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All Journal Jurnal Abdi: Media Pengabdian Kepada Masyarakat Abimanyu: Journal of Community Engagement Journal of Informatics and Computer Science (JINACS) ABDIMASY: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK) Journal of Emerging Information Systems and Business Intelligence (JEISBI)
Aries Dwi Indriyanti
Universitas Negeri Surabaya
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Web-Based Decision Support System for Best Laptop Selection Using MABAC Method Mochammad Rafi Diaz Ardhana; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 4 (2024): Vol. 05 Issue 04
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i4.64267

Abstract

The advancement of technology in the modern era has made devices such as laptops essential in daily life. According to a report from Ministry of Communication and Information Technology of Indonesia that published in 2017, from a survey of 2,121 respondents showed that more than half percent respondent use laptop for work and study, while 34.94% use laptop for entertainment. However, selecting the right laptop often poses a challenge, especially for students in the Informatics Engineering Department at Universitas Negeri Surabaya, who frequently use outdated laptops. To address this issue, a Decision Support System (DSS) is needed, utilizing the Multi-Attributive Border Approximation Area Comparison (MABAC) method. In this study, the MABAC method was used to select laptops based on criteria such as price, CPU, RAM, and storage. By applying the MABAC method, the DSS is believed to effectively address the issue of selecting the most suitable laptop, thereby enhancing productivity and performance. This research successfully developed a web-based Decision Support System (DSS) for selecting the best laptops using the Multi-Attributive Border Approximation Area Comparison (MABAC) method, which simplifies the evaluation process for users. The DSS incorporates 10 criteria: price, processor, RAM, storage, storage type, screen size, graphics card, laptop weight, battery, operating system, and warranty. The MABAC calculations ranked the Asus Vivobook 14 A1400EA as the best laptop with a score of 0.15, followed by the HP 14s EP0022TU and Lenovo Ideapad Slim 3 14ITL6 with scores of 0.05, while the Dell Latitude 3420 ranked last with a score of -0.05.
Sentiment Analysis of 2024 Election Fraud Using SVM and Naïve Bayes Algorithms Faalih Hibban Hilmi; Aries dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 4 (2024): Vol. 05 Issue 04
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i4.64703

Abstract

Elections are one of the main pillars of democracy, where the people's voice is the main determinant in government formation. Election fraud not only harms political competitors but also undermines public trust in democracy. The role of social media Twitter in widely disseminating information and disinformation adds to the challenge of maintaining election integrity. Sentiment analysis is the process of collecting and understanding individual opinions related to an event. Support Vector Machine (SVM) and Naïve Bayes algorithms are often used in this analysis due to their effectiveness and efficiency in text classification. This research aims to analyze public sentiment related to the 2024 presidential election fraud and compare the effectiveness of SVM and Naïve Bayes in sentiment classification. The study was conducted quantitatively, involving the stages of data collection, preprocessing, labeling, TF-IDF weighting, classification, and evaluation. The results of the sentiment analysis of public opinion on the 2024 presidential election fraud showed 42.5% negative sentiment, 38.6% neutral, and 18.9% positive. The dominance of negative sentiments reflects the public's concerns about election integrity. The high neutral sentiment indicates public doubt. To overcome this, transparency, strengthening supervisory institutions, electronic election technology, and strict law enforcement are needed. The SVM algorithm with RBF kernel produces 58% accuracy, better than Naïve Bayes with 51%.
Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model: Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model Darell Timotius Suhartono; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025): Vol. 06 Issue 01
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.
Application of User Centered Design Method on UI/UX of Indodax Cryptocurrency Exchange Application in Indonesia M FATIH FADLIL UBAIDILLAH; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 3 (2025): Vol. 06 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i3.65542

Abstract

This research aims to improve the quality of the User Interface (UI) and User Experience (UX) of the Indodax cryptocurrency exchange application in Indonesia through the application of the User-Centered Design (UCD) method, against the background of the rapid development of digital technology and the increasing public interest in cryptocurrency. Indodax, as one of the leading platforms in Indonesia, needs to ensure that the UI and UX of its application are able to meet user needs. This research identifies various problems with Indodax's UI and UX through literature studies and user surveys, which are then followed by application redesign using the UCD approach, including understanding the context of use, determining user needs, designing solutions, and evaluating these solutions. The results show that the application of the UCD method has significantly improved user satisfaction, which is reflected in the increase in the System Usability Scale (SUS) score from 56.6 (grade D) to 80.3 (grade B). The findings make an important contribution to the development of more humanistic and user-centered cryptocurrency applications, and can serve as a reference for similar application developers in Indonesia, which is expected to improve the overall competitiveness of cryptocurrency platforms.
Comparison of XGBoost and LightGBM for Product Demand Forecasting at KOPERASI XYZ Muhammad Andhika Fahrezzy; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 2 (2026): Vol. 07 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i2.80864

