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Asia Information System Journal
Published by Universitas Islam Negeri Raden Intan Lampung
ISSN : -     EISSN : 29638593     DOI : -
Core Subject : Science,
Computer Science & IT
Asia Information System Journal (AISJ) is an international journal promoting the study of, and interest in, information systems. Articles are welcome on research, practice, experience, academic, current issues and debates from all over the world that covers topics such as the improvement of information system and technology including but not limited to: Alignment of business processes with IT operations, Information system architecture, Information system methodologies, Information system security, Information System Technology, System requirements engineering, System testing and quality assurance and more
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 4 Documents
 1 
Search results for , issue "Vol. 4 No. 2 (2025): Asia Information System Journal" : 4 Documents clear
DEVELOPMENT OF MOBILE WEB APPLICATIONS TO IMPROVE ACCESS TO INFORMATION AND SERVICES (CASE STUDY: PEKON TANJUNG REJO) Joni; Ricco Herdiyan Saputra; Lucy Asiyani; Dita Novitasari
Asia Information System Journal Vol. 4 No. 2 (2025): Asia Information System Journal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/dpgvjm11

Abstract

The management of information and public services at the pekon level is still largely manual, resulting in delays, inefficiencies, and limited access for the community. This research aims to design and develop a mobile web application that supports improving access to information and administrative services in Pekon Tanjung Rejo. The methods used include needs studies through observation of service processes and interviews with pekon officials and residents, system design using the UML approach, implementation using PHP, Bootstrap, and XAMPP, and functional testing using the black-box method. User Acceptance Testing was conducted on eight participants consisting of three pekon officers and five residents as representatives of end users. The results of the development resulted in four main modules, namely the pekon information page, the administrative dashboard, the community contact feature through the Sapa Village menu, and the officer management module. Functional testing shows that all core functions including authentication, data management, and information delivery are running as specified. User acceptance tests show that the application interface is considered easy to understand, and supports accelerating access to information by the public. However, several obstacles were found, such as limited internet connectivity in certain regions and variations in users' digital literacy that affect the optimal use of applications. This study recommends improving connection stability, improving notification features, and long-term evaluation to assess the impact of applications on the effectiveness of public services at the pekon level.
HOW PERCEIVED RISK AND TRUST AFFECT ONLINE PAYMENT INTENTIONS: A SURVEY-BASED STUDY WITH CONFIRMATORY FACTOR ANALYSIS (CFA) AND STRUCTURAL EQUATION MODELLING (SEM) Rahul R. Verma
Asia Information System Journal Vol. 4 No. 2 (2025): Asia Information System Journal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/vm2xrf42

Abstract

The rapid expansion of digital financial services has transformed transaction behaviors, yet understanding the specific drivers of purchase intention remains complex. Comprehensive literature reviews exist, there is a lack of empirical research that distinctly separates "online purchase intention" from general "purchase intention," particularly regarding how specific risk dimensions directly erode user trust in emerging platforms. This study aims to bridge this gap by empirically examining the structural relationships between perceived risk (financial, privacy, and performance), trust, and online purchase intention. A quantitative survey approach was employed, gathering data from 300 respondents. The measurement model and structural paths were validated using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). The findings reveal that perceived risk significantly negatively affects trust. However, trust demonstrates the strongest positive effect on intention (β=0.53), accounting for substantial variance (R 2=0.52) in the model. These results suggest that fintech providers must prioritize trust-building mechanisms over merely functional features. Future research is recommended to explore moderating factors such as user experience levels to further validate this model across different demographics
ALGORITHMIC OPTIMIZATION INFORMATION AND STRATEGIES FOR INCREASING THE REACH OF BEGINNER CREATOR ACCOUNTS ON FACEBOOK PRO IN INDONESIA Chairul, Muhammad Ilham Firizkillah; Waskita, Arya Adhyaksa; Wiharjo, Sudarno; RA, Okta Reni Azrina
Asia Information System Journal Vol. 4 No. 2 (2025): Asia Information System Journal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/qa0g3q17

Abstract

The evolution of algorithmic systems on digital platforms has fundamentally transformed the logic of content distribution, shifting from chronological feeds to AI-driven recommendation ecosystems that act as active regulators of creator visibility. While discussions on algorithmic visibility are extensive for platforms like TikTok and Instagram, a significant research gap remains regarding the Indonesian creator ecosystem on Facebook Pro, particularly concerning how human–algorithm interaction shapes content performance. This study aims to analyze algorithm optimization strategies among beginner creators on Facebook Pro by examining the critical relationship between content format consistency, engagement velocity, and algorithmic distribution. Research Method: Adopting a qualitative-descriptive design, a case study was conducted on two Indonesian creator accounts—Muhammad Ilham Firizkillah and Sejenak Hening—representing contrasting storytelling-educational and motivational production paradigms. Primary data were collected from Facebook Pro Insights between July and October 2025, utilizing Python-based analytics to evaluate Reels performance, retention rates, and audience growth. The results indicate a striking contrast in performance: the Sejenak Hening account achieved an 876% increase in reach and 1.1 million views by maintaining consistent themes and visuals, allowing the algorithm to recognize stable patterns for exponential distribution. Conversely, the Ilham Firizkillah account saw a 52% decline in views due to high format variation and weak early interaction (2%), triggering algorithmic momentum decay. Findings confirm a perfect correlation (r = 1.00) between format stability and algorithmic reach. Implication and Recommendation: These findings emphasize that sustainable organic growth is determined by the synchronization between predictable upload patterns and the machine-learning system’s real-time evaluation of interaction efficiency. It is recommended that beginner creators prioritize the "three-second hook" to capture initial attention and maintain strict discipline in narrative and visual formats to build algorithmic credibility.
IMPLEMENTATION OF INFORMATION SYSTEM USING THE ANDROID-BASED K-MEANS CLUSTERING ALGORITHM TO DETERMINE GRADUATION SCORES AT SMK NEGERI 3 METRO azhari, amalyanda; Ratnasari, Mei; Sasmito, Angger; Saputra, Dian; Khan, Naqib Ullah
Asia Information System Journal Vol. 4 No. 2 (2025): Asia Information System Journal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/5fn10c18

Abstract

This study proposes the implementation of the K-Means clustering algorithm to analyze and classify student graduation scores at SMK Negeri 3 Metro in order to support academic decision-making and improve information management. The dataset consists of academic records of students from grades X to XII, including theoretical scores, practical scores, attendance rates, and final achievement scores. Prior to clustering, the dataset is subjected to preprocessing procedures, including data cleaning, attribute transformation, and min-max normalization to ensure proportional scaling among variables. The clustering process is performed using RapidMiner and configured into three clusters representing categories of academic performance. The experimental results indicate that the K-Means algorithm effectively identifies structured patterns in the distribution of graduation scores, enabling the institution to map student achievement levels objectively. To operationalize the analytical results, the clustering model is integrated into a web/Android-based information system that facilitates real-time access to graduation information for teachers, administrators, and students. The implementation of the system contributes to improved efficiency in academic data management, faster information dissemination, and enhanced transparency in graduation scores. The findings demonstrate that the application of data mining techniques, particularly K-Means clustering, provides a reliable framework for academic analytics and decision support in educational information systems, with potential scalability for broader institutional adoption.

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