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Jurnal ULTIMA InfoSys
Published by Universitas Multimedia Nusantara
ISSN : 20854579     EISSN : 25811851     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal ULTIMA InfoSys merupakan Jurnal Program Studi Sistem Informasi Universitas Multimedia Nusantara yang menyajikan artikel-artikel penelitian ilmiah dalam bidang Sistem Informasi, serta isu-isu teoritis dan praktis yang terkini, mencakup sistem basis data, sistem informasi manajemen, analisis dan pengembangan sistem, manajemen proyek sistem informasi, programming, mobile information system, dan topik lainnya terkait Sistem Informasi. Jurnal ULTIMA InfoSys terbit secara berkala dua kali dalam setahun (Juni dan Desember) dan dikelola oleh Program Studi Sistem Informasi Universitas Multimedia Nusantara bekerjasama dengan UMN Press.
Arjuna Subject : -
Articles 236 Documents
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Unlocking Sales Insight through Business Intelligence and ERP Aulia, Azka; Desanti, Ririn Ikana; Amri, Mahfudz
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4275

Abstract

In recent years, companies have experienced growing competition, financial inefficiencies, and operational instability, which have contributed to declining profitability. Digital transformation is found to increase operational efficiency while minimizing risk of insolvency. PT Dwi Family Investama, an offset and printing company, experiences similar problems from its manual record of orders and invoices, which causes decreased efficiency, errors, and complicated handling of customer information. Such inefficiencies slow down business strategy formulation and decision-making. This research designs a web-based Enterprise Resource Planning (ERP) system integrated with business intelligence dashboard to facilitate better decision-making. The system automates business processes and delivers real-time operational insights through an interactive dashboard. Performance assessments record an increase in operational efficiency by 52.3%, proving the system’s effectiveness in improving business operations and decision-making.
Extraction of Class Candidates from Scenario in Software Requirements Specifications Rasi Aziizah Andrahsmara; Siahaan, Daniel Oranova
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4325

Abstract

The development of software applications involves translating software requirement specifications (SRS) into structured models that guide system design. Among these, sequence diagrams are essential for visualizing dynamic interactions, but their manual construction from natural language descriptions is often error-prone and time-consuming. This study proposes an automated method for extracting sequence diagram elements namely classes, subclasses, and attributes from scenario sections of SRS documents. The approach leverages Natural Language Processing (NLP) techniques, combining Bidirectional Encoder Representations from Transformers (BERT) for contextual embeddings and Support Vector Machine (SVM) for classification. Noun phrases are identified and classified into UML-relevant entities using this hybrid model. To evaluate performance, two datasets SIData and SILo were used, each exhibiting distinct textual styles and domain characteristics. The system’s effectiveness was assessed using standard evaluation metrics such as precision, recall, and F1-score. Results indicate that the method is capable of capturing contextual relationships between extracted elements, although its performance varies across datasets, suggesting the need for further refinement. Overall, the study contributes toward automating early software design phases and reducing manual modeling effort.
Needle Stick Injury Report Application Design at XYZ Hospital in Tangerang Setiawan, Haditya; Suryasari
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4407

Abstract

Needle stick injuries are a common occurrence among healthcare workers. There are potential risks of HBV, HCV, and HIV infection transmission to healthcare workers caused by needle stick injury accidents. At XYZ Hospital, reporting is done manually through paper-based forms that must be filled out and submitted to other departments. To expedite the process, the forms are photographed and sent via WhatsApp. Manual reporting is still considered inefficient, so a website-based reporting application was created that can be accessed quickly and easily via mobile phones, tablets, and laptops. To ensure the project meets requirements, the application was created using a prototype methodology, so it can be completed according to user needs. By implementing a website-based reporting application, it can simplify reporting, tracing, and more neatly documenting by reducing physical/paper documents and switching to digital documents.
Analyzing Factors Influencing Flow Experience in Battle Royale Games: A Case Study of Free Fire MAX Fatih, Farrel Andhika; Saputra, Edi; Bintana, Rizqa Raaiqa
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4446

