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Journal of Emerging Information Systems and Business Intelligence (JEISBI)
Published by Universitas Negeri Surabaya
ISSN : -     EISSN : 27743993     DOI : 10.26740/jeisbi
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Library & Information Science
Journal of Emerging Information Systems and Business Intelligence (JEISBI) aims to provide scholarly literature focused on studies and research in the fields of Information Systems (IS) and Business Intelligence (BI). This journal also includes public reviews on the development of theories, methods, and applications relevant to these topics. All published works are presented exclusively in English to reach a global audience of readers and researchers. The journal’s scope includes but is not limited to the following fields: Data Mining Generative Artificial Intelligence Big Data Analytics Business Intelligence Enterprise Architecture UI/UX Business Process Management Enterprise System System Development Decision Support System IS/IT Strategy and Planning IT Investment and Productivity IT Project Governance IS Business Value Audit SI/TI Cybersecurity and Risk Management IS/IT Operations and Service Management IT Ethics Organizational and Human Behavior Technology Digital Sociology
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 343 Documents
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Bitcoin Transaction Multivariate Forecasting Analysis Deep Learning Model Walk Forward Validation Muhammad Dafi Bagas; Wiyli Yustanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.77536

Abstract

The volatile and non-linear movement of Bitcoin prices makes price prediction a complex problem in time series analysis. This study aims to compare the performance of several deep learning models, namely Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Transformer, and Temporal Fusion Transformer (TFT), in predicting Bitcoin closing prices based on multivariate data. The dataset consists of daily historical data from 2020 to 2025, including Open, High, Low, Close, and Volume features. Model evaluation was conducted using the Walk Forward Validation (WFV) approach with 5 folds and was compared with the Cross Validation (CV) method. Three data split scenarios were applied: 70:30, 80:20, and 90:10. Model performance was measured using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), Symmetric MAPE (sMAPE), and the coefficient of determination (R²). Furthermore, the Wilcoxon Signed-Rank Test was employed to analyze the statistical significance of performance differences between validation methods. The results indicate that the GRU model under the 90:10 data split scenario achieved the best performance, with a median MAE of 0.0116 and RMSE of 0.0179, along with an R² value of 0.8622. This model demonstrated lower prediction errors and greater stability compared to the other models. Meanwhile, the Wilcoxon test results showed no significant difference between Walk Forward Validation and Cross Validation (p-value > 0.05), indicating that both validation methods produce statistically equivalent performance. Based on these findings, the GRU model is recommended as the most optimal model for Bitcoin price prediction under the experimental configuration used in this study.
Engagement Patterns of Educational Content on TikTok Amalia Putri; Wiyli Yustanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78027

Abstract

The rapid development of digital technology has contributed to the increasing use of social media, particularly TikTok, which functions not only as an entertainment platform but also as a medium for distributing educational content through hashtags such as #edukasi. However, not all educational content generates the same level of engagement, making further analysis necessary to understand the interaction patterns formed within the platform. This study aims to analyze engagement patterns of educational content on TikTok and identify the dominant hashtags appearing alongside #edukasi within each cluster. The methods employed in this study include K-Means Clustering to group content based on engagement characteristics and Social Network Analysis (SNA) to examine relationships among hashtags. The findings indicate the formation of two clusters with different engagement characteristics, namely high-engagement and low-engagement clusters. Network analysis reveals that the low-engagement cluster forms several communities associated with topics such as facts, health, and children’s education, while the high-engagement cluster is dominated by hashtags related to educational toys, such as #mainananak and #mainanedukasi. These results demonstrate that the combination of clustering methods and social network analysis is effective in identifying engagement patterns and hashtag relationships in educational TikTok content.
Public Opinion on MyTelkomsel Using DeLone and McLean Model on X Bagas Setya Wicaksono; Cendra Devayana Putra; I Kadek Dwi Nuryana; Monica Cinthya
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78043

Abstract

The MyTelkomsel application is a digital service used by Telkomsel customers to access telecommunications information and services. The high number of users is accompanied by the emergence of various user opinions and complaints expressed through social media. This study aims to analyze user satisfaction with the MyTelkomsel application based on public opinions on the X (Twitter) platform using the DeLone and McLean Information Systems Success Model. The research data consist of 1,500 Indonesian-language tweets collected through a crawling process. The data then underwent a text preprocessing stage to improve analysis quality. Sentiment analysis was conducted using the RoBERTa model to classify user opinions into positive, neutral, and negative sentiments. Subsequently, each tweet was labeled into six dimensions of the DeLone and McLean model, namely System Quality, Information Quality, Service Quality, Use, User Satisfaction, and Net Benefits. Sentiment scores were used as quantitative values for each dimension. The relationships among variables were analyzed using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method. The results indicate that System Quality and Information Quality significantly influence User Satisfaction, while Service Quality shows a lower level of influence. This study is expected to provide academic contributions to the application of the DeLone and McLean model based on social media data and offer practical insights for the development of the MyTelkomsel application in improving service quality and user experience. Keywords : MyTelkomsel, Sentiment Analysis, Social Media, DeLone and McLean, User Satisfaction, SEM-PLS
Importance Performance Analysis (IPA) of Google Reviews Sentiments Based on SERVQUAL Dimension for Public Health Center Service in Surabaya Octania Sriwahyuni; Wiyli Yustanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78201

