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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 6 Documents
 1 
Search results for , issue "Vol. 6 No. 1 (2025)" : 6 Documents clear
Rendering Performance Analysis of Astro JS, Next JS, Nuxt JS, and SvelteKit Frameworks Using Google Lighthouse, PageSpeed Insight, and JMeter: Rendering Performance Analysis of Astro JS, Next JS, Nuxt JS, and SvelteKit Frameworks Using Google Lighthouse, PageSpeed Insight, and JMeter Ahmad Jourji Zaidan; Dwi Fatrianto Suyatno
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64283

Abstract

The development and popularity of modern technology encourage innovation in developing web applications to increase loading speed and retain users. This research analyzes the performance of websites that use Astro JS, Next JS, Nuxt JS, and SvelteKit frameworks using the SSR (Server Side Rendering) technique. The advantage of the SSR technique is that it can improve website performance, SEO (Search Engine Optimization) optimization, and user experience. The tools used in this research are Google Lighthouse, PageSpeed Insight, and JMeter. The metrics measured in Google Lighthouse and PageSpeed Insight testing are FCP (First Contentful Paint), TBT (Total Blocking Time), SI (Speed Index), LCP (Large Contentful Paint), and CLS (Cumulative Layout Shift). While JMeter testing, the metrics measured are Response Time (Min, Max, Average), Error Rate, and Throughput. The development method used is the XP (Extreme Programming) method. The results of this study show Astro JS has superior performance in most Web Vitals metrics, followed by Next JS which shows superiority in several metrics. Nuxt JS and SvelteKit each only excelled in one Web Vitals metric. In stability and reliability of the system testing using JMeter, Nuxt JS showed the best performance by excelling in the response time, error rate, and throughput metrics. SvelteKit also performed well with dominance in several stability metrics, while Astro JS and Next JS only excelled in a small number of them. This research was conducted to provide insight for developers in choosing the right framework based on their needs.
Implementation of the Support Vector Machine (SVM) Algorithm in Predicting Transaction Cancellations at Shopee E-commerce: Implementasi Algoritma Support Vector Machine (SVM) Dalam Memprediksi Pembatalan Transaksi Pada E-commerce Shopee Maulidia, Ridhotul; Yustanti, Wiyli
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64414

Abstract

In the digital era, shopping through e-commerce such as Shopee has become increasingly popular. However, transaction cancellation is still an obstacle that causes financial losses for sellers. This research aims to predict transaction cancellation on the Shopee platform using the Support Vector Machine (SVM) algorithm, which is expected to help sellers reduce the risk of loss. The data used comes from the transaction history of Shopee store nafystore.id and is processed using the CRISP-DM method, including business understanding, data preparation, modeling, and deployment. The data preparation process includes cleaning, encoding, normalization, and dimension reduction using Principal Component Analysis (PCA), as well as handling data imbalance with SMOTE. Model testing was conducted using K-Fold Cross-Validation at 3, 5, and 10 folds with different SVM kernels, where the linear kernel showed the best performance with 95.57% accuracy, 95.96% precision, 95.57% recall, and 95.58% F1-Score. The implementation of a web-based system is done using Streamlit to make it easier to use for sellers. The results of this research provide benefits for sellers in identifying cancellation factors, such as Total Payment and Estimated Shipping Fee Deductions. This research not only enriches the application of SVM algorithm in e-commerce analysis, but also provides a reference for other e-commerce platforms to improve transaction efficiency and customer satisfaction.
WEB-BASED EMPLOYEE RECRUITMENT DECISION SUPPORT SYSTEM USING THE FUZZY ANALYTICAL HIERARCHY PROCESS METHOD (CASE STUDY PT. AGROFARM NUSA RAYA) Setia Mahardika, Vicky Pratama; Sisephaputra, Bonda
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64415

