Decision Support System on Independent Curriculum Learning Models with Artificial Intelligence at Islamic Universities

The design of curricula in Islamic universities frequently encounters difficulties in addressing the evolving needs of students, industry demands and the distinctive integration of Islamic values. Conventional methodologies are inadequate in their capacity to adapt to the evolving needs of the modern educational landscape. Furthermore, the integration of artificial intelligence (AI) in this domain remains underdeveloped, with many instances overlooking the crucial role of religious principles and institutional characteristics. This study addresses this gap by developing a Decision Support System (DSS) using Mamdani type 1 fuzzy logic, with the objective of assisting in determining an independent curriculum learning model tailored to Islamic higher education. The system incorporates a number of input variables, including student needs, industry requirements, institutional characteristics and data analysis. The output variables include an evaluation of the suitability of the learning model and a recommendation as to the most appropriate model. To illustrate, in situations where student needs are high, industry demands are moderate, institutional characteristics are high, and data analysis is moderate, the recommended model places an emphasis on balancing theoretical knowledge with practical application, while also aligning with Islamic values. The validation of this AI-based model, utilizing 2023 historical data from five Islamic universities in West Sumatra, yielded an average Mean Absolute Error (MAE) of 0.64, thereby demonstrating good predictive accuracy. The integration of AI in this system facilitates data-driven decision-making, thereby enhancing the relevance and adaptability of the curriculum. It has the potential to improve the quality of education, support balanced student learning outcomes, and ensure alignment with Islamic principles, making it a transformative tool for curriculum development in Islamic higher education.

Authors

Institutions

Publication Details

Journal
ILKOM Jurnal Ilmiah
Published
2025-04-20
DOI
https://doi.org/10.33096/ilkom.v17i1.2082.74-85
Primary Topic
Blockchain Technology in Education and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Decision Support System on Independent Curriculum Learning Models with Artificial Intelligence at Islamic Universities

Liza Efriyanti, Ihwana As'ad
ILKOM Jurnal Ilmiah
Blockchain Technology in Education and Learning
article

Decision Support System on Independent Curriculum Learning Models with Artificial Intelligence at Islamic Universities

Liza Efriyanti, Ihwana As'ad
article en

Abstract

The design of curricula in Islamic universities frequently encounters difficulties in addressing the evolving needs of students, industry demands and the distinctive integration of Islamic values. Conventional methodologies are inadequate in their capacity to adapt to the evolving needs of the modern educational landscape. Furthermore, the integration of artificial intelligence (AI) in this domain remains underdeveloped, with many instances overlooking the crucial role of religious principles and institutional characteristics. This study addresses this gap by developing a Decision Support System (DSS) using Mamdani type 1 fuzzy logic, with the objective of assisting in determining an independent curriculum learning model tailored to Islamic higher education. The system incorporates a number of input variables, including student needs, industry requirements, institutional characteristics and data analysis. The output variables include an evaluation of the suitability of the learning model and a recommendation as to the most appropriate model. To illustrate, in situations where student needs are high, industry demands are moderate, institutional characteristics are high, and data analysis is moderate, the recommended model places an emphasis on balancing theoretical knowledge with practical application, while also aligning with Islamic values. The validation of this AI-based model, utilizing 2023 historical data from five Islamic universities in West Sumatra, yielded an average Mean Absolute Error (MAE) of 0.64, thereby demonstrating good predictive accuracy. The integration of AI in this system facilitates data-driven decision-making, thereby enhancing the relevance and adaptability of the curriculum. It has the potential to improve the quality of education, support balanced student learning outcomes, and ensure alignment with Islamic principles, making it a transformative tool for curriculum development in Islamic higher education.

ILKOM Jurnal IlmiahVol. 17(1)
Universitas Muslim Indonesia (ID), Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi (ID)
Openalex Percentile: Top 76%
Blockchain Technology in Education and Learning
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.

Decision Support System on Independent Curriculum Learning Models with Artificial Intelligence at Islamic Universities — Liza Efriyanti, Ihwana As'ad · ILKOM Jurnal Ilmiah (2025) | TGRS Research Map | TGRS