Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Proceedings of Femfest International Conference on Economics, Management, and Business
Dian Essa Nugrahini
Universitas Islam Sultan Agung, Indonesia
Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Exploring Cryptocurrency Investment Choices among Generation Z Muslims – A Conceptual Analysis Verina Purnamasari; Dian Essa Nugrahini; Diah Ayu Kusumawati
Proceedings of Femfest International Conference on Economics, Management, and Business Vol. 2 (2024): Proceedings of Femfest International Conference on Economics, Management, and Busines
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The emergence of cryptocurrency as a form of digital currency investment is a consequence of the global shift towards a technology-driven way of life. Despite its notable volatility, intricate price dynamics, and decentralized nature, cryptocurrencies have managed to attract a considerable number of investors for reasons that are not extensively explored. Indonesia, situated in Asia and characterized by a predominantly Islamic population and heightened awareness of cryptocurrencies, stands out in this context. The primary objective of this study is to pinpoint the factors that influence investment decisions in cryptocurrencies among potential Generation Z investors in Indonesia. The research methodology involves the dissemination of surveys to individuals who meet specific criteria, including being Indonesian citizens, at least 17 years old, practicing Islam, and possessing a National Identity Card, a prerequisite for engaging in cryptocurrency investments. The gathered data will undergo analysis using Structural Equation Modeling (SEM) equations through the SmartPLS application Keywords: Cryptocurrencies, Investments, Attitudes to risk, Subjective norms, Machine learning forecasting.
Co-Authors Diah Ayu Kusumawati Verina Purnamasari