Jurnal Teknologi Dan Sistem Informasi Bisnis

Decision Support System in Determining Employee Loan Eligibility Using AHP-TOPSIS at PT XYZ

2025-01-04T07:33:50+00:00

A decision support system is a system used by top level managers in making decisions. The decision support system has several methods that can be used, including the AHP and TOPSIS methods. The AHP (Analytical Hierarchy Process) method is a decision making method that focuses more on calculating criteria weights. Meanwhile, the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) is a decision-making method that is suitable for calculating final results and rankings. Determining employee loan eligibility using the AHP and TOPSIS methods produces objective values because the criteria weights and final results are calculated according to the method used.

Analisis Sentimen Pengguna Sistem E-Kinerja Desa Kabupaten Jembrana Menggunakan Metode Naive Bayes

2025-01-04T07:30:35+00:00

The current era of globalization where information is needed very quickly. However, this is an obstacle, especially at the village level where the performance of the village, especially in rural areas, is difficult to obtain information, because it still uses manual bookkeeping. In response to this, the Jembarana Regency Government has improved its services using the website-based E-Kinerja application. Even though E-Kinerja has been used, it is important to know how user sentiment is when using the E-Kinerja system so that it can be used as an evaluation. This study aims to determine the sentiment of E-Kinerja users using the Naive Bayes method, Naive Bayes is a simple method and has high effectiveness in classification. The results of sentiment analysis with the Naive Bayes method get an accuracy of 66% precison 67% and recall 67% with a total of 88 datasets, an accuracy of 77% precison 69% and recall 69% in a total of 150 datasets.

Hospital Clustering Based on Patient Visits Using the K-Means Algorithm: Data 2019-2023

2025-01-04T07:51:48+00:00

Hospitals play a vital role in providing healthcare services to the community. Every day, patients visit hospitals to receive medical care. Over time, patient visit data continues to grow, resulting in a massive accumulation of data. This large volume of patient visit data can be clustered using data mining algorithms, providing strategic insights for resource management, facility planning, and improving the quality of healthcare services. The purpose of this study is to classify hospitals based on the number of patient visits over the past five years. The clustering process was conducted using the K-Means Clustering Algorithm. The research data was obtained from the Satu Data Sumbar website. Hospital patient visit data was grouped into three clusters. The results indicate that Cluster 1 (K1) represents hospitals with very high visit intensity, Cluster 2 (K2) represents hospitals with medium visit levels, and Cluster 3 (K3) represents hospitals with low visit levels.

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Implementasi Metode Prototype Pada Proses PPDB dan Konsultasi Penjurusan (Studi Kasus: SMK Muhammadiyah 3 Yogyakarta)

2025-01-04T10:02:25+00:00

The development of information technology requires schools to optimize the system to improve efficiency, including in the process of admitting new students (PPDB). Muhammadiyah 3 Yogyakarta Vocational Highschool still uses manual PPDB methods such as data collection and processing which causes inefficiency in the registration process, data errors, and requires a lot of energy from the school. This research aims to develop a website-based PPDB system that is tailored to the needs of the school. Data was collected through interviews, observations, and literature studies, with a prototype method approach that involved schools at every stage of development. System testing using usability tests and User Experience Questionnaire (UEQ) with the results of the online PPDB system obtained a positive response with a score of “Excellent” in the aspects of Attractiveness (1.89) and Stimulation (1.81), as well as “Good” in the aspects of Efficiency (1.87), Dependability (1.58), and Novelty (1.57) showing a significant improvement in the quality of the PPDB system of Muhammadiyah 3 Yogyakarta Vocational Highschool.

Trends in Decision Support System Development Using the Simple Additive Weighting Method: Systematic Literature Review

2025-01-04T10:09:24+00:00

The advancements in digital transformation era have impacted the complexity of decision-making processes across various sectors, especially with the increasing volume of large and diverse data. In this context, efficient tools were required to objectively evaluate multi-criteria alternatives. Simple Additive Weighting (SAW) emerged as one of the most widely used methods in Decision Support Systems (DSS). However, systematic reviews discussing the development and implementation of this method in various contexts remained very limited. This study aimed to conduct a Systematic Literature Review (SLR) on the development of SAW-based DSS with a focus on identifying application platforms, design methods, and their benefits. This study employed a Systematic Literature Review approach following the Kitchenham guidelines. The findings showed that web-based platforms dominated DSS development due to their flexibility, accessibility, and ability to support real-time decision-making. Furthermore, the Prototyping design method was frequently used as it allowed dynamic adjustments of the system to meet user needs. The application of the SAW method consistently demonstrated improvements in accuracy, time efficiency, transparency, and user trust in the decision-making process.