Abstract

Google Reviews can serve as a digital mirror to gauge how the public evaluates the services of community health centers. This study focuses on analyzing the sentiment of Google Reviews for community health centers in Surabaya, mapping reviews into the SERVQUAL dimensions using Gap Analysis and Importance–Performance Analysis (IPA), and identifying the most influential keywords via TF-IDF within a GUI system. This study applies the Knowledge Discovery in Databases (KDD) workflow. Data was obtained by scraping reviews from 63 community health centers in Surabaya. Subsequently, sentiment was determined based on user ratings, then classified into the five SERVQUAL dimensions, and analyzed using the GAP analysis and Importance-Performance Analysis (IPA). The results indicate that positive public perceptions predominate. However, all dimensions still show negative scores, suggesting that service quality has not yet fully met user expectations. In the IPA analysis, Responsiveness, Assurance, and Empathy are categorized in Quadrant II as aspects that require maintenance, while Tangibles and Reliability fall into Quadrant III as low-priority aspects. Notably, no dimension is in Quadrant I. Additionally, TF-IDF successfully captures keywords such as “queue,” “long,” “friendly,” “clean,” and “procedure,” and has been successfully implemented in the GUI for automatic classification. Building on these results, this study confirms that digital reviews combined with sentiment analysis, SERVQUAL, and Importance-Performance Analysis (IPA) can serve as a more objective, practical, and sustainable evaluation tool for Public health center services.
Development of a Point of Sale (POS) System for the Digitalization of Sales Transaction Recording Based on AI (Case Study: PT XYZ) Erin Limanda Afriana; Dwi Fatrianto Suyatno
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78203

Abstract

Manual sales transaction management remains a common challenge for many small and medium-sized enterprises (SMEs), including PT XYZ, which still relies on physical receipts and handwritten recapitulation to record sales transactions. This condition increases the risk of recording errors, delays in data recapitulation, and difficulties in generating structured sales reports. This study aims to develop a web-based Point of Sale (POS) system integrated with an AI-based chatbot through Telegram and n8n workflow automation to support the digitalization of sales transaction records at PT XYZ. The system was developed using the Rapid Application Development (RAD) method, while data were collected through literature studies, observations, and interviews with the business owner. The developed system is capable of digitizing historical transactions through receipt data extraction using an AI chatbot while simultaneously supporting real-time transaction recording through a web-based POS system integrated into a centralized database. The black-box testing results indicate that all main system features operated according to user requirements, including product management, transaction recording, receipt digitization, and sales report generation. The implementation of the system improved transaction recording efficiency, minimized the risk of data loss, and produced more structured and accessible sales data. The findings demonstrate that the integration of AI chatbots and POS systems can serve as an effective sales transaction digitalization solution for SMEs.
Development of an AI-Based Customer Service Information System for MSME XYZ Izmi Fitriani; Dwi Fatrianto Suyatno
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78204

Abstract

This research aims to develop an Artificial Intelligence (AI)-based customer service information system for MSME XYZ. The study addresses problems in manual customer service processes, including slow response times, repetitive customer inquiries, and unstructured order management that affect operational efficiency and customer satisfaction. The study applies the Research and Development (R&D) method using the Rapid Application Development (RAD) approach. The developed system is a WhatsApp-based AI chatbot integrated with the n8n automation platform, supported by a PostgreSQL database and a web-based dashboard using Budibase. The system provides automated real-time responses, manages product information requests, processes customer orders, and handles customer complaints. System testing was conducted using the Black-Box Testing method to evaluate system functionality. The results indicate that all systems feature operate according to the specified requirements. The implementation of the AI-based chatbot system improves customer service efficiency, reduces manual workload, accelerates response time, and supports digital transformation for MSMEs.
Decision Support System for IT Equipment Procurement Prioritization Using WASPAS Daniel Axel Bagus Putranto; Dwi Fatrianto Suyatno
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78219

