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Menampilkan 1–2 dari 2 artikel
FTFPOS-IDF: A Fuzzy Rule-Based Thematic Term Weighting Scheme for Bloom's Taxonomy Question Classification
Sucipto, Sucipto
; Prasetya, Didik Dwi
; Widiyaningtyas, Triyanna
The increasing adoption of Artificial Intelligence (AI) in education has created a growing demand for automated and reliable assessment systems. Existing Bloom’s Taxonomy (BT) question classification approaches commonly rely on TF-IDF-based weighting schemes, which assign static term weights and often fail to capture the varying thematic importance of terms across cognitive levels. To address this limitation, this study proposes a novel Fuzzy Thematic Feature and Part-of-Speech Inverse Document...
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Ontology-Based Recommender Systems for E-Learning and Multimedia: A Systematic Literature Review Across Domains
Riska, Suastika Yulia
; Patmanthara, Syaad
; Widiyaningtyas, Triyanna
Indonesian Journal of Instructional Media and Model
Vol 7
, No 2
(2025)
The rapid expansion of digital content across various sectors has led to an overwhelming influx of data, highlighting the need for advanced recommendation systems. Traditional methods such as Collaborative Filtering (CF) and Content-Based Filtering (CBF) face limitations like data sparsity and the Cold Start problem, which affect the accuracy of recommendations. This study explores the use of ontologies in enhancing recommendation systems, aiming to overcome these challenges by providing a seman...
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