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php/bids/index Decision Support System for Selecting the Best Head of Study Program Applying the Multi-Objective Optimization Method on the Basis of Simple Ratio Analysis (MOOSRA) Juanda Hakim Lubis1.
Sanwani2.
Akhyar Lubis3.
Mesran4,*.
Julaysa5.
Novita Sari Hutapea5 1 Information Technology.
Universitas Pembinaan Masyarakat Indonesia.
Medan.
Indonesia 2 Information Technology.
Universitas Bina Sarana Informatika.
Jakarta.
Indonesia 3 Faculty of Science and Technology.
Computer Engineering.
Universitas Pembangunan Panca Budi.
Medan.
Indonesia 4 Management.
Sekolah Tinggi Ilmu Manajemen Sukma.
Medan.
Indonesia 5 Faculty of Computer Science and Information Technology.
Informatics.
Budi Darma University.
Medan.
Indonesia Email: 1juandahakim@gmail.
com, 2sanwani.
swq@nusamandiri.
id, 3akhyarlbs@pancabudi.
4,*mesran.
mkom@gmail.
com, 5julaysaneca@gmail.
com, 6novitasarihutapea06@gmail.
AbstractOeThe Head of Study Program plays an important role as the highest leader in the structure of a study program.
The Head of Study Program is responsible for the smooth running of academic activities in the study program he leads.
As a key element in higher education, the Head of Study Program must lead the managerial function by planning, implementing, and controlling the academic process and managing other supporting activities.
The head of the study program who shows high performance, dedication, and integrity deserves an award as the best head of the study program.
This assessment aims to ensure that the Head of Study Program is able to carry out his duties properly in accordance with the rules and demands, and advance the study program in accordance with its vision and mission.
Therefore, a decision support system is needed as a solution to overcome this problem, by utilizing the MOOSRA MOOSRA begins by formulating a decision matrix consisting of alternatives, criteria or attributes, individual weights or significance coefficients of each criterion, and performance measurements of related alternatives.
Normalization is then carried out to change the attribute values into the range 0Ae1.
The assessment results show that the Head of Study Program with the highest ranking is alternative A7, with a value of 0.
Keywords: Decision Support System.
Selection.
Best Head of Study Program.
MOOSRA Method
INTRODUCTION
The Head of Study Program is the highest leader in the structure of a study program.
The Head of Study Program is tasked with ensuring the smooth running of all academic activities in the study program he leads.
As a key and strategic element in higher education, the Head of Study Program must lead and manage various managerial functions such as designing plans, running the academic process, supervising the implementation of the academic process, and holding various other supporting activities.
In addition to managerial responsibilities, the Head of Study Program is also responsible for the activity or inactivity of the study program he leads .
As a key and strategic element in higher education, the Head of Study Program has the task of leading and managing various important aspects.
These tasks include the preparation of strategic and operational plans for study programs, implementation of learning processes and academic activities, control and evaluation of the quality of academic processes, and coordination of other supporting activities such as research, community service, and human resource The Head of Study Program also plays a role in ensuring that study programs remain relevant to the development of science and industry needs, as well as maintaining accreditation and quality of education according to established standards.
The head of the study program has the responsibility to lead and carry out managerial functions, including planning, implementing, and controlling academic activities and managing the administration of supporting activities.
Therefore, a head of a study program who demonstrates extraordinary performance, dedication, and integrity deserves to be awarded as the best head of the study program.
As an important component in university management, the head of the study program plays a role in realizing the vision, mission, and objectives of the study program that are in line with the vision, mission, and objectives of the institution as a whole.
The reward system is an important element and motivator that encourages the best performance and creates a conducive academic atmosphere, which ultimately accelerates the development of the scientific community today and in the future according to expectations .
The award system is expected to motivate the head of study program to be more accomplished and productive, so that the goals of developing the higher education system and national development in general can be achieved optimally.
This award is given routinely by the Ministry of Research.
Technology and Higher Education.
The assessment of the Head of Study Program covers various aspects, such as leadership, ability to provide protection, communication, activeness, research, and dedication.
