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All Journal Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain International Journal Research on Metaverse
Satrya Fajri Pratama
Department of Computer Science, School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, United Kingdom
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Temporal Patterns in User Conversions: Investigating the Impact of Ad Scheduling in Digital Marketing Satrya Fajri Pratama; Dwi Sugianto
Journal of Digital Market and Digital Currency Vol. 1 No. 2 (2024): Regular Issue September 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v1i2.10

Abstract

This study explores the impact of ad scheduling on user conversions by analyzing temporal patterns in user behavior. In the increasingly competitive landscape of digital marketing, optimizing the timing of ad placements is critical for maximizing user engagement and conversion rates. Utilizing a comprehensive dataset from Kaggle, which includes variables such as user ID, ad exposure details, and conversion outcomes, we employed both time series analysis and survival analysis to uncover insights into how different ad scheduling strategies affect conversion rates. The ARIMA model, used for time series analysis, provided reasonable predictive accuracy with a Mean Absolute Error (MAE) of 389.92, Root Mean Squared Error (RMSE) of 463.97, and Mean Absolute Percentage Error (MAPE) of 2.26%. This model effectively identified specific hours and days with higher likelihoods of conversion, particularly during evenings and weekends. On the other hand, the Cox Proportional Hazards model, used for survival analysis, demonstrated superior performance with a concordance index of 0.97, indicating its exceptional ability to predict the timing of user conversions based on various covariates such as the number of ads seen and the specific hours of exposure. The findings suggest that strategic ad scheduling, tailored to align with user temporal behavior, can significantly enhance marketing effectiveness by targeting users during peak conversion periods. These insights offer practical implications for digital marketers aiming to refine their ad delivery strategies to achieve higher conversion rates and improve return on investment.
Analyzing the Determinants of User Satisfaction and Continuous Usage Intention for Digital Banking Platform in Indonesia: A Structural Equation Modeling Approach Satrya Fajri Pratama
Journal of Digital Market and Digital Currency Vol. 1 No. 3 (2024): Regular Issue December 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v1i3.21

Abstract

This study investigates the factors influencing user satisfaction (US) and continuous usage intention (UI) of the digital banking platform in Indonesia. Utilizing a quantitative research approach, structural equation modeling (SEM) via SmartPLS was employed to analyze data from 376 users. The study integrates key constructs, including Task-Technology Fit (TTF), System Quality (SQ), Performance Expectancy (PE), US, and UI, into a comprehensive model. The findings confirm that TTF, SQ, PE, and US significantly influence UI. Specifically, higher TTF and SQ directly enhance PE (path coefficient = 0.871, t-value = 92.895) and US (path coefficient = 0.798, t-value = 47.957), positively impacting UI. Performance Expectancy emerged as a stronger predictor of UI (path coefficient = 0.559, t-value = 12.800) compared to the US (path coefficient = 0.245, t-value = 5.229), underscoring the critical role of perceived performance benefits in driving continuous usage. All five hypotheses were supported: TTF positively affects UI (path coefficient = 0.250, t-value = 7.154); SQ positively influences PE and US; PE positively impacts UI; and US positively affects UI. The Sobel test results indicated that PE significantly mediates the relationship between SQ and UI (Z = 12.60), and US also significantly mediates this (Z = 5.19). The R-squared values indicate the explanatory power of the model: PE (0.758), UI (0.956), and US (0.637), demonstrating that the model explains a substantial portion of the variance in these constructs. The study contributes to the literature by validating the integrated model, extending existing models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), and highlighting the importance of technical and perceptual factors in technology adoption. Practically, the results offer actionable insights for digital banking providers. Enhancing TTF and maintaining high SQ are crucial for fostering positive user experiences and encouraging continuous usage. Providers should also emphasize the performance benefits of their platforms to improve PE and UI. Despite its contributions, the study has limitations, including sample size and reliance on self-reported data, which may affect generalizability. Future research could expand the sample size, incorporate objective usage data, and explore additional factors such as social influence and facilitating conditions. Overall, the study provides a robust framework for understanding user behavior in digital banking and offers practical strategies for improving user satisfaction and retention in the industry.
Evaluating Blockchain Adoption in Indonesia's Supply Chain Management Sector Satrya Fajri Pratama; Priyo Agung Prastyo
Journal of Current Research in Blockchain Vol. 1 No. 3 (2024): Regular Issue December 2024
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v1i3.21

Abstract

This research evaluated the adoption of blockchain technology in the supply chain management sector, focusing on the factors that influence the intention to use blockchain, including perceived usefulness, security, facilitating conditions, cost, regulatory support, and trust. Data were collected through a cross-sectional survey distributed to 315 individuals actively involved in supply chain management, of which 309 valid responses were obtained after a validation process that included screening questions such as prior use of blockchain technology. The study employed structural equation modeling (SEM) for data analysis. The findings highlighted that trust played a significant mediating role between perceived usefulness, security, and intention to use blockchain technology. Perceived usefulness and security were found to significantly enhance trust, which in turn positively influenced the intention to adopt blockchain. Regulatory support also had a strong positive impact on adoption intentions, underscoring the importance of clear and supportive regulatory frameworks. Cost was identified as a barrier to adoption, reflecting the need for organizations to address financial concerns associated with blockchain implementation. The results contributed to the theoretical understanding of blockchain adoption by integrating trust as a key mediator in the Technology Acceptance Model and offered practical implications for supply chain management professionals and policymakers.
Analyzing Genre Patterns in Virtual-Themed Animated Films Using Association Rule Mining Satrya Fajri Pratama; Eko Priyanto
International Journal Research on Metaverse Vol. 1 No. 3 (2024): Regular Issue December 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijrm.v1i3.15

Abstract

This study investigates patterns in virtual-themed animated films using association rule mining to explore the relationships between genre combinations, production companies, and their impact on both popularity and revenue. The dataset consists of films from various genres, with a focus on those exploring virtual worlds, alternate realities, and futuristic settings, aligning with metaverse concepts. The analysis revealed several significant findings. The association rule mining results identified that films combining Fantasy and Science Fiction genres are 1.8 times more likely to achieve high box office revenue, with a confidence level of 80%. Additionally, Pixar adventure films were found to have a 2.1 times higher likelihood of attaining high popularity. Films blending Fantasy and Adventure genres showed a strong correlation with high revenue, with a 70% confidence level and a lift value of 1.9. These patterns suggest that imaginative storytelling and virtual world elements are key drivers of success in animated films. Revenue analysis demonstrated that 30% of the virtual-themed films in the dataset generated more than 1 billion USD, while 50% earned between 0.5 and 1 billion USD. The popularity analysis further highlighted that Fantasy, Science Fiction, and Adventure genres consistently rank highest in audience engagement. These findings underscore the significant commercial potential of films exploring virtual and digital environments, particularly as audience demand for immersive experiences continues to grow. This study concludes that films featuring virtual world themes, particularly those combining Fantasy, Science Fiction, and Adventure genres, are well-positioned to succeed both financially and in terms of audience engagement. As AR, VR, and metaverse technologies advance, the demand for immersive cinematic experiences is likely to increase, offering filmmakers new opportunities to innovate and expand this genre.
Co-Authors Dwi Sugianto Eko Priyanto Priyo Agung Prastyo