Abstract

The rapid growth of the mobile gaming industry, especially within the Battle Royale genre, has reshaped player engagement and competition. Free Fire MAX stands out by combining immersive gameplay with narrative driven elements that sustain long term involvement. This study investigates the influence of Game Design Factors (GDF) on players’ Flow Experience using quantitative analysis. Eleven factors Game Goals, Game Mechanism, Interaction, Freedom, Game Fantasy, Narrative, Sensation, Game Value, Challenges, Sociality, and Mystery were examined. Results show that Narrative, Challenges, and Mystery significantly affect Flow (Sig < 0.05), while others have no substantial impact. The narrative dimension, reinforced through collaboration based storytelling such as themed skins and crossover events, enhances emotional engagement. The challenge factor promotes Flow through balanced difficulty and adaptive gameplay, while the mystery element stimulates curiosity through hidden rewards and unpredictable events. Gender based analysis revealed no significant difference in Flow between male and female players, indicating that psychological immersion transcends gender. These findings support Csikszentmihalyi’s Flow Theory and Shi and Shih’s (2015) Game Design Factors model, emphasizing that engaging narratives, balanced challenges, and mystery driven discovery are key to sustaining player immersion in competitive mobile gaming.
An Exploratory Study of Video Game Pricing in the Southeast Asian Market Wibowo, Tony; Sandriawan, Elfan; Eryc
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4456

Abstract

This exploratory study examines optimal video game pricing within the Southeast Asian market from the perspective of gamers. Employing a two-phase quantitative analysis of 405 respondents across six nations—Indonesia, Malaysia, Singapore, Thailand, the Philippines, and Vietnam—the study identifies a consistent psychological pricing framework. Key findings reveal two stable price thresholds: a normative expectation of approximately USD 20 for indie titles and an upper limit of USD 40–60 for premium AAA games. The research confirms a significant market transition from price sensitivity to value sensitivity, where developer reputation and production quality directly influence price acceptance. Furthermore, the study substantiates the emergence of a "premium indie" category, indicating consumers are willing to invest more in independent games that demonstrate high levels of trust, quality, and artistry. These insights offer crucial guidance for developers and publishers, highlighting the need for localized pricing strategies that respect established value perceptions while adjusting for regional purchasing power. This study addresses a notable gap in the literature concerning consumer pricing behavior in the rapidly growing Southeast Asian gaming market.
Utilizing a Data Warehouse to Analyze the Effects of Sales Type, Product Type, and Price on Net Profit in an F&B Outlet Putri, Allegra Aretha; Aurelia, Nadine; Veronika, Vera; Wiriady, Fransiska Eka Putri; Kurniawan, Rido Dwi; Sari, Muh. Masri
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4513

Abstract

This research aims to investigate how sales type, product type, and price influence net profit in an F&B outlet using a Data Warehouse system. A quantitative method was applied by integrating daily transaction data into a Data Warehouse architecture built through an Extract, Transform, and Load (ETL) process, allowing the data to be more organized and easier to analyze. To address heteroskedasticity and obtain more reliable coefficient estimates, multiple linear regression with HC3 robust standard errors was used. The results show that price and sales type have a significant and positive effect on net profit, while product type shows mixed effects depending on the category. The regression model, with an R² value of 0.994, indicates that these three variables explain most of the variation in net profit. Overall, the findings highlight how structured data processing through a Data Warehouse can support profitability analysis and improve decision-making in F&B operations.
Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) Model Using GIS and Machine Learning Febryansyah Hans Arieyantho, Febry; Luqman; Agtriadi, Herman Bedi
ULTIMA InfoSys Vol 16 No 2 (2025): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v16i2.4543

Abstract

The adoption of electric vehicles in Indonesia is a strategic initiative supporting the national “Go Green” agenda and the Net Zero Emission target by 2060. As electric vehicle usage continues to grow, especially in West Java, well-distributed Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) locations are increasingly important. Inefficient placement may lead to operational issues, reduced user convenience, and financial losses. This research develops such a model by integrating Geographic Information System (GIS) techniques with machine learning algorithms, specifically Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). Data preparation includes collecting spatial datasets such as road networks, housing, apartments, parking areas, public facilities from OSM, administrative boundaries from Geofabric, and existing SPKLU points from OpenData West Java. Proximity analysis is used to measure distances to key features, enabling classification of potential locations into Shared-Residential, Enroute, and Destination categories. These outputs are combined with socio-economic variables, including population density, income levels, vehicle ownership, household characteristics, education levels, and age distribution processed using Kernel Density Estimation (KDE). Results show that MLP performs best with 92.8% accuracy. The most influential variable is the productive-age population, minority population, unemployment, and total population. Overall, demographic factors play a dominant role in determining optimal SPKLU locations.
Sentiment Analysis of Indonesian Tourism Social Media Using Naïve Bayes for Decision Support Nathaniel Felix Fraderic; Aditiya Hermawan; Junaedi Junaedi
ULTIMA InfoSys Vol 17 No 1 (2026): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v17i1.4139

