Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Vol 10 No 3: Agustus 2021

Regresi Linear untuk Mengurangi Bias Sistem Penilaian Uraian Singkat

Silmi Fauziati (Universitas Gadjah Mada)
Adhistya Erna Permanasari (Universitas Gadjah Mada)
Indriana Hidayah (Universitas Gadjah Mada)
Eko Wahyu Nugroho (Universitas Gadjah Mada)
Bobby Rian Dewangga (Universitas Gadjah Mada)



Article Info

Publish Date
26 Aug 2021

Abstract

This study is aimed to improve the performance of a short essay scoring system. The improvement is executed by integrating a simple linear regression to the output of a combined cosine similarity method (with weighted term frequency using Term Frequency –Inverse Document Frequency (TF-IDF) method) and term-matching mechanism.The linear regression is conducted by taking the short essay score (resulting from the combined cosine similarity and termmatching) as a regressor variable. In order to demonstrate the effectivenessof the proposedscoring system, the performance of the scoring system is measured relative to manual scoring by a lecturer.The results show that prior to linear regression, the scoring system tends to give higher score(biased score) compared to the manual score,which is problematic. The following scoring system with linear regression tackles this problem as the scoring bias is significantly reduced, that is, no tendency to givehigher or less scorecompared to the manual score.That the scoring bias is significantly reduced using a simple approach, linear regression,is expected to contribute in the acceleration of implementingautomatedessay scoring system on online learning technologiessuch as e-learning.

Copyrights © 2021






Journal Info

Abbrev

JNTETI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Description

Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, ...