Accurate and Objective Lecturer Appraisal System: Implementation of the LOPCOW Method

This research proposes the use of the Logarithmic Precursor Chain-Driven Objective Weighting (LOPCOW) method to evaluate the best lecturers in universities. The LOPCOW method ensures that the assessment covers all aspects of lecturer quality and performance, including education, research, community services, discipline, commitment, cooperation skills, and innovation. The evaluation of lecturers using the scores and ratings provided showed that CDE lecturers were the best, with the highest score of 0.715. CDE lecturers showed high consistency in all aspects assessed, especially in education, research, and community service. This was followed by MNO lecturers (0.676), STU lecturers (0.668), XYZ lecturers (0.637), and AFI lecturers (0.627). In conclusion, highly ranked lecturers showed strong dedication to the Tridharma of higher education, with consistent performance and a positive impact on the academic community and the general public. Future research should focus on developing strategies to improve lecturers' teaching quality by applying new educational technologies and evaluating their impact on student learning.

Authors

Institutions

Publication Details

Journal
Komputasi Jurnal Ilmiah Ilmu Komputer dan Matematika
Published
2024-08-12
DOI
https://doi.org/10.33751/komputasi.v21i2.10188
Citations
2
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accurate and Objective Lecturer Appraisal System: Implementation of the LOPCOW Method

Sumanto Sumanto, Lita Sari Marita, Adi Supriyatna, Ahmad Yani et al.
2 citations
Komputasi Jurnal Ilmiah Ilmu Komputer dan Matematika
Management and Optimization Techniques
1.11
article

Accurate and Objective Lecturer Appraisal System: Implementation of the LOPCOW Method

Sumanto Sumanto, Lita Sari Marita, Adi Supriyatna, Ahmad Yani, Lise Pujiastuti, Ummu Radiyah
article en
2 citations

Abstract

This research proposes the use of the Logarithmic Precursor Chain-Driven Objective Weighting (LOPCOW) method to evaluate the best lecturers in universities. The LOPCOW method ensures that the assessment covers all aspects of lecturer quality and performance, including education, research, community services, discipline, commitment, cooperation skills, and innovation. The evaluation of lecturers using the scores and ratings provided showed that CDE lecturers were the best, with the highest score of 0.715. CDE lecturers showed high consistency in all aspects assessed, especially in education, research, and community service. This was followed by MNO lecturers (0.676), STU lecturers (0.668), XYZ lecturers (0.637), and AFI lecturers (0.627). In conclusion, highly ranked lecturers showed strong dedication to the Tridharma of higher education, with consistent performance and a positive impact on the academic community and the general public. Future research should focus on developing strategies to improve lecturers' teaching quality by applying new educational technologies and evaluating their impact on student learning.

Komputasi Jurnal Ilmiah Ilmu Komputer dan MatematikaVol. 21(2)
Universitas Informatika dan Bisnis Indonesia (ID), Universitas Katolik Widya Mandira (ID)
Openalex Percentile: Top 15%
Management and Optimization Techniques
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.