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Journal : Journal of Information Technology and Its Utilization

USABILITY AND USEFULNESS FOR ONLINE SINGLE SUBMISSION SYSTEM IN INVESTMENT AND ONE-STOP INTEGRATED SERVICE OFFICE, SAMARINDA CITY Ummul Hairah; Edy Budiman
Journal of Information Technology and Its Utilization Vol 4, No 1 (2021)
Publisher : Sekolah Tinggi Multi Media (STMM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.4.1.3892

Abstract

The challenge of implementing the online service public system from the user side of the system is the acceptance and use of technology. User characteristics for accepting or rejecting the use of the system for various reasons (digital literacy) for the adoption of new technologies such as the Online Single Submission (OSS) system. The research purpose is to offer a theoretical model of the Technology Acceptance Model (TAM) to evaluate the use and acceptance of users to the OSS system at the Investment Service and One-Stop Integrated Service of the Samarinda City during the Covid-19 pandemic. The method used to measure the variable effects using Partial Least Square - Structural Equation Modeling (PLS-SEM) on perceived ease of use (usability) and perceived usefulness, behavior intention to use, and Attitude toward Using the Online Single Submission system. Based on the results of testing the hypothesis H0 proposed is accepted. OSS system users find it useful to assist in completing work (licensing process). That perceived Ease of Use, Perceived Usefulness have a positive effect and significant on the Behaviour Intention to Use adopt the OSS system for users and have a goodness of fit.
COMPARISON OF LINEAR AND VECTOR DATA NORMALIZATION TECHNIQUES IN DECISION MAKING FOR LEARNING QUOTA ASSISTANCE Edy Budiman; Ummul Hairah
Journal of Information Technology and Its Utilization Vol 4, No 1 (2021)
Publisher : Sekolah Tinggi Multi Media (STMM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.4.1.3897

Abstract

Data normalization is essential for all kinds of decision-making problems, and a lot of effort has been spent on the development of normalization models in multi-criteria decision making (MCDM), but despite all this, there is no definite answer to the question: Which is the most appropriate technique?. This paper compares the popular normalization techniques: Linear Normalization (LN) and Vector Normalization (VN) using VIsˌekriterijumsko KOmpromisno Rangiranje (VIKOR) Method. The beneficiaries dataset of learning quota was collected of 399 students sample through observation (drive-test measurements and online questionnaires) to obtain information on criteria data including attributes in online learning during the Covid-19 pandemic. The ranking results for vector vs linear normalization show how ranking is affected. The difference in the selection of the best alternative (rank) shows that there are differences in vector and linear assessments that are influenced by the max-min criterion value which has an impact on the rank- sum results (benefit/cost). This test clearly shows how important it is to use an appropriate (normalized) representation of the model because there will often be a criterion where "the higher the better" while for others (cost) "the lower the better".