Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal PROFIT : Jurnal Administrasi Bisnis International Journal of Business Accounting Management Social Science
Rizki Yudhi Dewantara
Universitas Brawijaya
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
SUCCESS OF IMPLEMENTATION OF COMPUTER CRIME ACT (UU ITE NO.11 2008) (A Case Study in the Higher Education Institution in Indonesia) Rizki Yudhi Dewantara
Profit: Jurnal Adminsitrasi Bisnis Vol. 11 No. 1 (2017): PROFIT : Jurnal Administrasi Bisnis
Publisher : FIA UB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (394.737 KB) | DOI: 10.21776/ub.profit.2017.011.01.4

Abstract

Computer crime rate grow rapidly along with the development of the digital world that has touched almost all aspects of human life. Institutions of higher education cannot be separated from the problem of computer crime activities. The paper analyses the implementation of Indonesia Computer Crime Act (UU ITE NO.11 2008) in the Higher Education Institution in Indonesia. It aims to investigate the level of computer crimes that occurred in the higher education institution environment and the act (UU ITE 11, 2008) successfully applied to prevent the crime that would arise. In this research, the analysis using Descriptive Statistics, Binary logistic regression. This paper also describes the success implementation of the Information System Security Policy (ISSP) as a computer crime prevention policy in higher education institution in Indonesia. In factor of act, clarity of objectives and purpose of the UU ITE 11, 2008 was low, the communication and socialization activities are still low to the society especially to the higher education institution, moreover the control process has been running on UU ITE 11, 2008, but at a low level.Keywords: computer crime, computer crime act, public policy implementation ABSTRAK Kejahatan Komputer berkembang pesat sejalan dengan perkembangan dunia digital, pada institusi perguruan tinggi tidak dapat dipisahkan dari bagian kejahatan computer. Penelitian ini merupakan analisis kesuksesan penerapan undang-undang kejahatan komputer (UU ITE 11, 2008) di institusi perguruan tinggi di Indonesia. Penelitian ini bertujuan untuk mengetahui tingkat kejahatan komputer yang terjadi pada lingkungan institusi perguruan tinggi dan kesuksesan penerapan undang-undang kejahatan komputer untuk mencegah tindakan kejahatan komputer yang mungkin dapat terjadi maupun menangani kejahatan yang sedang terjadi. Berdasarkan tujuan penelitian, digunakan pendekatan quantitative dengan beberapa uji statistic antara lain analisis statistic deskriptif, dan regresi logostik binari. Hasil penelitian menjelaskan tingkat kesuksesan penerapan kebijakan keamanan sistem informasi sebagai tindakan pencegahan kejahatan sistem informasi di Institusi perguruan tinggi di Indonesia. Hasil penelitian menyatakan bahwa rendahnya faktor undang-undang, kejelasan isi dan tujuan dari kebijakan kemanan komputer di institusi perguruan tinggi mempengaruhi tingkat kesuksesan penerapan kebijakan kemanan sistem informasi, selanjutnya proses pengendalian telah berjalan pada UU ITE 11, 2008, namun pada skala yang rendah.Kata Kunci: kejahatan komputer, undang-undang kejahatan komputer, implementasi kebijakan publik 
Mobile Gamification and Purchase Intention: Evidence from Traveloka Rizki Yudhi Dewantara; M. Alif Elijah Veron
IJBAMS: International Journal of Business Accounting Management Social Science Vol. 1 No. 3 (2025): December
Publisher : Manajemen Multitalenta Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64530/ijbams.v1i3.35