This assessment aims to ensure that the Head of Study Program can carry out his/her duties properly in accordance with existing rules and demands, and advance the study program in accordance with its vision and mission.
Therefore, a decision support system is needed as a solution to this problem .
Decision Support System (DSS) is a computerized system designed to solve problems and produce data used in decision The main components in DSS include Data Management.
Model Management.
Communication, and Knowledge Management.
Some methods used in DSS include Complex Proportional Assessment (COPRAS).
Step-wise Weight Assessment Ratio Analysis Method (SWARA).
Additive Ratio Assessment (ARAS).
Rank Order Centroid (ROC).
Preference Selection Index (PSI).
Multi-Attributive Border Approximation area Comparison (MABAC).
Multi Attribute Copyright A 2025 Authors.
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php/bids/index Utility Theory (MAUT).
Preference Ranking Organization Method For Enrichment Evaluation (PROMETHEE I-II-.
Elimination And Choice Expressing Reality (ELECTRE I-II-.
, and The Extended Promethee (EXPROM I&II) .
In this study, the author solves the problem using the MOOSRA method ( Multi-Objective Optimization on the Basis of Simple Ratio Analysis ).
The MOOSRA methodology begins by formulating a decision matrix that typically includes four main parameters: alternatives, criteria or attributes, individual weights or significance coefficients of each criterion, and performance measures of the alternatives related to those criteria.
In the multiattribute phase, normalization is required as a process to transform attribute values into the range 0Ae1 .
There are several related studies that are used as reference materials by the author in making this research, such as research in 2022 conducted by Zulfi Azhar et al.
, discussing the selection of the best E-Commerce using the Moosra method resulting in the best preference value of 3.
26323 in alternative A1 .
In 2023 research conducted by Elsa Fitria et al.
discussing the selection of E-commerce in purchasing fashion products applying the Moosra method resulting in the best preference value of 2.
11960 in alternative A1 .
, research conducted by Deby Lorensyah Rambe et al.
, discussing the Application of the Moosra Method and ROC Weighting in assessing the Performance of Chemistry Laboratory Assistants resulting in the best preference value of 207.
92651 in alternative LK07 .
Research conducted by Rima Tamara Aldisa et al.
, discussing the acceptance of permanent lecturers using the Moora and Moosra methods resulting in the best preference value of 0.
4742 using the Moora method and 28.
1366 using the Moosra method in alternative A1 .
Research conducted by Elfrianti Fransiska Hutahaean et al.
, discussing the application of the Moosra method in recommendations for selecting candidates for the voting committee (PPS) produced the best value of 4.
812 for alternative A1 .
Based on this research as a solution to solve the problems that the author studied with the multi-objective optimization method on the basis of simple ratio analysis (MOOSRA) as the best alternative value in selecting the best study program head.
The purpose of this research is to make it easier for higher education institutions to choose the best study program head more accurately, it is hoped that this research will be a reference for readers and can help readers solve the problem of a Decision Support System with the same method in this research.
RESEARCH METHODOLOGY
1 Decision Support System Decision Support System (DSS) is a computer-based information system designed to assist in decision making in various contexts and fields.
This DSS is developed to support complex and unstructured decision making by collecting, processing, and analyzing relevant data.
Decision support systems are specifically designed to assist management in making decisions related to semi-structured problems.
This DSS is equipped with facilities to generate various alternatives that are used interactively by users .
2 Head of Study Program As an academic official who has the main responsibility in organizing education, research, and community service at the study program level, the Head of Study Program leads, manages, and develops study programs to achieve the vision, mission, and academic goals set by the educational institution.
The role of the Head of Study Program is very important in ensuring the smooth operation of study programs, meeting the established academic standards, and supporting the development of students and lecturers effectively .
3 Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) is a method decision making used to solve multi-objective optimization problems.
MOOSRA is useful in complex decision situations where multiple conflicting criteria need to be considered.
This method integrates simple ratio analysis principles to evaluate and rank alternatives based on their performance across multiple objectives.
In carrying out a calculation using the Moosra method, there are four stages of calculation, namely as follows .