Pengembangan Aplikasi Rekeningku Sebagai Platform Pencatatan Nomor Rekening Menggunakan Metode Waterfall

2025-01-04T10:33:36+00:00

Perkembangan teknologi mobile memberikan kemudahan dalam berbagai aspek kehidupan, salah satunya adalah pengelolaan informasi seperti nomor rekening bank. Penelitian ini bertujuan untuk merancang dan mengembangkan aplikasi “Rekeningku”, sebuah platform yang memungkinkan pencatatan nomor rekening bank. Proses pengembangan menggunakan model Waterfall, yang meliputi tahapan analisis kebutuhan, pengembangan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Hasil penelitian ini menunjukkan bahwa aplikasi ini dapat berfungsi dengan baik dan memberikan kemudahan bagi pengguna dalam mengelola nomor rekening pribadi maupun orang lain. Evaluasi pengguna menunjukkan kepuasan terhadap fitur dan kemudahan dalam menggunakan aplikasi ini.

Analisis Penerapan Teknologi Web3.0 pada Pengembangan Game: Systematic Literature Review

2025-01-07T03:15:09+00:00

The development of Web3.0 technology in the gaming industry is showing significant and promising progress. Web3.0 offers innovation in game development through the application of blockchain, NFT, and metaverse technologies. This research aims to identify applications of Web3.0 technologies that are commonly used in game development and analyze the challenges and opportunities faced. The Systematic Literature Review (SLR) method was chosen to review the literature relevant to the application of Web3.0 in gaming. The results of this study cover the various technologies and platforms used, as well as challenges such as cost and scalability, and opportunities arising from digital ownership and new business models. The findings are expected to provide guidance for game developers in adopting Web3.0 technologies effectively and innovatively.

Prediksi Harga Rumah menggunakan Machine Learning Algoritma Regresi Linier

2025-01-07T03:23:30+00:00

The property sector plays a vital role in the global economy, especially regarding property price prediction, which is a complex challenge influenced by factors such as building size, number of rooms, location, and property condition. This study aims to build a property price prediction model using the Linear Regression algorithm. The data used in this research was obtained from Kaggle, consisting of 1460 data points on house prices in Ames, USA. The preprocessing phase includes handling missing data, outlier management, and feature standardization using StandardScaler to ensure data consistency. The linear regression model was trained and evaluated using R-squared (R²) and Root Mean Squared Error (RMSE) metrics. The evaluation results show an R² of 0.81, indicating the model explains 81% of the variation in house prices. Additionally, the RMSE value of 35,830.40 shows the model's relatively low and consistent error when tested with different data. Features such as overall house quality (OverallQual) and living area size (GrLivArea) significantly correlate with house prices. These findings demonstrate that linear regression is an effective tool for predicting property prices.

Pengembangan Aplikasi Bengkel Las di Kediri dengan Metode Extreme Programming

2025-01-07T03:34:48+00:00

In the ever-evolving software development industry, efficient methodologies are crucial for delivering high-quality applications on time. Extreme Programming (XP) is one of the methodologies adopted for various types of software projects, offering flexibility and responsiveness to user feedback. This study aims to apply the XP method in the development of an online welding workshop mobile application and document the process and results. The main goal is to explore how XP practices contribute to the development of a functional mobile application and provide valuable insights for future application development strategies. The XP method was applied over a seven-week period, focusing on small iteration planning (small releases), Test-Driven Development (TDD), and Continuous Integration (CI). These techniques were employed to ensure efficient development, continuous testing, and close collaboration with users to meet their needs. The application of XP in this project demonstrated its effectiveness in delivering a functional, user-focused mobile application in a short timeframe. This study documents the entire XP process and can serve as a reference for future development strategies, particularly in mobile and web app development.

Evaluasi dan Rekomendasi Perbaikan Proses Pemenuhan Permintaan Layanan Teknologi Informasi: Studi Kasus PT Bank XYZ

2025-01-07T03:41:57+00:00

As digital payments in Indonesia increase, they drive the financial industry, especially banking, to continue their digital transformation. BANK XYZ is one of the banks that is also undergoing digital transformation. To improve banking services that are always available and meet market demand, it is necessary to fulfill the demand for information technology (IT) services. However, there is a problem in this process, namely that many requests are not followed up and closed even though they have been worked on, causing delays in fulfilling user requests. Therefore, this research aims to evaluate the process of fulfilling IT service requests and provide improvement recommendations for the future. The evaluation process in this study uses the COBIT 2019 framework to measure the capability of relevant process areas, and ITIL V4 provides good practices for process improvement recommendations. After data collection and capability measurement on eleven processes, the results showed that three processes were at level two, namely APO09, BAI08, and BAI10. There are five processes at level three, namely BAI07, BAI08, DSS02, DSS03, and DSS04. For the achievement of level four, there are two processes, namely APO14 and BAI06, and one process that has reached the level, namely DSS01. Then, in the gap analysis process, there are three processes that have met the management's targets, namely APO14, BAI06, and DSS01, and eight processes that have not yet met the targets. Recommendations are given for the eight processes that have not yet met the management's expected targets.

