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All Journal POSITIF InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan SISFOTENIKA Technomedia Journal Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) CCIT (Creative Communication and Innovative Technology) Journal ADI Journal on Recent Innovation (AJRI) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics International Journal of Marine Engineering Innovation and Research ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Engineering, Science and Information Technology International Journal of Cyber and IT Service Management (IJCITSM) Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application
Marviola Hardini
Universitas Raharja
Religion Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Aptisi Transactions on Management

 1 
Understanding Consumer Acceptance of AI in the Leisure Economy: A Structural Equation Modeling Approach Susilawati; Juliastuti, Dyah; Hardini, Marviola
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2348

Abstract

This research examines the determinants of consumer acceptance of artificial intelligence (AI) in the leisure economy, using a structural equation model to analyze responses from 560 participants. The study focuses on several psychological factors: Perceived Ease of Use (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Perceived Value (PV), and Habit (HB), and their impact on Behavioral Intention (BI) to adopt AI technologies. Results indicate significant influence of six constructs (PE, FC, SI, PV, HM, HB) on BI, with the exception of one hypothesis. The research also assesses the role of Personal Innovativeness in enhancing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model's predictive accuracy. This study contributes to understanding AI adoption in leisure, offering valuable insights for AI application development and marketing strategies in this sector.
Management of Utilizing Data Analysis and Hypothesis Testing in Improving the Quality of Research Reports Yusup, Muhamad; Syauqi Naufal, Romzi; Hardini, Marviola
APTISI Transactions on Management (ATM) Vol 2 No 2 (2018): ATM (APTISI Transactions on Management)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.306 KB) | DOI: 10.33050/atm.v2i2.789

Abstract

Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses.
Analysis of Covid 19 Data in Indonesia Using Supervised Emerging Patterns Rahardja, Untung; Dewanto, Ignatius Joko; Djajadi, Arko; Candra, Ariya Panndhitthana; Hardini, Marviola
APTISI Transactions on Management (ATM) Vol 6 No 1 (2022): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v6i1.1768

Abstract

This research method uses CRISP-DM with emerging pattern supervision modeling and EPM Algorithm. The contribution of the research is to assist the Government in overcoming the problem of the spread of the COVID-19 cluster in several regions in Indonesia. The research aims to implement information on the COVID-19 data mining pattern in the DKI Jakarta area. The problems faced are the difficulty of identifying the pattern of COVID-19 data in one area, it is difficult to dig up data on the http://corona.jakarta.go.id website. It is not easy to decide on the handling of COVID-19. The output of the research results in a cluster of information on COVID-19 in the DKI Jakarta area based on Significance level depends on the Covid Map In terms of Region, Status, Gender, & age And Signification can be the basis for determining covid OTG, DTG, and Positive. The theoretical and practical implications can be stated as follows: The use of supervised emerging pattern methods can affect the processing of COVID-19 data. For 5 Regions in DKI Jakarta and distribution to determine covid OTG, DTG, and Positive. The result of the development of this data mining system is to produce pattern reports to produce Supervised Emerging Patterns technology for decision making at the COVID-19 Task Force in DKI Jakarta.
Risk Management Model for Compliance and Security in Blockchain Powered Payment Platforms Novalita Savitri, Agnes; Hardini, Marviola; Yao, Goh
APTISI Transactions on Management (ATM) Vol 9 No 2 (2025): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i2.2475