Forming a decision matrix ycU11 ycU = [ 21 ycUyco1 ycU12 ycU22 ycUyco2 ycU1ycu ycU2ycu ycUycoycu Determining the normalization matrix ycU O ycnyc = ycUycnyc yco ocycn=yc ycUycnyc 2 Determining Preference Values If the weight interest is the same as the formula:
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php/bids/index O Ocyci yc=1 ycU ycnyc ycUycn = Ocycu yc=yci 1 ycU ycnyc If the weight interests differ from the formula :
Ocyci yc=1 ycycycu ycnyc ycUycn = Ocycu yc=yci 1 ycyc ycu ycnyc 4 Research Stages In this research, the author carried out the following stages:
In the problem identification stage The author conducted an in-depth analysis of the problems related to the selection of the best Head of Study Program.
This study also considers the most appropriate method to solve the problem, according to the solution needed in the context of this study.
Literature Study stage involves searching for and analyzing relevant data and information related to the problems discussed, including from journals, books and e-books that are in line with the focus of this research.
Application of MOOSRA Method At this stage, the MOOSRA method is implemented to perform calculations using data samples relevant to this Research Report At this stage, the results of the report are presented covering all stages that have been carried out by the author.
This report includes solutions to the problems identified, the results of using the selected methods, and the conclusions obtained from all of this research.
The research stages above can be described in Figure 1 below:
Start Problem Identification Literature Review Application of the MOOSRA Method Implementation of Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA):
Formulate a decision matrix Normalize the matrix Determine the preference values or final scores Research Report Preparation End Figure 1.
Research Stages RESULTS AND DISCUSSION The Head of Study Program is the highest position in the study program structure that is responsible for the managerial and academic aspects of the study program.
The Head of Study Program needs to be actively involved in the development and progress of the study program to achieve goals in accordance with the vision and mission set by the university.
The Head of Study Program is also expected to be able to communicate effectively with structural members of the study program and students under his management, to create a harmonious academic atmosphere.
Therefore, high integrity is one of the important prerequisites in carrying out leadership in a study program.
Based on this, it is important to evaluate the performance of the Head of Study Program during one leadership This evaluation is carried out by the highest leadership elements in the university and must be carried out objectively and optimally.
The goal is to ensure that the evaluation produces good results and can be accounted for to related parties, and is carried out without harming any party.
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php/bids/index Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) is used to find solutions in selecting the Best of Head of Study Program by utilizing several alternative data samples that are considered to meet the established criteria.
The process of describing and applying this data can be seen clearly as described below:
1 Alternative Determination Alternatives are an important requirement in the process of selecting the best Head of Study Program, where each alternative must meet the established criteria.
The following is alternative data for the Head of Study Program contained in Table 1 below:
Table 1.
Alternative Data for Head of Study Program Alternative Lecturer Name Imam Saputra.
Kom.
Kom Guidio Leonardo Ginting.
Kom.
Kom Taronisokhi Zebua.
Kom.
Kom Fince Tinus Waruw.
Kom.
Kom Kurnia Ulfa.
SS.
Hum Efori Bu'ulolo.
Kom.
Kom Putri Ramadhani.
SS.
Hum Siti Nurhabibah Hutagalung.
Msi 2 Determination of Criteria In the process of selecting the best Head of Study Program, there are several criteria that have been met, as listed in Table 2 and Table 3 below:
Table 2.
Criteria Data Criteria Information Leadership Protecting Communication Activity Study Devotion Type Benefit Benefits Benefits Benefits Benefits Cost Weight Table 3.
Alternative Data and Criteria Data Alternative (C 1 ) (C 2 ) (C 3 ) (C 4 ) (C 5 ) ( C .
Very good Good Good Good Good Good Enough Good Good Good Good Very good Good Enough Good Enough Good Bad Very good Enough Very good Enough Good Good Good Good Enough Very good Enough Enough Enough Enough Good Enough Enough Good Very good Good Good Good Enough Very good Bad Enough Good Enough Enough Good To complete a method, data that is not in the form of a numeric value needs to be converted into a numeric value.
This is necessary so that the calculation process can be carried out correctly.
