Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Abstract

Profile Matching Performance for Advisor Recommendation Based On Google Scholar Index

Author(s): Nurul Aini, Andi Irmayana, Asmah Akhriana, Irmawati Irmawati, Ahyuna Ahyuna, Sitti Aisa

 Determination of thesis advisor and examiner is the authority of the Head of Department in which the process involves a conventional way following the personal experience of an advisor in his\her corresponding field that is relevant to a research. In Dipanegara school of informatics management and computer (STMIK), Makassar, it is often resulted in non-optimal decisions that students did not get thesis advisors that match their field of expertise. This study applied the Profile Matching method, a decision-making method with an ideal variable level that must be met by the subject under study. The matching was based on the history of lecturers’ publication obtained from Google Scholar Index by searching through the scholar ID of advisors. The stages were the formulation of Gap score, Core Factor, Secondary Factor, and total aspect value. The role of Profile Matching supports the thesis advisor recommendation system operated by the Head of Department to the thesis advisor, examiner, and students based on the resulted research topic. The decision support system had been evaluated with questionnaires distributed to 30 lecturer and staff departement as the respondents. The evaluation process used the Technology Acceptance Model and Likert scale. It was found that CronBach scores for Perceived Usefulness was 0.71 and Perceived Ease of Use was 0.60 and then they were considered as reliable.

Get the App