(Korespondensi) Automatic Assessment of Technology Readiness Level Using LLDA-Helmholtz for Ranking University

Rintyarna, Bagus Setya (2021) (Korespondensi) Automatic Assessment of Technology Readiness Level Using LLDA-Helmholtz for Ranking University. International Journal on Advanced Science, Engineering and Information Technology.

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Abstract

The assessment process of Technology Readiness Level using the questionnaire-based
tool for Indonesian university's academic papers is considered to be labor-intensive. This
paper introduces a new method of determining the TRL of an academic paper based on a
text mining technique. The content of the research paper represented by their abstract
published by university lecturers is justified to represent the technology maturity of
research. Abstracts of papers were collected from the nine most reputable universities in
Indonesia. By utilizing Labelled Latent Dirichlet Allocation, the abstracts were categorized
into 1 of 9 levels of TRL. To determine the prior label of LLDA, we built a corpus of
keywords representing each TRL level based on Bloom Taxonomy. Beforehand, Helmoltz
principle was utilized to select the text feature. Since Bloom Taxonomy has only six
levels, we split the keywords into 9 level. Afterward, the reputation score is calculated
using our formula. Lastly, the university ranking is generated according to the extracted
academic reputation score. To evaluate the proposed method, we compare our rank with
QS’s. We calculate the ranking gap and Pearson correlation to evaluate the result.
Helmholtz has successfully pruned 86% of features. The utilization of Helmholtz
significantly improves the Pearson correlation of our proposed method. In short, the new
insight of university ranking introduced in this work is promising. For all indicator
experiments, LLDA-Helmholtz performed better results indicated by 0.95 Pearson
correlation between two rankings, while for LLDA without Helmhotz, the correlation is
0.78.

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Item Type:	Peer Review
Keywords/Kata Kunci:	Technology readiness level; labeled latent Dirichlet allocation; Helmholtz principle; bloom taxonomy; Pearson correlation.
Subjects:	600 Technology and Applied Science > 620 Engineering
Divisions:	Faculty of Engineering > Department of Informatics Engineering (S1)
Depositing User:	Bagus Setya Rintyarna | bagus.setya@unmuhjember.ac.id
Date Deposited:	19 Jun 2023 01:45
Last Modified:	20 Oct 2023 06:35
URI:	http://repository.unmuhjember.ac.id/id/eprint/17322

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