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JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Published by Universitas Lambung Mangkurat
ISSN : 25275399     EISSN : 25282514     DOI : http://dx.doi.org/10.20527
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) is intended as a media for scientific studies on the results of research, thinking and analytical-critical studies regarding research in Systems Engineering, Informatics / Information Technology, Information Management and Information Systems. As part of the spirit of disseminating knowledge from the results of research and thought for service to the wider community and as a reference source for academics in the field of Technology and Information.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 10 Documents
 1 
Search results for , issue "Vol. 10 No. 2 (2025)" : 10 Documents clear
Implementation of Midtrans Payment Gateway in the 81 Coffee Sales Application Ari anto; Rafie Rafie
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.471

Abstract

81 Coffee is a coffee shop business established in Banjarmasin City that faces challenges in its conventional sales system and dependency on third-party marketplaces, which affect profit margins and operational efficiency. This study aims to design and implement a mobile-based coffee sales application to improve transaction efficiency, expand customer reach, and provide a better user experience. The research employed a software development method using the Flutter framework for mobile application development, Firebase as the cloud database, and Midtrans as the payment gateway. The system was tested through functional, integration, and field testing using various devices and network conditions to measure response time, transaction success rate, and data consistency. The results show that the application performs effectively, achieving an average UI response time of 1.2 seconds, payment success rate of 98%, and data consistency of 100%. The integration of Midtrans enables a secure and seamless digital payment process. Overall, the developed system improves operational efficiency and provides a reliable digital sales platform for 81 Coffee’s business operations.
Web-Based Contract Employee Payroll Information System at PT.Bridgestone Kalimantan Plantation Asti Yana; Rahmat Hidayat; Rafie Rafie
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.472

Abstract

The payroll system for contract employees used by PT. Bridgestone Kalimantan Plantation has been relying on Microsoft Excel to calculate contract employee salaries. However, using Microsoft Excel has several drawbacks when it comes to payroll processing, one of which is its inefficiency when dealing with large datasets. This study aims to analyze and design a web-based payroll system for contract employees to assist and simplify the process of calculating payroll for contract employees at PT. Bridgestone Kalimantan Plantation. The methods used in this study include system requirements analysis, database design, and the implementation of a web-based system using Laragon as the database. This research was conducted by analyzing the current system, obtaining data from direct interviews with parties involved in the employee payroll system, and conducting observations. The results of this research simplify the processing of contract employee data, minimize data errors, accelerate data verification and validation, and make salary calculations easier, thereby generating more effective and efficient information.
Implementation of An Indonesian Vehicle License Plate Recognition System In Real-Time Using EasyOCR and Regex Pattern Validation Moch Taufik; Asep Hernandi; Muhammad Wahyu Syaiful Anaam; Andi Riansyah
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.473

Abstract

This study presents the design and implementation of a real-time Automatic License Plate Recognition (ALPR) system specifically tailored for Indonesian vehicle plates, integrating EasyOCR, computer vision-based image preprocessing, and Regular Expression (regex) validation. The system captures images or video streams and applies a multi-level preprocessing pipeline, including grayscale conversion, Gaussian noise reduction, edge detection, and contour-based plate localization, before performing optical character recognition based on deep learning using a convolutional recurrent neural network with an attention mechanism. Post-recognition processing with regex filtering ensures strict compliance with the official Indonesian license plate format, thereby minimizing false positives and improving recognition accuracy. Experimental evaluation using real-world surveillance data achieved 75% accuracy, 100% precision, 75% recall, and an F1-score of 86%, indicating an optimal balance between detection precision and sensitivity. The system’s advantages include real-time performance, ease of deployment with open-source software, and adaptability to various lighting and environmental conditions. However, the system still shows limitations under extreme conditions such as nighttime, heavy rain, and dense traffic, where recognition accuracy tends to decrease. Therefore, future research will focus on algorithm optimization for low-light, adverse weather, and motion-blur scenarios, large-scale deployment in urban areas, and integration with AI-based vehicle tracking, positioning this system as a key enabling technology in the development of smart city infrastructure.
Design of a Web-Based Medical Equipment Monitoring Information System at Bhakti Yudha Hospital Evy Nurmiati; Ahmad Khahfi; Musthafa Kamil
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.474

