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All Journal Journal of Artificial Intelligence and Digital Economy
Ika Ratna Indra Astutik
Muhammadiyah University of Sidoarjo, Indonesia

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IMPLEMENTATION OF THE AGILE METHODOLOGY IN A DIET AND BULKING MOBILE APPLICATION USING THE FLUTTER FRAMEWORK Rahmat Syahrur Ramadhan; Nuril Lutvi Azizah; Ika Ratna Indra Astutik; Sumarno Sumarno
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 4 (2025): Journal of Artificial Intelligence and Digital Economy
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jaide.v2i4.1516

Abstract

Objective: This study aims to develop and evaluate the FitLaksana mobile application as a digital solution for improving dietary management and physical activity to address rising health issues such as obesity and metabolic disorders. Method: The application was developed using the Flutter framework and Firebase database, following the Agile methodology through stages of system analysis, user interface design, feature implementation, and Black Box testing. User evaluations were conducted using a Likert scale to assess satisfaction levels regarding functionality, usability, and reliability. Results: All features of the FitLaksana application operated effectively, with users reporting high satisfaction levels—50% rated the app “Agree” (score 4) and 65.38% rated “Strongly Agree” (score 5). The application was praised for its user-friendly interface, stability, and usefulness in supporting healthy lifestyle management. Novelty: This study introduces a comprehensive, user-centered mobile health application that integrates nutritional guidance and exercise planning, demonstrating the effective application of Agile-based development in creating practical digital health tools for self-managed wellness.
DESIGN OF A CLOTHING SALES INFORMATION SYSTEM BASED ON JAVA NETBEANS USING THE WATERFALL METHOD Achmad Yudha Pratama; Ika Ratna Indra Astutik
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 6 (2025): Journal of Artificial Intelligence and Digital Economy
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jaide.v2i6.1534

Abstract

Objective: This study aims to develop an efficient and integrated information system to optimize the management of clothing sales within Micro, Small, and Medium Enterprises (MSMEs) in the retail sector, particularly those still operating with manual processes that are time-consuming and prone to errors. Method: The research employs the Waterfall model as a systematic software development approach, encompassing stages of requirements analysis, system design, implementation, testing, and maintenance. The system was developed using Java programming language with NetBeans IDE as the development environment and MySQL as the database management system. Results: The resulting Java-based Clothing Sales Information System successfully automates key business processes, including inventory management, transaction recording, and sales reporting, thereby improving data accuracy and operational efficiency. Novelty: The study contributes by presenting a practical and scalable information system model tailored to the needs of MSMEs in the retail clothing industry, demonstrating how digital transformation can enhance competitiveness and streamline business management in the era of globalization.
DESIGN OF A WEBSITE-BASED FRUIT SEED SALES INFORMATION SYSTEM Muhammad Nurhidayat; Arif Senja Fitrani; Ika Ratna Indra Astutik; Sumarno Sumarno
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 7 (2025): Journal of Artificial Intelligence and Digital Economy
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jaide.v2i7.1535

Abstract

Objective: This study aims to evaluate the effectiveness of the “Design of a Website-Based Fruit Seed Information System” in Tulangan District, Sidoarjo Regency, as a technological innovation to enhance agricultural management within the context of globalization and the Industrial Revolution 4.0. Method: The research employed a developmental and testing approach, where 10 users participated in system trials to assess usability, response time, and data accuracy. The system utilized a MySQL database and was evaluated based on service speed, data input success, and user satisfaction. Results: The findings revealed that the average service time was reduced to 5 minutes—significantly faster than manual transactions—with 80% of users successfully entering data and 90% expressing satisfaction with the system’s ease of use. The average seller response time ranged between 2–5 minutes, and all transactions were encrypted to ensure data security. Novelty: This study presents an innovative integration of digital technology into the agricultural sector, demonstrating how a web-based system can streamline seed sales, promote digital literacy among farmers, and improve agricultural productivity through efficient information management.
APPLICATION OF APRIORI DATA MINING METHOD FOR PURCHASING PATTERN ANALYSIS AT UB MART MINIMARKET Ihsan Ferdy Nurfauzy; Ade Eviyanti; Hamzah Setiawan; Ika Ratna Indra Astutik
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 12 (2025): Journal of Artificial Intelligence and Digital Economy
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jaide.v2i12.1556

Abstract

Objective: The Apriori Algorithm method can be used to see the pattern of purchasing goods, such as what happens in the retail industry, including UB Mart minimarkets. UB Mart is one of the minimarkets that sells daily necessities and is often faced with challenges in increasing sales and revenue. Considering that there is quite a lot of competition in this minimarket, UB Mart is required to be able to think of a marketing strategy so that it is not inferior to competitors and one of them is by analyzing purchase patterns with a priori algorithm. It is hoped that by conducting this research it can find out the purchase pattern from UB Mart transaction data, so that transaction data that was initially just a pile of sales reports can turn into the right business strategy. Method: The Apriori Algorithm method can be used to see the pattern of purchasing goods by analyzing purchase patterns with a priori algorithm. Results: The results of this study resulted in 4 association rules from sales transaction data in 2024 in January and February. For example if someone buys a 600 ml retail Tras, they are likely to also buy Sakha with a confidence level of 23.89%. And the results of this research can provide business strategy advice to minimarket management for stock strategies, placement of goods to bundling promos. Novelty: Transaction data that was initially just a pile of sales reports can turn into the right business strategy through the application of the a priori algorithm to reveal purchase patterns in UB Mart.
Co-Authors Achmad Yudha Pratama Ade Eviyanti Arif Senja Fitrani Hamzah Setiawan Ihsan Ferdy Nurfauzy Muhammad Nurhidayat Nuril Lutvi Azizah Rahmat Syahrur Ramadhan Sumarno Sumarno Sumarno Sumarno