Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Bulletin of Social Informatics Theory and Application

Internship recommendation system using simple additive weighting Santoso, Priyo Aji; Wibawa, Aji Prasetya; Pujianto, Utomo
Bulletin of Social Informatics Theory and Application Vol. 2 No. 1 (2018)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v2i1.102

Abstract

Internship is an activity that is compulsory for students of Vocational High School. Great selection of internships and the lack of information about the industry, is the common barriers of apprentice implementation. So find apprenticeship places that fit the needs of students to increase the intensity of the work and the motivation of students is not easy. Apprenticeship recommendation system using a simple additive weighting (SAW) can be used as a solution to assist students in determining the place of internship according to the needs of student. Method SAW can provide recommendations based on the weight of the priority criteria for students and can provide the level of accuracy of calculation of 100%. Evaluation on the behavior of users of the system are also carried out, as many of the implementation of the system failed is caused not due to technical factors but more on users. The results of the evaluation of the Technology Acceptance Model (TAM) approach, the average of user already feel usability and ease of use. While the influence of TAM each variable can give significant effects.
Technology acceptance model of student ability and tendency classification system Dwi Jaelani, Mardian; Prasetya Wibawa, Aji; Pujianto, Utomo
Bulletin of Social Informatics Theory and Application Vol. 2 No. 2 (2018)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v2i2.113

Abstract

Skill and competency test (SCT) is part of the Government's intervention in ensuring the quality of education in the Vocational High School (SMK) education unit. The teacher prepares vocational students to face SCT, especially vocational students of class XII. However, the obstacles often encountered by teachers in recommending students to choose competency that are in accordance with students' abilities. Ability Classification System and Student Ability Trends by applying the Learning Vector Quantization (LVQ) algorithm, it can be used as a solution to assist teachers in classifying student abilities and the tendency of students' abilities to be used to select skills competencies during SCT. This study aims to examine the use of the technology acceptance model (TAM) implementation of the classification system. As a result, the average user has felt the usefulness and ease of use of the system. Each TAM variable has a significant effect.