Technology Acceptance Model on Internship Placement Recommendation System Based on Naïve Bayes

Abstract

The application of internship has several obstacles that can lead to the possibility of failure to achieve the objectives of the internship itself. Some barriers to internship are inaccuracies in the placement, imbalance between students’ abilities and industrial needs. In this study, an Internship Information System (Siprakerin) was developed to overcome the problem of technical internalization that arises by predicting the accuracy of industry selection using the Naive Bayes classification method. System accuracy that has been obtained is 80%. This study will examine the behavior of Siprakerin users based on the factors that influence them with the Technology Acceptance Model (TAM) approach. Based on the results of the analysis it is known that there is an influence of Perceived Ease of Use on Perceived Usefulness of 89%, while the influence of Perceived Ease of Use and Perceived Usefulness on Attitude Toward Using is 88.8%. It is also known that the effect of Perceived Usefulness and Attitude Toward Using on Behavioral Intention to Use is 91.7%. And there was a Behavioral Intention to Use effect on Actual System Usage of 92.6%.