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All Journal JURNAL SISTEM INFORMASI BISNIS Variance : Journal of Statistics and Its Applications
Tikno, Tikno
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Computer Science & IT Economics, Econometrics & Finance Mathematics

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FILLING THE PRECIPITATION GAPS: ACCURATE IMPUTATION WITH SUPPORT VECTOR REGRESSION IN NORTH SULAWESI Cahyaning, Angelin; Miftahurrohmah, Brina; Prassida, Grandys Frieska; Tikno, Tikno
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page183-194

Abstract

Incomplete precipitation data poses major challenges in accurate precipitation predictions, hindering the effectiveness of water resource management and disaster risk mitigation efforts in North Sulawesi, Indonesia. This research aims to develop a precipitation prediction model using Support Vector Regression (SVR) to handle missing data. The precipitation data used comes from BMKG and ERA5 stations. The results show that using the RBF kernel with parameters ∁ = 1000, ɛ = 0.1, γ = 100 produces the best predictions, except Dtatiun Meteorologi Naha with γ = 1000. The best model is shown in the model evaluation RMSE of 0.099, MAE of 0.099, and R² of 0.999. The ability of SVR to capture precipitation trends is shown in the model evaluation results. The best model obtained is used for the missing data imputation process.
Evaluating The Impact of Digital Marketing Strategies on Enrollment Decisions through PLS-SEM Analysis: Insights from Private University X Syunita, Zahra Raniah Putri; Tikno, Tikno
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp237-250

Abstract

This study evaluates the effectiveness of digital marketing strategies in influencing enrollment decisions at Indonesian private universities. With the increasing reliance on digital platforms, higher education institutions (HEIs) have adapted their marketing approaches to engage digitally-savvy prospective students. The aim of this research is to identify the most impactful strategies and their contribution to student enrollment decisions. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM), the study compares three models: one derived from prior research and two newly proposed by the authors. Data collected from 325 respondents revealed that social media engagement and personalized direct messaging significantly enhance enrollment decisions, with the highest R² value (0.772) observed for social media engagement in Model 2. The Bayesian Information Criterion (BIC) indicated Model 2 as the best fit (-255.774) for explaining enrollment decisions. These findings suggest that strategies emphasizing social media engagement and personalized communication yield the greatest impact on prospective students. This study contributes to the growing field of digital marketing in higher education by offering actionable insights for enhancing online visibility and optimizing enrollment outcomes in a competitive market.
Analysis of Self-Efficacy and User Satisfaction in Sustainable Use of The GOBIS Surabaya Application through PLS-SEM Approach Abdhillah, Sony; Tikno, Tikno
Jurnal Sistem Informasi Bisnis Vol 15, No 3 (2025): Volume 15 Number 3 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss3pp%p

Abstract

This study aims to examine the factors influencing the sustained usage of the GoBis e-government application in Surabaya, Indonesia. By investigating constructs such as Information Quality (IQ), Personal Outcome Expectation (POE), Self-Efficacy (SE), Satisfaction (SAT), Service Quality (SQ), Social Influence (SI), and Prior Experience (PE), the research utilizes Structural Equation Modeling - Partial Least Squares (SEM-PLS) to analyze user engagement and behavior. The analysis, based on a sample of 409 respondents, reveals that Information Quality, Personal Outcome Expectation, Self-Efficacy, and Satisfaction significantly impact users' intention to continue using the application. Specifically, Information Quality was identified as a crucial determinant, influencing Continuance Intention, Self-Efficacy, and Satisfaction, highlighting the importance of high-quality information in building user confidence and satisfaction. In contrast, Service Quality and Social Influence were found to have a limited effect on Continuance Intention, suggesting that these factors contribute to user satisfaction but are not primary drivers of long-term engagement. The findings emphasize the need for improving user experiences by enhancing information quality, promoting self-efficacy programs, and providing regular user-centered updates. The study concludes with recommendations for stakeholders to focus on continuous service improvements and regular user feedback evaluations to meet evolving public service standards and foster higher community engagement.
Co-Authors Abdhillah, Sony Cahyaning, Angelin Grandys Frieska Prassida Miftahurrohmah, Brina Syunita, Zahra Raniah Putri