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All Journal JELAJAH: Journal of Tourism and Hospitality Journal of Business and Political Economy: Biannual Review of The Indonesian Economy Review The International Journal of Financial Systems
Kurniawan, Bagja
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Humanities Economics, Econometrics & Finance Social Sciences

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Dynamics of Economic Factors Influencing Human Development in ASEAN-7 Kurniawan, Bagja
Journal of Business and Political Economy : Biannual Review of The Indonesian Economy Vol. 4 No. 2 (2022): Journal of Business and Political Economy
Publisher : INDEF - Institute for Development of Economics and Finance

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46851/175

Abstract

Abstract This study analyzes the relationship between economic factors and human development in the seven ASEAN countries using the panel data regression approach and Moderated Regression Analysis (MRA). The factors investigated include international trade (TRD), per capita GDP growth (GrGDPPC), inflation (INF), and economic freedom (EFI). Panel data covers seven ASEAN countries during the 2012–2020 time period. Based on the results of the panel data regression analysis, it was found that only the inflation variable did not have a significant effect on human development. Meanwhile, the results of the MRA analysis show that economic freedom acts as a quasi-moderation in the relationship between international trade and human development. Meanwhile, economic freedom also functions as an independent variable in influencing the growth of GDP per capita and inflation in human development. These findings provide a deeper understanding of the complexity of the interactions between economic factors shaping HDI achievement in ASEAN. Keywords: ASEAN, economic freedom, human development JEL: O15, F43, E31, I32
RegTech on Crypto FinTech: What Needs to be Done and Its Implications for the Anti-Money Laundering Mechanism Fajri, Kharisma Fatmalina; Faachrezzi, Bima Rafly; Kurniawan, Bagja
The International Journal of Financial Systems Vol. 2 No. 2 (2024)
Publisher : Otoritas Jasa Keuangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61459/ijfs.v2i2.75

Abstract

Crypto laundering has become a significant threat in Indonesia since 2015, particularly through digital payment systems. Despite efforts to combat this threat using Regulatory Technology (RegTech), the outcomes have been largely ineffective. This study expands on previous research exploring the causes of RegTech's ineffectiveness and seeks to provide policy recommendations based on RegTech provider perspectives, for Indonesian regulators to enhance crypto laundering mitigation through RegTech. The research employed an exploratory-inductive methodology, utilising primary data from semi-structured interviews with AML operating system specialists. The data were transcribed and thematically analysed using NVivo software. The findings reveal six key themes for improving RegTech effectiveness: (1) AML mechanisms tailored to various sizes of Crypto FinTechs; (2) Access to PEP data by RegTech providers; (3) Clear classification of RegTech; (4) Strengthened collaboration between regulators and RegTech providers; (5) Regulator-led education initiatives for Crypto FinTechs; and (6) The establishment and enforcement of sanctions. These insights hold significant implications for regulatory policies aimed at preventing crypto laundering through RegTech and contribute to the application of Rational Choice and Butterfly Effect theories in understanding crypto laundering as a criminal phenomenon.
Tourist Destination Segmentation in Jember Using Cluster Analysis for Data-Driven Tourism Development Kurniawan, Bagja
JELAJAH: Journal of Tourism and Hospitality Vol. 6 No. 2 (2025)
Publisher : Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jelajah.v6i2.11704

Abstract

For strategic tourism planning in Jember, data-based segmentation must be applied in order to optimize destination management. The clustering of tourist attractions in Jember needs to be categorized in order to derive descriptive patterns and support the policies pertaining to tourism development. Experiments apply K-Means Clustering, DBSCAN, and Agglomerative Clustering methodologies to classify the tourist sites based upon name, rating, ticket prices, location, and reviews. Data Preprocessing involves encoding for categorical features, scaling for numerical features, and addressing missing values. Elbow Method, Silhouette Score, Davies-Bouldin Score, and Calinski-Harabasz Score are applied to ascertain the most fitting clustering solution. K-means clustering has identified three major clusters: high-priced premium destinations, low-priced mass spread destinations, and overwhelmingly crowded yet highly satisfactory destinations. DBSCAN shows two distinctive clusters and outlier clusters with unique destinations. Agglomerative Clustering gives clear separate clusters of high, middle, and low-cost attractions. Such findings are useful for tourism stakeholders to develop targeted marketing policies, improve visitor experiences, and use their resources in the most efficient way. By the performance indicators of each cluster, tourism managers can optimize service quality and competitiveness of the destination. This study assists in data-informed decision-making in regional tourism planning which goes hand in hand with sustainable tourism development.
Co-Authors Faachrezzi, Bima Rafly Fajri, Kharisma Fatmalina