Abstract

Determining the priority of IT equipment procurement is a critical process in supporting organizational operational effectiveness. However, procurement decision-making at PT XYZ was previously conducted manually using spreadsheet-based recording, resulting in subjective assessments, time-consuming discussions, and inconsistent prioritization outcomes. This study proposes a web-based Decision Support System utilizing the Weighted Aggregated Sum Product Assessment (WASPAS) method to support objective and data-driven IT procurement prioritization. The proposed system evaluates procurement alternatives based on five criteria: equipment importance, remaining stock, usage frequency, equipment age, and equipment price. The WASPAS method was selected because it combines the advantages of the Weighted Sum Model (WSM) and Weighted Product Model (WPM), improving ranking consistency and decision accuracy. System development was conducted using the Agile methodology to ensure iterative and adaptive development according to user requirements. The research results indicate that the developed system successfully generates automatic procurement priority rankings based on predefined criteria weights. In addition, the system provides reporting and analysis history features that support faster and more transparent decision-making processes. Black Box Testing results demonstrate that all system functionalities operate successfully according to user requirements. Therefore, the proposed system improves efficiency, accuracy, and objectivity in IT procurement decision-making processes.
User Acceptance of the SpeedCash Digital Wallet Using TAM Laura Naily Tsabita; Dwi Fatrianto Suyatno
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78260

Abstract

The rapid development of financial technology has increased the use of digital wallets as a practical and efficient payment method. One of the developing digital wallet applications in Indonesia is SpeedCash. This study aims to analyze user acceptance of the SpeedCash digital wallet application using the Technology Acceptance Model (TAM). The variables used in this study include perceived ease of use, perceived usefulness, attitude toward using, and behavioral intention to use. This research employed a quantitative approach by distributing questionnaires to SpeedCash users. The collected data were analyzed using the Structural Equation Modeling-Partial Least Square (SEM-PLS) method. The results indicate that perceived ease of use has a positive effect on perceived usefulness and attitude toward using. In addition, perceived usefulness significantly influences users’ attitudes toward using the application. The variable attitude toward using also has a significant effect on behavioral intention to use the SpeedCash application. These findings indicate that ease of use and perceived benefits are the main factors influencing user acceptance of the SpeedCash digital wallet. This study is expected to provide insights for application developers in improving service quality and user experience to increase sustainable application usage.
Sentiment Analysis And UTAUT2 Classification On Maxim Application User Reviews Using IndoBERT And Zero-Shot Hilal Hindi Saputra; Cendra Devayana Putra; I Kadek Dwi Nuryana; Monica Cinthya
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78304

Abstract

The rapid growth of ride-hailing services has intensified competition, making user feedback on digital platforms a critical asset for service improvement. This study addresses the challenge of managing and extracting actionable insights from large volumes of unstructured user reviews on the Google Play Store for the Maxim application. To overcome this, a comprehensive text-mining framework is proposed, integrating sentiment analysis and technology acceptance modeling. A dataset of 2.000 Indonesian-language user reviews from July to September 2025 was retrieved via web scraping. Data preprocessing was executed using case folding, filtering, and normalization. Subsequently, sentiment classification was performed using the IndoBERT model, while the mapping of user text to the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework was automated using a Zero-Shot Classification approach. Finally, Structural Equation Modeling–Partial Least Squares (SEM-PLS) via SmartPLS 4.0 was utilized to test the structural hypotheses. The analytical findings reveal that negative sentiments slightly dominate the dataset (48.05%), heavily driven by system stability and sudden fare adjustments. Furthermore, the structural model proves that behavioral intention, effort expectancy, facilitating conditions, habit, performance expectancy, price value, and social influence exert positive and significant effects on adoption, whereas hedonic motivation exhibits no significant influence.
Business Process Reengineering of Motor Vehicle Insurance Claims Using the Business Process Reengineering Method Satrya Hidayat; Amrul Hidayat; Achmad Zidane Fatih Ramadhan; Keysha Azzahra Putri; Tasyaufy Isma Nur Aulia; Raulia Riski
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78314

Abstract

In the current era of digital transformation, motor vehicle insurance claim services can be rendered significantly more effective. However, PT Asuransi Umum Bumiputera Muda 1967 (BUMIDA) encounters challenges with manual vehicle surveys, which lead to prolonged queues in claim services. To address this issue, enhancing the business processes associated with the provision of motor vehicle insurance claim services is imperative. The objective of this research is to analyze the motor vehicle insurance claim process utilizing the Business Process Reengineering (BPR) method and to propose an optimized process. The methodology employed in this study encompasses analyzing the current (As-Is) business process, formulating the problem, designing the proposed (To-Be) business process, and ultimately executing a process simulation using BPMN 2.0 within the Visual Paradigm application. The primary finding indicates that the implementation of digital surveys integrated with video calling technology can significantly enhance the business process and eliminate bottlenecks within the vehicle surveying procedure. The newly proposed process and subsequent improvements are anticipated to substantially increase the efficiency of the motor vehicle insurance claim services provided by the company.

Page 34 of 35 | Total Record : 343

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