Abstract

Blockchain technology has revolutionized financial services by enabling decen- tralized, transparent, and tamper-resistant payment platforms. However, these innovations bring significant challenges related to regulatory compliance and security management, which threaten platform adoption and user trust. This study aims to develop and empirically validate a comprehensive risk management model that integrates both regulatory oversight and security auditing dimensions specific to blockchain-powered payment systems. A cross-sectional survey was conducted among 215 industry practitioners involved in blockchain payment platforms. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study tested hypothesized relationships among regulatory over- sight, smart contract auditing, perceived compliance and security risks, risk mit- igation intent, and platform adoption intention. The results demonstrate that regulatory oversight and smart contract auditing significantly increase perceived compliance and security risks. These heightened risk perceptions positively in- fluence intentions to mitigate risks, which in turn significantly drive platform adoption. The model explains 58% and 42% of the variance in risk mitigation intent and platform adoption intention, respectively, confirming its strong ex- planatory power. This research contributes a validated, unified risk manage- ment framework that guides policymakers, platform operators, and auditors in addressing intertwined compliance and security risks. The findings support the advancement of safer, more trustworthy blockchain payment systems, fostering broader adoption and aligning with evolving regulatory landscapes. 
Framework for Implementing Green Supply Chain Practices in Indonesian Small and Medium Enterprises Aini, Qurotul; Hardini, Marviola; Hikam, Ihsan Nuril; Green, Thomas
APTISI Transactions on Management (ATM) Vol 9 No 3 (2025): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/23c5gv23

Abstract

The urgent need to address climate change, environmental degradation, and resource depletion has driven the adoption of sustainable business practices globally. For Small and Medium Enterprises (SMEs), particularly in developing countries such as Indonesia, transitioning toward sustainability presents both challenges and opportunities. Green Supply Chain Management (GSCM) offers a comprehensive approach to integrating environmental considerations into every stage of the supply chain, from sourcing raw materials to end-of-life product management. This study develops a practical GSCM framework tailored for Indonesian SMEs, using a qualitative multiple-case study method across three sectors: food, handicrafts, and logistics. Data collection methods included semi-structured interviews, on-site observations, and document analysis, followed by thematic coding and cross-case synthesis. The resulting framework identifies five interrelated components: supplier collaboration, eco-friendly material selection, waste reduction strategies, energy efficiency optimization, and sustainability performance monitoring. The framework is validated through triangulation of data sources and feedback from SME stakeholders. By aligning with the United Nations Sustainable Development Goals (SDGs), particularly Goals 12 and 13, this study provides actionable insights for policymakers, SME owners, and practitioners seeking to enhance sustainability while maintaining operational efficiency.
Co-Authors Abbas, Maulana Aditya Mardiansyah Agarwal, Vertika Ali Djamhuri Amitkumar Dudhat Andriyansah . Ani Wulandari Anjani, Sheila Aulia Ankur Singh Apriliasari, Dwi Arko Djajadi Bist, Ankur Singh Candra, Ariya Panndhitthana Chandra Abianto Chen, Shih Chih Dedeh Supriyanti Desy Apriani Dewi Immaniar Dwi Julianingsih Farail, Maulana Faqih Faturahman, Adam Fitra Putri Oganda Fitriani, Anandha Green, Thomas Harahap, Eka Purnama Hetilaniar Hetilaniar Hikam, Ihsan Nuril Hiroshi Kenta Husni Teja Sukmana Ignatius Joko Dewanto, Ignatius Joko Ihsan Nuril Hikam Ikhsan, Ramiro Santiago Ilham, Muhammad Ghifari Julianingsih, Dwi Juliastuti, Dyah Karts, Kawl W Leffia, Abigail Lena Magdalena Lic, Yung-Ming Lusyani Sunarya Maulana, Sabda Megha Upreti Mertayasa, I Komang Mey Anggraeni Mochamad Heru Riza Chakim Muhamad Yusup Muhammad Rehan Anwar Nanda Septiani Natalia, Elisa Ananda Ninda Lutfiani Novalita Savitri, Agnes Nuke Puji Lestari Santoso Nur Azizah NURAENI, RANI Nurasiah Nurasiah Nurhaeni, Tuti Pandey, Chitra Parker, Jonathan Po Abas Sunarya Pujiati, Tri Qurotul Aini Rafika, Ageng Setiani Rawat, Buphest Rissa Rahmania Santoso, Nuke Puji Lestari Semaria Eva Elita Girsang Setiawaty, Elika Sihotang, Sondang Visiana Siti Nurindah Sari Souza Nurafrianto Windiartono Putra Sudaryono Sudaryono Sunarjo, Richard Andre Susilawati Syauqi Naufal, Romzi Tarisya Ramadhan Tuti Nurhaeni Untung Rahardja Upreti, Megha Vaher, Kristina Widjaya, Irene Apriani Widya Febriani Yao, Goh