturers to be accepted, the assessment process is based on the results of the tests followed by prospective lecturers with an assessment weight (0-100). Therefore, in this study, the addition of parameters in the selection process for lecturer admissions was carried out, adding parameters to the selection process aimed at getting prospective lecturers according to the needs of the institution.
To carry out the assessment process, a decision support system (DSS) is needed to assist decision-makers in making decisions, as well as to increase the effectiveness of decision making. DSS is usually built to support a solution to a problem or evaluate an opportunity [1].
The methods used in this research are the AHP (Analytical Hierarchy Process) and the MOORA (Multi-Objective Optimization On The Basis Of Ratio Analysis) method. The AHP method is used to calculate the weight value of each criterion, sub-criteria and scoring data, while the MOORA method is used to calculate the final score and ranking. Research related to the selection of lecturer admissions was carried out by Kharisma [2] using the AHP and SAW methods, the AHP method was used to find the weighted criteria and the SAW method was used to calculate the final score. Different things were done in research conducted by Anike [2] developing a decision support system for sorting outstanding employees using the AHP method, the AHP method was used to calculate the weight of the criteria and also calculate the final score. Another study was conducted by Sinaga [3] a decision support system for the selection of the best employees using the MOORA method, in this study the value of each criterion and sub-criteria have been determined by the decision-maker and the MOORA method is used to calculate the final score and ranking.
The AHP method in this study was chosen because it has advantages in determining the weights and hierarchy of criteria [5] while the MOORA method was chosen because it has a degree of flexibility and ease of understanding in separating the subjective part of an evaluation process into decision weight criteria with several decision-making attributes [6].

System Description
The methods used in this decision support system are AHP and MOORA methods. The AHP method is used to help determine the parameter weights that will be used in calculating the final value to be more effective, besides the AHP method also helps to find qualitative input values (text), namely by scoring the data, in this system the data whose input is in the form of text is the latest educational data [7]. The MOORA method is used to calculate the final score and ranking.

Analytical Hierarchy Process (AHP)
The AHP method is a multi-criteria decision-making model that can help humans think patterns where systemic processes can optimize logical factors, knowledge, emotions and feelings. The AHP method is a way to solve complex or unstructured problems in sub-problems, then arrange them into a hierarchical form [8] [9]. The steps for the AHP method

Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)
The MOORA method is a multi-objective system that optimizes two or more conflicting attributes simultaneously [12] [13].
The MOORA method has a good level of selectivity because it can determine conflicting criteria, namely benefits and costs [14] [15]. The method for solving the MOORA method can be described as follows: a. Determine the criterion value of each alternative b. Making a decision matrix (3) Description : i = 1,2,3,….,n is the serial number of criteria j = 1,2,3,…,m is an alternative sequence number X = Decision Matrix c. normalization matrix (4) Description : Xij = alternative response j on criterion i I = 1,2,3,…,n is the serial number of criteria J = 1,2,3,….,m is an alternative sequence number X*ij = alternative normalization matrix j on criterion i d. Calculating optimization value If the criteria for each alternative are not given weight. Then the formula (5) Description : I= 1,2,….,g criteria with status maximized J= g+1,g+2,…,n criteria with maximizedminimized status Wj= weight to j Yj = the value of the assessment has been normalized alternative I against all criteria

Result and Discussion
The data that will be tested on the system is the selection data for prospective lecturers at STMIK SZ NW Anjani. The data tested on the system can be seen in table 1.

Calculations Using the AHP Method
The calculation process using the AHP method includes the provision of pairwise comparisons where the comparison value is obtained from the head of the selection committee, the calculation of the weight of the criteria, the calculation of the sub-criteria and the scoring of the text data. a) Criteria Weight Calculation The calculation of the pairwise comparison matrix can be seen in table 2. After performing a pairwise comparison matrix and calculating the number of each column, then normalizing the matrix, and calculating the value of the criteria weights. The results of the normalization of the matrix can be seen in table 3 and the results of the calculation of the value of the criteria weights can be seen 4.   The same steps are carried out to obtain the normalization matrices of SK 2, SK 3 and SK 4. The normalization results of the X matrix are as follows.
Calculating In the same way, count to Y8, so that the results for the test criteria values for each alternative are obtained in table 8.

Conclusion
From the description of the entire description that has been raised previously to the discussion of the implementation of the AHP and MOORA methods for the selection of lecturer admissions, it can be concluded that from the results of the test it has been able to run correctly so that this system can be used by the chairman of the selection committee for acceptance of lecturers as a basis for making decisions in determining prospective lecturers. which will be accepted.