Abstract

The increasing competitiveness among online travel agencies (OTAs) has encouraged companies to innovate through user‐engagement strategies such as mobile gamification. Gamification refers to the integration of game elements into non‐game contexts to enhance users’ enjoyment, motivation, and behavioral intentions. This study investigates the effect of gaming affordances on purchase intention, mediated by enjoyment, among users of the Traveloka mobile application in Indonesia. Using an explanatory quantitative design, data were collected from 115 respondents who had previously interacted with Traveloka’s gamified features. The analysis employed path analysis using SPSS version 29. Results indicate that gaming affordances particularly achievement, identity, and competition affordances significantly influence enjoyment, while self‐expression affordance shows a positive but nonsignificant relationship. Furthermore, enjoyment significantly predicts purchase intention, confirming its mediating role between gaming affordances and user behavioral intention. These findings demonstrate that well‐designed gamification elements can enhance user experience and drive purchase decisions in mobile travel platforms. Implications for OTA developers and future research directions are also discussed.
Understanding Customer Satisfaction Through Aspect-Based Sentiment Analysis in The Aku Cinta Indonesia App Sopyan Sopyan; Rizki Yudhi Dewantara
IJBAMS: International Journal of Business Accounting Management Social Science Vol. 2 No. 1 (2026): April
Publisher : Manajemen Multitalenta Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64530/ijbams.v2i1.46

Abstract

Understanding customer satisfaction is essential for digital service providers operating in highly competitive markets, particularly in the online transportation sector, as numerical ratings alone are often insufficient to capture the complexity of user experiences expressed in textual reviews. This study employs Aspect-Based Sentiment Analysis (ABSA) to obtain a more granular understanding of customer satisfaction based on user reviews of the Aku Cinta Indonesia (ACI) application collected from the Google Play Store. Five key service aspects are examined, namely User Experience, Payment, Service, Promo and Benefit, and Security and Access. To support the analysis, two sentiment classification approaches, Naive Bayes and IndoBERT, are utilized to evaluate sentiment polarity at the aspect level. The results indicate that User Experience, Payment, and Service are the most influential aspects shaping customer satisfaction, as they consistently appear in both positive and negative reviews. While both models demonstrate reliable performance, IndoBERT achieves higher classification accuracy at 82% compared to Naive Bayes at 77%, indicating a stronger ability to capture contextual nuances in Indonesian user generated content. From a business perspective, these findings highlight how ABSA transforms unstructured customer feedback into actionable insights that enable service providers to identify critical improvement areas, prioritize service quality enhancements, and strengthen customer satisfaction strategies. This study demonstrates the value of ABSA as a business analytics tool that supports data driven decision making and enhances competitiveness in the digital transportation service market.
Identifying Customer Satisfaction through Negative Sentiment Analysis using Support Vector Machine in the JIWA+ App Muhammad Faqih Maulana; Rizki Yudhi Dewantara
IJBAMS: International Journal of Business Accounting Management Social Science Vol. 2 No. 1 (2026): April
Publisher : Manajemen Multitalenta Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64530/ijbams.v2i1.47

Abstract

The rapid growth of mobile commerce has positioned mobile applications as critical touchpoints influencing customer satisfaction and business performance. This study aims to identify customer satisfaction patterns by analyzing negative user reviews of the JIWA+ mobile application using the Support Vector Machine (SVM) algorithm. A total of 1,025 reviews collected from the Google Play Store during the period 2022–2025 were processed through text preprocessing, TF-IDF feature extraction, and sentiment classification into positive, neutral, and negative categories. The SVM model achieved an overall accuracy of 0.746, demonstrating reliable capability in classifying sentiment polarity, particularly in detecting negative reviews. The findings indicate that 35.7% of reviews reflect negative sentiment, highlighting significant dissatisfaction among users. The dominant complaint themes include transaction failures (“pesan”), feature usability issues (“pakai”), and discrepancies between digital information and outlet conditions (“gerai”). These issues primarily relate to system reliability, payment functionality, and digital–offline integration. From a business management perspective, this study positions sentiment analysis as a strategic analytical tool that transforms unstructured customer feedback into actionable managerial insights. The results contribute to the literature on mobile applications, sentiment analysis, and customer satisfaction by demonstrating how machine learning–based approaches can support data-driven decision-making in enhancing digital service performance and sustaining competitive advantage.
Co-Authors M. Alif Elijah Veron Muhammad Faqih Maulana Sopyan Sopyan