Abstract

Effective inventory management is a critical component for ensuring smooth operational continuity, especially in a healthcare setting where timely access to supplies directly impacts patient care. At Bhakti Yudha Hospital, this vital process is hampered by its reliance on manual, spreadsheet-based tracking. This traditional approach is highly susceptible to human error, resulting in significant data inaccuracies and a critical lack of real-time stock visibility, which can ultimately compromise service delivery. To overcome these challenges, a web-based inventory monitoring information system was developed using the Rapid Application Development (RAD) methodology, chosen for its rapid and iterative prototyping capabilities. Modeled with UML diagrams, the system is designed to automate data entry, enhance accuracy, and provide transparent, role-based stock information for both administrators and general users. Key features include an analytical dashboard for strategic oversight, automated low-stock notifications to prevent shortages, and versatile PDF report generation for documentation. Comprehensive black-box testing has confirmed that all core functionalities perform as expected, meeting the initial requirements. This positions the system as an effective solution to significantly optimize the reliability and efficiency of the inventory management process at Bhakti Yudha Hospital.
Financial Management Website Design Using a Design Thinking Approach (Case Study Noka Dessert) Okti Bela Alisia; Moch. Tiofany Yugi Ferdiansyah; Muhammad Alimun; Anisa Hudi Widaningrum; Priska Choirina
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.475

Abstract

Micro, small and medium enterprises (MSME) such as Noka Dessert often use outdated methods to document financial transactions, which makes tracking finances in real time impossible and is prone to errors. This study intends to explore the creation of a web-based financial management system with the purpose of automating the task of record-keeping and improving real time reporting using the Design Thinking approach. Focusing on users such as owners and employees ensures enhanced accuracy, efficiency, and improved accessibility of the data. The system allows forser authentication as admin and staff, with rights for data entry, validation, and reporting. Functional testing using the System Usability Scale (SUS) has indicated a satisfactory user experience with a mean score of 76. Further research is recommended towards connecting the system with digital payment platforms, overhauling the inventory system, and conducting regular workshops. Noka Dessert is anticipated to improve financial management in this system, leading to sustainable business growth.
Comparison of Naive Bayes and SVM in Public Opinion Sentiment Analysis on Platform X Salma Ngarifatul Khofiyah; Pungkas Subarkah
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.478

Abstract

The growth of social media has made it the primary means for the general public to express their opinions, including on political and legal issues in Indonesia. One topic that has been widely discussed is the abolition of Tom Lembong and the amnesty granted to Hasto Kristiyanto by President Prabowo Subianto, which has garnered mixed public reactions on the X platform. The purpose of this study is to analyze public sentiment regarding current issues and compare the performance of two machine learning algorithms, Naïve Bayes and Support Vector Machine (SVM), to classify public opinion. Data was obtained through a crawling process of 3,003 tweets, followed by a preprocessing stage that included cleaning, case folding, slang normalization, tokenizing, stopword removal, and stemming. Next, a suitability analysis using the TF-IDF method was conducted before the data was processed by the two algorithms. The results showed that, of the 2,998 valid tweets, 78.6% of public opinion was negative and only 21.4% was positive, indicating a predominance of criticism of the issues discussed. When comparing the algorithms, SVM provided more accurate results with an accuracy rate of 78.66%, while Naïve Bayes only achieved 58%. This shows that SVM is more flexible in analyzing text data with a high level of complexity compared to Naïve Bayes.
Comparative Evaluation of Data Mining Classification Algorithms For Predicting Earthquake Alert Levels Arya Ardhi Baskara
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.481

