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Journal of Artificial Intelligence and Digital Economy
Published by PT. Antis International Publisher
ISSN : -     EISSN : 30321077     DOI : https://doi.org/10.61796/jaide
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Journal of Artificial Intelligence and Digital Economy is part of the Discover journal series committed to providing a streamlined submission process, rapid review and publication, and a high level of author service at every stage. It is an open-access, community-focused journal publishing research covering all aspects of artificial intelligence in theory and application.
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Articles 200 Documents
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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.
IMPLEMENTATION OF A WEB-BASED SALES INFORMATION SYSTEM FOR COMPUTER NETWORKING EQUIPMENT AT MY RISE SIDOARJO Hafid Pradana; Rohman Dijaya; Mochamad Alfan Rosid; Irwan Alnarus Kautsar
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1557

Abstract

Objective: The rapid advancement of information technology has highlighted the need for efficient systems in sales data management. This study aims to develop and implement a web-based sales information system to enhance operational efficiency and customer service quality in My Rise, a store in Sidoarjo specializing in computer network equipment. Method: The research employed qualitative methods, including interviews to gather system requirements from business operators and direct observation to analyze the current sales process. The system was designed with an integrated approach to manage sales data, inventory, and transactions in real-time. Results: The implementation of the system resulted in significant improvements in the speed and accuracy of sales processes, with enhanced customer access to information and services. Novelty: This study introduces a practical web-based solution for small and medium-sized enterprises in the computer network equipment sector, addressing common issues such as data entry errors and delays in service, thus contributing to the digital transformation of the business.
DESIGN AND IMPLEMENTATION OF A DIGITAL MARKETING INFORMATION SYSTEM FOR KOHAN_YA (HANS JAYA GARMENT SME) Ilham Rizky Almahdi; Hindarto Hindarto; Sumarno Sumarno; Hamzah Setiawan
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1558

Abstract

Objective: This study aims to design and implement a web-based information system for KSI Hansjaya, a garment production business, to serve as both an information dissemination medium and an efficient online promotional tool. Method: The system development process followed the Software Development Life Cycle (SDLC) using the Waterfall model, which includes stages such as requirements analysis, system design, implementation, testing, and maintenance. The system accommodates two user categories: administrators and general users. Results: The system features were tested and evaluated through functionality testing and a questionnaire distributed to 20 respondents. The results showed that 70% of respondents strongly agreed, and 30% agreed that the system is feasible as a digital promotion medium, with all features functioning optimally according to user requirements. Novelty: This web-based system offers a responsive single-page website interface that allows administrators to manage product categories, details, and company contact information, while general users can access product information, ordering guidelines, and contact details. The developed website significantly supports KSI Hansjaya’s promotional activities and contributes positively to the business’s digital growth.
APPLICATION OF FUZZY LOGIC IN PREDICTING GROCERY STORE REVENUE Hamzah Dwi Kusuma; Hindarto Hindarto; Arief Senja Fitrani; Azmuri Wahyu Azinar
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1559

Abstract

Objective: This study aims to predict grocery store income accurately using the Mamdani fuzzy logic method to address challenges caused by price fluctuations and market uncertainty in retail operations. Method: Data were collected through direct observation at a grocery store in Sidoarjo over one month, including variables such as the number of items sold, total price, and operational costs. Each variable was classified into fuzzy sets using triangular and shoulder-shaped membership functions. The fuzzy inference system consisted of 27 if–then rules, with output values determined through the Weighted Average defuzzification method. Results: Based on input data of 1,004 units sold, a total price of Rp. 14,124,500, and operational costs of Rp. 4,500,000, the system successfully predicted an income of Rp. 10,000,000. Evaluation using Mean Absolute Percentage Error (MAPE) indicated an error rate of 0%, signifying exceptional predictive accuracy. Novelty: The study demonstrates that fuzzy logic can serve as a highly effective decision-support tool for income prediction in small-scale retail businesses, providing a reliable framework for managing financial uncertainty.
WEB-BASED SALE INFORMATION SYSTEM FOR POLLUX SHOES AT CV NOTO PUTRA Zsendy Ernosa; Sumarno Sumarno; Cindy Taurusta; Suprianto Suprianto
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1560

Abstract

Objective: This study aims to analyze the digital transformation strategy of CV Noto Putra, a Surabaya-based footwear manufacturing company, in strengthening its competitiveness through the adoption of e-commerce platforms and legal compliance in online transactions. Method: The research applies a descriptive qualitative approach focusing on company practices related to technology adoption, marketing strategies, and adherence to Indonesia’s Civil Code in conducting digital business operations. Results: Findings indicate that the integration of e-commerce has enhanced operational efficiency, expanded market reach, and improved customer engagement. Furthermore, compliance with legal frameworks reinforces consumer trust and transaction transparency. Novelty: This study highlights how traditional manufacturing companies, such as CV Noto Putra, can leverage digital innovation combined with legal integrity to sustain competitiveness and achieve long-term business growth in Indonesia’s evolving footwear industry.
DESIGN OF POINT OF SALE INFORMATION SYSTEM CASE STUDY: MAJU JAYA GROCERY STORE Achmad Amirudin; Rohman Dijaya; Hamzah Setiawan; Arif Senja Fitrani
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1561