Abstract

Employees or employees are part the most important thing for the company. So therefore, When recruiting, it must be done carefully maximum in order to obtain quality employees, quality and according to needs. In the process recruitment of new employees, PT. Agrofarm Nusa Raya still using the manual method and not yet apply methods for decision making. A large number of prospective employees make HRD find it difficult to select prospective employees who match the criteria for acceptance in company. To overcome this problem So a Decision Support System is needed web-based by applying the Fuzzy method Analytical Hierarchy Process (Fuzzy AHP). Criteria used for the employee recruitment process namely interviews, psychological tests, Islamic knowledge, work experience, education and certificates. Results The end of the research shows that the application Employee recruitment decision support system can be developed using the Extreme method Programming (XP). In the calculation results applying the Fuzzy AHP method obtained results that the highest score is 1,660 with the name Akbar,while the lowest value is -1.810 with the name Priest. With the existence of a Decision Support System Those who implement Fuzzy AHP will make it easier HRD work in the decision making process related to the final results of employee recruitment.
Comparison Of Web Load Speed Between Babel Transpiler and SWC On Website-Based Applications Rangga Prasetya, Rangga Prasetya; Sujatmiko, Bambang
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64610

Abstract

Transpilers play an important role in software development by translating code from one programming language to another, allowing developers to take advantage of modern features and capabilities without having to change the entire project. For example, by using a transpiler like Babel, developers can write the latest JavaScript code that remains compatible with older browsers, similar to translating a book into multiple languages ​​to make it accessible to a wider audience. Babel is the most commonly used transpiler. On the other hand, there is SWC which is a new transpiler that is claimed to be faster than Babel. This study aims to determine the difference in the speed of the Babel and SWC transpilers. The data for this study were taken from several pages using Google Lighthouse. The data were analyzed using a parametric test, namely the paired sample t-test. The results of the study showed that SWC had a significant difference in speed compared to Babel in the First Contenfulpaint (FCP) and Speed ​​​​Index (SI) indicators. Babel is superior in Total Blocking Time (TBT). While in the Largest Contenfulpaint (LCP), Babel is significantly superior to SWC. This shows that SWC is faster than Babel transpiler in web load speed because in the speed indicators, namely FCP and SI, SWC is significantly superior.
IT Risk Management Planning on Avesina Application RSUD Waluyo Jati Kab. Probolinggo Using OCTAVE Allegro: IT Risk Management Planning on Avesina Application RSUD Waluyo Jati Kab. Probolinggo Using OCTAVE Allegro Jamil, Safaru Khoiron; Ghea Sekar Palupi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64629

Abstract

The application of information technology at RSUD Waluyo Jati Kraksan can pose a risk. The example of information technology risks that have occurred is the occurrence of additional working hours caused by system errors in the Avesina application related to room procurement. The purpose of this study is to determine the IT risks that arise from the implementation of the Avesina application, and provide the necessary mitigation in managing these risks. The method used in this research is OCTAVE Allegro. Before determining the risk, asset profiling and wadan of the asset are carried out. The risks arising from the implementation of the avesina application are data input errors, application hacking, applications can be easily accessed by unauthorized people, and account sharing. There are several stages used to determine the mitigation approach. Of the four risks, it was found that only two risks needed to be mitigated. The mitigation provided focuses on the asset containers that need to be controlled, namely the SIM RS Unit and management. The mitigation includes procuring a renewable security system, procuring a 2-factor authentication system, and monitoring compliance with information technology.
Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model: Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model Suhartono, Darell Timotius; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64722

Abstract

The widespread use of software to enhance organizational efficiency makes software development essential. The Airport Authority Region III Office uses MV5PAS software for operational activities, aiming to improve public services. Ensuring software quality is crucial for optimal performance, which this study evaluates using the FURPS model. This model assesses software based on five characteristics: functionality, usability, reliability, performance, and supportability.The study employs a mixed-method evaluation approach. Functionality and usability are assessed via a questionnaire with 25 respondents, while reliability is tested using WAPT V.10.1. Performance is measured with GTMetrix web analysis, and supportability is tested across different OS and browsers.Results indicate that MV5PAS meets the FURPS model standards in four categories. Functionality scores 0.983 (0 ≤ X ≤ 1), reliability achieves R = 0.982, usability scores 80.2, and supportability is confirmed through successful multi-device testing. However, performance requires improvement, receiving a “D” on the GTMetrix Grade. This highlights the need for quality enhancements to optimize the system’s overall efficiency.

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