(Similarity) Automatic Assessment of Technology Readiness Level Using LLDAHelmholtz for Ranking University

Rintyarna, Bagus Setya and Sarno, Riyanarto and Fitrianto, Eko Putro and Satyaji, Anugerah Yulindra (2022) (Similarity) Automatic Assessment of Technology Readiness Level Using LLDAHelmholtz for Ranking University. International Journal on Advanced Science, Engineering, and Information.

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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 Electrical Engineering (S1)
Depositing User:	Bagus Setya Rintyarna | bagus.setya@unmuhjember.ac.id
Date Deposited:	24 Dec 2022 02:58
Last Modified:	24 Dec 2022 02:58
URI:	http://repository.unmuhjember.ac.id/id/eprint/15719

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