Abstract

Objective: This study aims to design and implement a Point of Sale (POS) system as a technological solution to enhance sales transaction efficiency, inventory management, and customer data processing in retail and service-oriented businesses. Method: The research adopts a software engineering approach, encompassing user requirements analysis, interface design, and system testing to ensure the application meets user and operational needs. The system integrates payment processing, receipt generation, and real-time sales recording within a unified platform, while also supporting cloud connectivity and cashless transactions to align with modern digital practices. Results: The implementation of the POS system demonstrated improvements in service speed, accuracy of transaction recording, and overall customer satisfaction. Novelty: This study provides an applicable model for developing integrated, cloud-connected POS systems, emphasizing the role of digital transformation in enhancing business performance and operational reliability in the retail sector.
MARKETING STRATEGY OF UMRAH BANNER PRODUCTS IN INCREASING THE NUMBER OF PROSPECTIVE PILGRIMAGES DURING COVID 19 AT SAMIRA TRAVEL SIDOARJO Nur Iza Faizah; Masruchin Masruchin
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1562

Abstract

Objective: This study aims to evaluate the marketing strategies implemented by PT. Samira Utama Wisata (Samira Travel) to increase the sales of its Talangan Umrah product during the Covid-19 pandemic. Background: The global pandemic led to the temporary suspension of Umrah pilgrimages in mid-2020, resulting in a sharp decline in demand for travel services. In response, Samira Travel introduced an innovative financing product—Talangan Umrah—designed to assist customers in fulfilling their religious pilgrimage aspirations amid financial constraints. Method: The research employs a descriptive qualitative approach, with data obtained through interviews and documentation at the Samira Travel branch office in Sidoarjo. Findings: The results indicate that Samira Travel effectively utilized digital marketing strategies, leveraging social media platforms and online promotional campaigns to maintain visibility and attract customer interest. Additionally, the company enhanced communication with potential pilgrims through multiple channels, including telephone, WhatsApp, and the official company website. Conclusion: The study concludes that the integration of digital marketing and direct communication strategies played a crucial role in sustaining customer engagement and promoting the Talangan Umrah product during the pandemic, offering valuable insights for marketing resilience in times of crisis.
MIDDLEWARE PAYMENT GATEWAY ON THE DIGITAL CROWDFUNDING PLATFORM M. Bima Surya; Irwan Alnarus Kautsar; Yulian Findawati; Suhendro Busono
Journal of Artificial Intelligence and Digital Economy Vol. 3 No. 1 (2026): 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.v3i1.1563

Abstract

Objective: This study aims to develop and implement a microservices-based payment gateway middleware integrated with web services to enhance transaction efficiency and reliability on crowdfunding platforms. Background: In the digital era, the demand for fast, secure, and efficient transaction systems has become increasingly critical, particularly in platforms handling large volumes of financial transactions. Traditional monolithic architectures often struggle to maintain scalability and flexibility, leading to potential bottlenecks and security risks. Method: The system was designed using a microservices architecture, allowing each payment-related process—such as authentication, transaction validation, and notification handling—to operate independently yet remain interconnected through APIs. Integration with web services ensures compatibility with various payment providers and crowdfunding systems. Findings: The implementation results demonstrate that the proposed middleware improves transaction processing speed, scalability, and fault tolerance compared to traditional models. Conclusion: The study concludes that adopting a microservices-based payment gateway middleware provides a sustainable solution for high-volume digital transactions, supporting the scalability, flexibility, and security required by modern crowdfunding ecosystems.
THE ROLE OF GENERATIVE ARTIFICIAL INTELLIGENCE TECHNIQUES IN PREDICTING FINANCIAL VOLATILITY: AN APPLIED STUDY ON EMERGING MARKETS Bidaa Mohammed Ahmed
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 11 (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.v2i11.1573

Abstract

Objective: This paper examines the perception and implementation of generative artificial intelligence (AI) in the context of financial forecasting on emerging markets. Method: The research uses a structured survey that was emailed to 137 financial analysts and professionals to examine their familiarity with the latest AI technologies, their application in the field, and the obstacles that they encounter in the implementation of these models. Results: The findings show that an enormous proportion of the population feels that generative models, including GANs, can provide more valid predictions than conventional ones. Approximately 65 percent of the respondents affirm that these models render it significantly more correct to predict, and an additional 75 percent of those who responded affirm the necessity to utilize these models in order to execute contemporary financial analysis. A lack of data (68%), poor infrastructure (50%), and a lack of skills (45%) are also pointed out as some of the key issues in the study. The positive relationship between the talents of the respondents at eminent AI and their desires to employ sophisticated modelling techniques is statistically significant. The results emphasize the necessity of the construction of a strong data collection infrastructure and enhancement of technological infrastructure, and the development of human capabilities through the specialization of training. Novelty: This research provides important lessons on the opportunities and challenges of introducing generative AI models into the financial decision-making processes in emerging economies and some key areas for policy and industry intervention to optimise their potential advantages.
INDONESIA'S MINING PRODUCTS TRADE POLICY, DOWNSTREAMING AND CONTROVERSIAL INTERNATIONAL TRADE Syahrudi; Abdul Azim Wahbi
Journal of Artificial Intelligence and Digital Economy Vol. 2 No. 11 (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.v2i11.1578

Abstract

Objective: This study investigates the impact of Indonesia’s trade policy on mining products, emphasizing the downstream processing strategy and its implications within international trade dynamics. Method: Using a qualitative approach combining policy analysis, literature review, and expert interviews, the research examines how Indonesia’s efforts to promote value addition through downstream processing have influenced trade relations and compliance with global trade norms. Results: The findings reveal that while the policy enhances domestic economic benefits and industrial competitiveness, it also generates tensions with several trading partners, sparking debates on trade fairness, market access, and the sovereignty of natural resource utilization. These controversies highlight the complex interplay between national economic interests and international trade obligations. Novelty: This study provides a comprehensive perspective on Indonesia’s downstream policy as a case of resource-based industrialization in a globalized economy, offering new insights into balancing national development goals with international trade commitments through cooperative and sustainable policy frameworks.

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