Information Technology Management System of Sharing Knowledge Between Universities Using Systematic Literature Review

2025-01-16T06:16:19+00:00

Knowledge is a vital resource for academic institutions, driving innovation dan development. However, universities face challenges in effective knowledge sharing due to cultural barriers, lack of trust, and technological constraints. This research, conducted using a Systematic Literature Review (SLR), identifies key variables influencing knowledge sharing, highlights challenges, and proposes solutions to foster collaboration. The findings reveal that cultural barriers, such as competitive organizational environments and technological constraints, including high costs and user-friendly systems, significantly hinder knowledge sharing. To address these issues, the study recommends implementing user-friendly technologies, promoting collaboration through seminars and workshops, and encouraging cross-departmental projects. These solutions provide actionable insights to enhance knowledge sharing frameworks and support innovation across academic institutions

Deteksi Sampah Botol Plastik di Perairan Menggunakan YOLO v4-Tiny

2025-01-16T06:23:56+00:00

This study focuses on the implementation of the YOLOv4-Tiny algorithm on Raspberry Pi 5 for detecting plastic bottle waste in aquatic environments. The primary goal is to optimize the frame per second (FPS) while maintaining detection accuracy. A dataset consisting of 914 images was augmented using RoboFlow to enhance the robustness of the model under real-world conditions. Experiments were conducted in a controlled pool environment with an input resolution of 320x320 pixels. Results demonstrated an average FPS of 7-8, with detection accuracy ranging between 67% and 80%. Further evaluation reported a total loss of 0.3, mean Average Precision (mAP) of 97.94%, precision of 93%, recall of 96%, F1 score of 0.95, and an average Intersection over Union (IoU) of 76.47%, indicating effective bounding[1] box prediction capabilities. These results highlight the potential of YOLOv4-Tiny as a lightweight and real-time detection solution, particularly for low-computational devices such as Raspberry Pi. The findings provide a solid foundation for developing efficient plastic waste detection systems, which can be deployed across various aquatic locations, supporting environmental monitoring and waste management initiatives.

A Novel RGB-Depth Imaging Technique for Food Volume Estimation

2025-01-16T06:52:10+00:00

Evaluating nutrient intake among patients in a hospital is crucial, as it can accelerate their recovery process. Estimating calorie intake can be achieved by monitoring the quantity of food consumed by patients both before and after their meals. This approach involves various methods, including the use of digital scales, the Comstock level, and digital imaging techniques. Nonetheless, these techniques have their own limitations, particularly the risk of subjective assessments. To reduce errors arising from human factors, an objective evaluation is proposed. This paper introduces a new technique for measuring volume using RGB-Depth images. The method incorporates image segmentation and edge detection in RGB images to correspond with the depth image. Subsequently, the segmented regions and boundaries from the depth images are converted into point clouds. The volume of interest is calculated by fitting the point cloud to an ellipsoid. The lowest Mean Average Percentage Error (MAPE) is 2.73. It indicates that the proposed method is sufficient to measure the food volume.

Analisa Efektivitas sistem Adaptive Defense Schemes (ADS) dengan teknologi 4.0 dalam Meningkatkan Keandalan Sistem Transmisi Tenaga Listrik Kalimantan

2025-01-16T07:45:51+00:00

The disruption of the electricity transmission system can lead to a total blackout, resulting in losses for both customers and PT PLN (Persero) UIP3B Kalimantan company. The vulnerability map of the Kalimantan interconnection system indicates that the Barikin - Tanjung Line is particularly vulnerable due to this transmission line is a crucial junction connecting major power plants to the transmission lines of South Kalimantan, Central Kalimantan, and East Kalimantan. Adaptive Defense Schemes (ADS) is an adaptive protection system that dynamically implements load shedding to reduce the risk of blackouts. ADS employs a Technology 4.0 system that integrates SCADA, protection, and IT systems, necessitating substantial costs. The effectiveness of ADS is assessed using ARIMA forecasting. Research result shows that ADS implementation reducing total disturbance as much as 77%, disturbance duration 68%, and ENS 65%. The result of ADS implementation impact in financial sector shows the reduction of 65% of company potential loss in effect of disturbance in transmission system, and also in the period of 2023 – 2026 where the ADS is still implemented, then the company could reduce 60% of its potential loss because of the disturbance in the transmission system