Open AccessFunctional test of the online Recognition of Work Experience and Learning Outcome System using black box testing
Author(s) -
Zamtinah,
Edy Supriyadi,
Soeharto
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1446/1/012060
Subject(s) - cronbach's alpha , test (biology) , black box , reliability (semiconductor) , outcome (game theory) , computer science , function (biology) , white box testing , multimedia , artificial intelligence , software , psychometrics , statistics , mathematics , paleontology , software construction , power (physics) , physics , mathematical economics , quantum mechanics , evolutionary biology , software system , biology , programming language
This paper describes: (1) the development of the online Work Experience and Learning Outcome (ReWELO) website, (2) the feasibility testing of the online ReWELO system, and (3) the functional testing of the ReWELO system using black-box testing. The method used to develop the ReWELO website was the design method. The instruments used for testing were questionnaires and observation sheets. The instrument’s validity was tested through expert judgment and the instrument’s reliability was examined with Cronbach’s Alpha. The feasibility of the website was analyzed by information technology experts and users (assessors and candidates). The function of the ReWELO Website was tested by using black-box testing. The collected data were then analyzed descriptively. The test results revealed that ReWELO’s website was rated “good” by information technology experts, assessors, and candidates. The average score of evaluation from information technology experts, practitioner, assessors, and candidates were 3.3; 3.5; 3.4; and 3.2 respectively. All features of the online ReWELO system were able to function properly as planned.