Abstract

Earthquakes are one of the most destructive natural disasters, particularly in Indonesia, which is located at the convergence of three active tectonic plates. Conventional early warning systems generally rely on real-time vibration detection but lack the capability to provide comprehensive predictions about the potential severity of an earthquake. This study aims to address these limitations by applying data mining techniques and machine learning algorithms to classify earthquake alert levels based on seismic parameters, including magnitude, depth, Community Determined Intensity (CDI), Modified Mercalli Intensity (MMI), and significance (Sig). A dataset of 1,300 earthquake records was obtained and processed using the Knowledge Discovery in Database (KDD) methodology, which includes data selection, preprocessing, transformation, modeling, and evaluation. Five classification algorithms were compared: Decision Tree, Random Forest, Naïve Bayes, K-Nearest Neighbor (KNN), and Neural Network. Model performance was evaluated using confusion matrix metrics such as accuracy, precision, recall, and F1-score. The results indicate that Random Forest achieved the highest performance with an accuracy of 88.52% and macro recall of 88.90%, outperforming other algorithms. Decision Tree ranked second with balanced performance, while KNN and Neural Network achieved moderate results. Naïve Bayes performed the weakest. Overall, Random Forest is the most reliable algorithm for supporting earthquake early warning systems.
Application of the Heart Metrics Method in Analyzing User Experience on the Rayz UMM Website Wildan Suharso; Briansyah Setio Wiyono; Firman Firman
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.482

Abstract

The Rayz UMM Hotel website serves as the primary medium for conveying information about services and facilities, but so far, the quality of the user experience (UX) on the website has not been studied in depth. Based on the initial questionnaire results, there were also several negative responses that indicated dissatisfaction with the aspects of Happiness and Adoption. Therefore, a comprehensive UX evaluation is needed. This study uses the HEART Framework method, which covers five aspects, namely Happiness, Engagement, Adoption, Retention, and Task Success. The research instrument is a questionnaire with 20 questions distributed to website users, which is then analyzed through validity and reliability tests, hypothesis testing, and measurement of the level of usability. The results show that the variables of Happiness and Task Success are in the very high category, Retention is in the very high category, while Engagement and Adoption are in the very high category. These findings confirm that the Hotel Rayz UMM website has generally been able to provide a fairly good user experience, but still needs development in terms of navigation and system performance in order to optimize UX quality.
Performance Evaluation of Random Forest for Hypertension Risk Prediction Arya Ardhi Baskara
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.483

Abstract

Hypertension is a major global health concern and a leading risk factor for cardiovascular disease, stroke, and kidney failure. Early prediction of hypertension is crucial because the condition is often asymptomatic in its initial stages and late detection increases the likelihood of severe complications. This study aims to develop and evaluate a predictive model for hypertension using the Random Forest algorithm, a robust ensemble learning method well-suited for medical data classification. The dataset used in this research was obtained from Kaggle and contains 1,985 records with 11 attributes representing demographic, lifestyle, and clinical risk factors. Preprocessing was performed to ensure data quality, followed by Random Forest classification with different parameter settings. The model was evaluated using 5-fold and 10-fold cross-validation with various numbers of trees ranging from 50 to 250. Performance metrics included accuracy, precision, recall, F1-score, and AUC. Experimental results demonstrated that the Random Forest algorithm achieved consistently high performance, with accuracy above 93%, precision above 95%, recall above 91%, F1-scores above 93%, and AUC values between 0.986 and 0.991. These findings confirm that Random Forest is highly effective and reliable for predicting hypertension risk. The study highlights the algorithm’s potential as a decision-support tool for early detection, enabling preventive measures and improving public health outcomes.
The Application of Augmented Reality in Furniture Purchasing and Evaluation Based on the System Usability Scale (SUS) Muhammad Fajrian Noor; Sofyar Sofyar; Dwipayana Ismulya; M. Utiya Raihan; Aqil Rahmatullah; M. Renald Abdi
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.489

Abstract

The furniture industry is undergoing a significant digital transformation, reshaping how consumers interact and make purchasing decisions. Augmented Reality (AR) technology enables users to visualise furniture products in their actual physical spaces before making a purchase, offering a more interactive, realistic, and personalised shopping experience. This study aims to evaluate the effectiveness of AR technology in supporting online furniture purchasing by applying the ADDIE development model and assessing usability through the System Usability Scale (SUS) method. A total of 35 respondents, representing millennial and Gen Z users aged between 18 untill 35, participated in testing an AR-based furniture shopping application. The research findings indicate that the application achieved an average SUS score of 81.5, which falls into the "Excellent" usability category, signifying a high level of user satisfaction and acceptance. The results also reveal that AR improves consumer confidence in product selection by allowing realistic visualisation of furniture items in users' own environments. Therefore, this study concludes that integrating AR technology in digital commerce not only enhances user experience but also provides an effective marketing strategy for furniture businesses to strengthen customer engagement, trust, and purchase decisions in the digital era.

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