Abstract

The tourism sector remains one of the main contributors to Indonesia's economy, but its development is still challenged by inadequate communication and publication. Understanding visitors' opinions is essential for improving tourist destinations. This study aims to analyze public sentiment toward Indonesian tourist attractions by automatically processing visitor responses using sentiment analysis. The proposed approach applies text mining with the Naïve Bayes algorithm to classify sentiments efficiently. Data were collected through the X platform API using tourism-related keywords and hashtags, providing real-time public opinions on Indonesian destinations. A web-based application was developed using Python to visualize the sentiment analysis results as graphs showing the distribution of sentiment categories. The proposed model achieved an accuracy of 87%, demonstrating its effectiveness in classifying public responses. The findings provide useful insights for tourism stakeholders to evaluate visitor perceptions, identify areas for improvement, and support data-driven decision-making to enhance tourism services and visitor experiences. This study contributes to tourism research by applying the Naïve Bayes algorithm to Indonesian-language tweets related to tourist attractions, demonstrating the feasibility of text mining for automatically analyzing public opinion and supporting tourism development.
Applied Machine learning for Pediatric Nutrition A K-Means Clustering Application Based on WHO Z-Scores Julius Sepadan Maruli Tua Manurung; Sri Agustina Rumapea; Edward Rajagukguk; Fernando Rumapea
ULTIMA InfoSys Vol 17 No 1 (2026): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v17i1.4495

Abstract

Abstract—Nutritional status in early childhood is a key indicator of public health and serves as a basis for targeted nutritional interventions. This study applies the K-Means Clustering algorithm to anthropometric data—including weight, height, and head circumference—to classify children's nutritional status into five categories: severely undernourished (−3 SD), moderately undernourished (−2 SD), normal, mildly overnourished (+1 SD), and moderately overnourished (+2 SD). The clustering process is based on Z-scores derived from WHO standards, namely Weight-for-Age (WAZ), Height-for-Age (HAZ), and Head Circumference-for-Age (HCAZ), which serve as input features for the clustering algorithm. The number of clusters (k = 5) is aligned with national nutritional classification guidelines. The clustering results are visualized to illustrate the data distribution across the three indicators, and evaluated using Euclidean distance to assess the proximity of each data point to its assigned cluster centroid. The results demonstrate that K-Means Clustering can effectively classify children's nutritional status in a manner consistent with manual classification based on WHO thresholds. This study highlights the potential of data mining approaches in supporting health information systems for the early and automated detection of child malnutrition. Index Terms—Nutritional Status; Anthropometry; Z-Score; K-Means Clustering
E-Service Quality Analysis of the MyTelkomsel Application Using CSI, IPA, and PGCV Ananda Khoirunnisa; Dwi Rosa Indah; Ardina Ariani; Ari Wedhasmara; Naretha Kawadha Pasemah Gumay; M. Rudi Sanjaya; Mukhlis Febriady
ULTIMA InfoSys Vol 17 No 1 (2026): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v17i1.4497

Abstract

This study evaluates the e-service quality of the MyTelkomsel application in response to ongoing user concerns, particularly slow service response and the limited effectiveness of the automated support system. A structured questionnaire based on the five SERVQUAL dimensions was used and demonstrated strong validity and reliability. Data were collected from one hundred users in Java and Sumatera. The analysis combined three methods: the Customer Satisfaction Index, Importance Performance Analysis, and Potential Gain in Customer Value. The findings show that the application achieved a Customer Satisfaction Index score of 67.75 percent, indicating that users are generally satisfied but expect further improvement. The Importance Performance Analysis recorded a suitability level of 74.54 percent, with several attributes placed in the high-importance low-performance quadrant, including login security, chatbot speed, complaint handling, and personal data protection. The Potential Gain in Customer Value results indicate that chatbot-related attributes and transaction reliability provide the highest potential for increasing customer value. Overall, the study highlights specific service attributes that require priority enhancement to strengthen user satisfaction and service quality.

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