The following are the parameters that have been formed in Table 4 below:
Table 4.
Value Description Criteria Information Very good Good Pretty good Bad Very bad Type After adjusting the values, the following are the numerical values of each alternative in Table 5 as follows:
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php/bids/index Table 5.
Alternative Values Against Criteria Alternative Imam Saputra.
Kom Guidio Leonardo Ginting.
Kom Taronisokhi Zebua.
Kom Professor Tinus Waruw.
Kom Kurnia Ulfa.
SS.
Hum Efori Bu'ulolo.
Kom.
Kom Putri Ramadhani.
SS.
Hum Siti Nurhabibah Hutagalung.
Msi
(C 1 )
(C 2 )
(C 3 )
(C 4 )
(C 5 )
(C 6 )
3 Application of the MOOSRA Method The following are the steps for calculating data for suitability assessment using the Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) method:
Creating a normalization matrix ycUycnyc = .
,6 1 1 0,8 0,8 0,8 0,6 0,8 1
0,6 1 0,8 0,8
0,8 0,6 0,8 0,8
0,6 0,6 0,6 0,8
0,8 0,8 1 0,6
0,4 0,6 0,6 1
0,6 0,6 0,8 0,.
Matrix normalization Then form a normalized matrix using the equation For Criteria C1 ya1 = Oo12 0,82 0,82 0,82 0,62 0,82 0,62 0,62 = 2,154065 ycU11 = 2,154065 = 0,464238 ycU21 = 2,154065 = 0,371390 ycU31 = 2,154065 = 0.
ycU41 = 2,154065 = 0,371390 ycU51 = 2,154065 = 0,278543 ycU61 = 2,154065 = 0,371390 ycU71 = 2,154065 = 0,278543 ycU81 = 2,154065 = 0,278543 For Criteria C2 ya2 = Oo0,82 0,82 0,62 0,82 0,62 0,82 0,82 0,62 = 2,068816 ycU12 = 2,068816 = 0,386694 ycU22 = 2,068816 = 0,386694 ycU32 = 2,068816 = 0.
ycU42 = 2,068816 = 0,386694 ycU52 = 2,068816 = 0,290020 Copyright A 2025 Authors.
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php/bids/index ycU62 = 2,068816 = 0,386694 ycU72 = 2,068816 = 0,386694 ycU82 = 2,068816 = 0,290020 For Criteria C3 ya3 = Oo12 0,82 0,62 0,82 0,62 0,82 0,42 0,62 = 2,039607 ycU13 = 2,039607 = 0,490290 ycU23 = 2,039607 = 0,392232 ycU33 = 2,039607 = 0.
ycU43 = 2,039607 = 0,392232 ycU53 = 2,039607 = 0,294174 ycU63 = 2,039607 = 0,392232 ycU73 = 2,039607 = 0,196116 ycU83 = 2,039607 = 0,294174 For Criteria C4 ya4 = Oo12 0,62 12 0,62 0,62 0,82 0,62 0,62 = 2,107130 ycU14 = 2,107130 = 0,474579 ycU24 = 2,107130 = 0,287747 ycU34 = 2,107130 = 0.
ycU44 = 2,107130 = 0,287747 ycU54 = 2,107130 = 0,287747 ycU64 = 2,107130 = 0,379663 ycU74 = 2,107130 = 0,287747 ycU84 = 2,107130 = 0,287747 For Criteria C5 ya5 = Oo0,82 0,82 0,82 0,82 0,62 12 0,62 0,82 = 2,218107 ycU15 = 2,218107 = 0,360667 ycU25 = 2,218107 = 0,360667 ycU35 = 2,218107 = 0.
ycU45 = 2,218107 = 0,360667 ycU55 = 2,218107 = 0,270500 ycU65 = 2,218107 = 0,450834 Copyright A 2025 Authors.
