Optimization of Data Envelopment Analysis Method with MOORA in the Selection of Research Proposals and PKM

The quality of the selection of research proposals and Community Service (PKM) of lecturers is an important element in supporting the implementation of the Tridarma of Higher Education. However, the selection process that is still carried out manually and tends to be subjective has the potential to cause bias in decision-making. This research aims to develop a decision support system that integrates the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) and Data Envelopment Analysis (DEA) methods to increase objectivity and efficiency in the selection process of research proposals and PKM lecturers at Rokania University. The MOORA method is used to determine a preference score based on the five main criteria for research proposals and six main criteria for PKM proposals, while the DEA method is utilized to evaluate the relative efficiency of each proposal based on the ratio between the MOORA score and the amount of funding submitted. The data used in this study was obtained from the results of the assessment of three reviewers on 14 research proposals and 11 PKM proposals. Each proposal is assessed based on criteria that have been determined by LPPM, then calculations are carried out using both methods. The results show that the combination of MOORA and DEA methods is able to produce more transparent and fair proposal rankings, as well as being able to identify the most efficient proposals in the use of the budget. This study concludes that the integration of MOORA and DEA methods in the lecturer proposal selection system is able to strengthen data-based research and PKM governance, as well as make a real contribution to more rational and measurable decision-making. This system also has the potential to be further developed to support the selection of external grants, recruitment of reviewers, or the allocation of research funds nationally. These findings can be replicated in other higher education institutions that face similar challenges.

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Publication Details

Journal
Jurnal KomtekInfo
Published
2025-09-30
DOI
https://doi.org/10.35134/komtekinfo.v12i3.652
Primary Topic
Data Mining and Machine Learning Applications
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article
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article

Optimization of Data Envelopment Analysis Method with MOORA in the Selection of Research Proposals and PKM

Jurnal KomtekInfo
Data Mining and Machine Learning Applications
article

Optimization of Data Envelopment Analysis Method with MOORA in the Selection of Research Proposals and PKM

article en

Abstract

The quality of the selection of research proposals and Community Service (PKM) of lecturers is an important element in supporting the implementation of the Tridarma of Higher Education. However, the selection process that is still carried out manually and tends to be subjective has the potential to cause bias in decision-making. This research aims to develop a decision support system that integrates the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) and Data Envelopment Analysis (DEA) methods to increase objectivity and efficiency in the selection process of research proposals and PKM lecturers at Rokania University. The MOORA method is used to determine a preference score based on the five main criteria for research proposals and six main criteria for PKM proposals, while the DEA method is utilized to evaluate the relative efficiency of each proposal based on the ratio between the MOORA score and the amount of funding submitted. The data used in this study was obtained from the results of the assessment of three reviewers on 14 research proposals and 11 PKM proposals. Each proposal is assessed based on criteria that have been determined by LPPM, then calculations are carried out using both methods. The results show that the combination of MOORA and DEA methods is able to produce more transparent and fair proposal rankings, as well as being able to identify the most efficient proposals in the use of the budget. This study concludes that the integration of MOORA and DEA methods in the lecturer proposal selection system is able to strengthen data-based research and PKM governance, as well as make a real contribution to more rational and measurable decision-making. This system also has the potential to be further developed to support the selection of external grants, recruitment of reviewers, or the allocation of research funds nationally. These findings can be replicated in other higher education institutions that face similar challenges.

Jurnal KomtekInfo
Universitas Putra Indonesia "YPTK" (ID)
Openalex Percentile: Top 34%
Data Mining and Machine Learning Applications
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Optimization of Data Envelopment Analysis Method with MOORA in the Selection of Research Proposals and PKM · Jurnal KomtekInfo (2025) | TGRS Research Map | TGRS