Answer categorization method using K-means for Indonesian language automatic short answer grading system based on latent semantic analysis

Anak Agung Putri Ratna, Naiza Astri Wulandari, Aaliyah Kaltsum, Ihsan Ibrahim, Prima Dewi Purnamasari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The Automatic Short Answer Grading (Simple-O) has been created for grading short answer with Bahasa Indonesia using K-Means and Latent Semantic Analysis (LSA) method. In this experiment, the text document feature will be extracted using Term Frequency-Inverse Document Frequency (TF-IDF) and then classified using K-Means. From the experiment, 149 documents are expected to be clustered into five classes. The result of the clustering using K-Means is 100% matched with clustering using human rater. The result of grading with LSA is 74%.

Original languageEnglish
Title of host publication2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728118987
DOIs
Publication statusPublished - Jul 2019
Event16th International Conference on Quality in Research, QIR 2019 - Padang, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

Name2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering

Conference

Conference16th International Conference on Quality in Research, QIR 2019
Country/TerritoryIndonesia
CityPadang
Period22/07/1924/07/19

Keywords

  • Answer categorization
  • Essay grading
  • K-means
  • Latent semantic analysis
  • Tf-idf

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