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Jurnal Teknologi Dan Sistem Informasi Bisnis
Published by Universitas Dharma Andalas
ISSN : -     EISSN : 26558238     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal Teknologi dan Sistem Informasi Bisnis merupakan Jurnal yang diterbitkan oleh Prodi Sistem Informasi Universitas Dharma Andalas untuk berbagai kalangan yang mempunyai perhatian terhadap perkembangan teknologi komputer, baik dalam pengertian luas maupun khusus dalam bidang-bidang tertentu yang terkait dengan teknologi informatika komputer. Naskah yang diterima untuk diterbitkan berupa hasil penelitian lapangan, penelitian kepustakaan, pengamatan serta karya ilmiah yang berhubungan dengan topik yang relevan dengan situasi Teknologi Komputer.Jurnal Teknologi Komputer terbit 2 kali dalam satu tahun yaitu bulan Januari dan Juli.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 30 Documents
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Search results for , issue "Vol 7 No 1 (2025): Januari 2025" : 30 Documents clear
Sistem Pendukung Keputusan dalam Menentukan Kelayakan Pinjaman Karyawan Menggunakan AHP-TOPSIS pada PT XYZ Sulistiyaningsih, Febriani
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1565

Abstract

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 aditya, eka; Astawa, I Gede Karya; Limbong, Kevin Gary; Indrawan, Gede; Gunawan, Made Agus Oka
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1693

Abstract

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.
Klasterisasi Rumah Sakit berdasarkan Kunjungan Pasien menggunakan Algoritma K-Means: Data 2019-2023 Mayola, Liga; Hafizh, M.; Syahputra, Hadi
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1703

Abstract

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. Keywords:
Analisis Penerapan Teknologi Web3.0 pada Pengembangan Game: Systematic Literature Review Sama, Hendi; Liang, Suwarno; Khomali, Carlos Justin
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1711

Abstract

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.
Implementasi Metode Prototype Pada Proses PPDB dan Konsultasi Penjurusan (Studi Kasus: SMK Muhammadiyah 3 Yogyakarta) Afifah, Qonita; Mardhia, Murein Miksa
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1722

Abstract

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.
Tren Pengembangan Sistem Pendukung Keputusan Metode Simple Additive Weighting: Systematic Literature Review Rahman, Ikhlasul Aulia
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1727

Abstract

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.
Prediksi Harga Rumah menggunakan Machine Learning Algoritma Regresi Linier hallan, rosalia roja; Fajri, Ika Nur
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1732

Abstract

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.
Information Technology Management System of Sharing Knowledge Between Universities Using Systematic Literature Review Fernando, Ricky; Sama, Hendi
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1733

Abstract

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
Pengembangan Aplikasi Bengkel Las di Kediri dengan Metode Extreme Programming Lisdiyanto, Angga; Nugroho, Rizky Aditya; Andhyka, Awang; Wibowo, Agus; Winarti, Winarti; Budiman, Budiman
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1740

Abstract

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.
Deteksi Sampah Botol Plastik di Perairan Menggunakan YOLO v4-Tiny Nur Santoso, Ubaidillah Ramadhan; Gamar, Farida
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 1 (2025): Januari 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i1.1744

Abstract

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.

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