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php/bids/index ycU75 = 2,218107 = 0,270500 ycU85 = 2,218107 = 0,360667 For Criteria C6 ya6 = Oo0,82 12 0,82 0,82 0,82 0,62 12 0,42 = 2,253885 ycU16 = 2,253885 = 0,354942 ycU26 = 2,253885 = 0,443678 ycU36 = 2,253885 = 0.
ycU46 = 2,253885 = 0,354942 ycU56 = 2,253885 = 0,354942 ycU66 = 2,253885 = 0,266207 ycU76 = 2,253885 = 0,443678 ycU86 = 2,253885 = 0,177471 After performing normalization, the results obtained for the normalized matrix are as follows:
Table 6.
Matrix Normalization Data Alternative Imam Saputra.
Kom Guidio Leonardo Ginting.
Kom Taronisokhi Zebua.
Kom Professor Tinus Waruwu.
Kom Kurnia Ulfa.
SS.
Hum Efori Bu'ulolo.
Kom.
Kom Putri Ramadhani.
SS.
Hum Siti Nurhabibah Hutagalung.
Msi
(C 1 )
(C 2 )
(C 3 )
(C 4 )
(C 5 )
(C 6 )
After normalizing the values, the next step is to determine the ranking by multiplying the weights of each alternative Then, the results are divided between benefits and costs, where the profit value that has been added after multiplying the weights is divided by the cost value after multiplying the weights.
ycU1 = ycU2 = ycU3 = ycU4 = ycU5 = ycU6 = ycU7 = ycU8 = .
,464238 ycu 0,.
,386694 ycu 0,.
,490290 ycu 0.
,474579ycu0,.
,360667ycu0,.
,490290 0,.
,371390 ycu 0,.
,386694 ycu 0,.
,392232ycu0.
,287747ycu0,.
,360667ycu0,.
,392232 0,.
,371390 ycu 0,.
,290020 ycu 0,.
,294174ycu0.
,474579ycu0,.
,360667ycu0,.
,294174 0,.
,371390 ycu 0,.
,386694 ycu 0,.
,392232ycu0.
,287747ycu0,.
,360667ycu0,.
,392232 0,.
,278543 ycu 0,.
,290020 ycu 0,.
,294174ycu0.
,287747ycu0,.
,270500ycu0,.
,294174 0,.
,371390 ycu 0,.
,386694 ycu 0,.
,392232ycu0.
,379663ycu0,.
,450834ycu0,.
,392232 0,.
,278543 ycu 0,.
,386694 ycu 0,.
,196116ycu0.
,287747ycu0,.
,360667ycu0,.
,196116 0,.
,371390 ycu 0,.
,290020 ycu 0,.
,294174ycu0.
,474579ycu0,.
,360667ycu0,.
,294174 0,.
0,398709 = 0,590290 = 0,675445 0,327861 0,492232 = 0,666070 0,316939 = 0,394174 = 0,804058 0,327861 = 0,492232 = 0,666070
0,256664
= 0,394174 = 0,651143
0,327861
= 0,492232 = 0,666070
0,265426
= 0,296116 = 0,896358
0,316939
= 0,394174 = 0,804058
Y Value Ranking The final step in the resolution process is to perform ranking to determine the best alternative using the MOOSRA The following is Table 7 which shows the ranking results:
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Ranking Results Alternative Lecturer Name Imam Saputra.
Kom Guidio Leonardo Ginting.
Kom Taronisokhi Zebua.
Kom Professor Tinus Waruw.
Kom Kurnia Ulfa.
SS.
Hum Efori Bu'ulolo.
Kom.
Kom Putri Ramadhani.
SS.
Hum Siti Nurhabibah Hutagalung.
Msi Results Ranking From the application of the MOOSRA method, the selection of the best study program head was obtained with the highest alternative, namely alternative A7 in the name of Putri Ramadhani.
SS.
Hum with a value of 0.
CONCLUSION
Based on the results of the research and discussion that have been presented, it can be concluded that the assessment process in selecting the best Head of Study Program using the Decision Support System produces an objective, optimal, and accountable evaluation.
The application of the MOOSRA method in the Decision Support System to evaluate the performance of the best Head of Study Program is able to provide an in-depth analysis of each Head of Study Program.
The assessment results show that the Head of Study Program with the highest ranking is alternative A1, with a value of REFERENCES