Abstract

ABSTRACT Accurate product demand forecasting is essential for small internal retail units such as cooperative stores (koperasi), where manual, intuition-based stock decisions frequently cause overstock and stockouts. This study develops and compares two gradient boosting algorithms, XGBoost and LightGBM, to forecast daily product demand at KOPERASI XYZ, an internal store located in Sunter, North Jakarta. Historical transaction records from 1 January 2024 to 22 December 2025 were aggregated into daily demand series for four product categories: mineral water, tea drinks, cigarettes, and milk. A total of 37 predictive features were engineered, comprising lag features, rolling and expanding statistics, and calendar features that encode 34 Indonesian national holidays. The data were divided using a chronological (time-based) split of 60:20:20, and both models were tuned using Grid Search cross-validation with a log-transformed target. Forecasting performance was evaluated using the Root Mean Squared Error (RMSE) and the Mean Absolute Percentage Error (MAPE). The results show that LightGBM outperforms XGBoost, achieving an overall RMSE of 24.53 and a MAPE of 9.72% (highly accurate), compared with an RMSE of 27.52 and a MAPE of 11.75% for XGBoost, corresponding to improvements of 10.86% in RMSE and 17.28% in MAPE. The best model was integrated into an interactive Streamlit dashboard that visualizes forecasts and recommends monthly stock levels to support data-driven inventory planning. Keywords:Demand Forecasting, XGBoost; LightGBM, Gradient Boosting, Time Series, Inventory Management
Evaluasi Pengalaman Pengguna Aplikasi Andal By Taspen Menggunakan Model UX Honeycomb Rifqi Firdaus Caesar; Aries Dwi Indriyanti
Jurnal Ilmu Ekonomi, Pendidikan dan Teknik Vol. 3 No. 6 (2026): IDENTIK - November
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/identik.v3i6.2118

Abstract

The Andal by Taspen application was developed to support pension authentication and administrative services. However, users still report problems related to authentication, usability, and system stability. This study evaluates the user experience of the application using the UX Honeycomb model. A quantitative descriptive approach was employed by distributing questionnaires to 232 users selected through simple random sampling. The instrument consisted of 21 items representing seven UX Honeycomb dimensions. Data were analyzed using descriptive statistics based on mean scores. The overall user experience achieved a mean score of 2.78 (fair). The desirable dimension obtained the highest score (3.54), while valuable (2.05) and useful (2.39) received the lowest scores. The findings indicate that improvements are needed in authentication, perceived usefulness, accessibility, and system reliability to enhance the quality of the Andal by Taspen application.  
Analisis Pengalaman Pengguna Pada Aplikasi Discord Menggunakan Heart Framework Ahmad Wahhab Firosyan; Aries Dwi Indriyanti
Jurnal Ilmu Ekonomi, Pendidikan dan Teknik Vol. 3 No. 6 (2026): IDENTIK - November
Publisher : CV. SINAR HOWUHOWU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70134/identik.v3i6.2153

Abstract

Discord is a digital communication platform that provides various features to support communication, communities, work, gaming, and education. The diversity of these features may affect users’ experience in understanding and utilizing them optimally. This study aims to evaluate the User Experience (UX) of the Discord application using the HEART Framework, which consists of Happiness, Engagement, Adoption, Retention, and Task Success. This study employed a quantitative approach using a survey method involving 237 Discord users who were at least 16 years old, had used Discord for at least three months, and were still actively using the application. The research instrument was tested through a pilot test involving 41 respondents and was declared valid and reliable. The results showed that Happiness scored 82.91%, Engagement 80.23%, Adoption 66.72%, Retention 83.07%, and Task Success 81.80%. Four dimensions met the target goal of 80%, while Adoption did not meet the target and had the lowest score. This indicates that users have not fully understood and utilized the various features available on Discord. Therefore, improvements in onboarding, navigation simplification, user guides, and feature discoverability are needed to help users better understand and utilize the available features.  
Co-Authors Ahmad Ajib Ridlwan Ahmad Wahhab Firosyan Aji Catur Prayogo Alya Choirum Mahmudah Anggraeni Widya Purwita Arisni Kholifatu A.S Azhari Yudistya Nurrahman Bonda Sisephaputra Catur Surya Saputra Chusnul Nuur Fadillah Daffa Raihan Antoro Darell Timotius Suhartono Davin Putra Febriansyah Desando Anugrah Ramadhan Faalih Hibban Hilmi Fadhilah Shabuhalaika Aliyya Farah Nabilah Ardana Fattah Bima Maulana Fitri Aurellia Soraya Ghea Sekar Palupi Hafidz Aqilla Herlambang Haris Supratno I Kadek Dwi Nuryana, I Kadek Dwi Ichwan Wahyu Utama Khoirul Anas Khonsa Aziza Almash Lutvia Rahmawati M FATIH FADLIL UBAIDILLAH M. Alfan Tsalits M. Desfreezal Zurarah Bartien Moch. Araafi Syamsul Ibrahim Mochammad Chafithul Ngulum Mochammad Rafi Diaz Ardhana Muhammad Andhika Fahrezzy Muhammad Hashfiudin Tridharma Putra Muhammad Wisnu Aditya Aulia Rachman Nabilla Widyaretno Nadia Nur Thahirrah Rafli Satria Iswandaru Rahadian Bisma Raharjo, Resdianto Permata Rifqi Firdaus Caesar Rizdana Galih Pambudi Yemi Fitriana Yonathan Setiagita Yunus