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Jurnal Ilmiah Matrik Jurnal Ilmiah Terpadu (JIT) Universitas Bina Darma Jalan Jenderal Ahmad Yani No. 3, Gedung Bochari Rachman 1, Universitas Bina Darma, Kota Palembang, Indonesia.
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Jurnal Ilmiah Matrik
Published by Universitas Bina Darma
ISSN : 14111624     EISSN : 26218089     DOI : https://doi.org/10.33557/jurnalmatrik
Core Subject : Science,
Computer Science & IT
Peringkat Akreditasi Jurnal Ilmiah Periode III Tahun 2022 KEPUTUSAN DIREKTUR JENDERAL PENDIDIKAN TINGGI, RISET, DAN TEKNOLOGI KEMENTERIAN PENDIDIKAN, KEBUDAYAAN, RISET, DAN TEKNOLOGI REPUBLIK INDONESIA NOMOR 225/E/KPT/2022 TENTANG PERINGKAT AKREDITASI JURNAL ILMIAH PERIODE III TAHUN 2022. Jurnal Ilmiah MATRIK telah terakreditasi SINTA dengan Peringkat 4 The Journal of Scientific MATRIK ISSN: 1411-1624, E-ISSN: 2621-8089. was published in collaboration between the Faculty of Computer Science (FIK) with Integrated Scientific Journal (JIT-UBD) and Publishing and Printing Center of Bina Darma Press University (PPP-UBD Press). The results of research and theoretical studies in the journal Matrik in Computer Science. Publication conducted 3 (three) times (April, August and December). The editorial board welcomes original submissions in Indonesia and English. The number of words for a research article should preferably be between 5,000 and 8,000. Each of the articles published have a DOI (Digital Object Identifier). The paper will be checked for plagiarism using Turnitin.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 449 Documents
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Rancang Bangun E-Catering Pada CV. Lembaga Palembang Ardiansyah, Muhammad Ridho; Sayuti, Akhmad; Nurhasanah
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/17yxbj58

Abstract

The catering service sector in Palembang faces significant challenges in adapting to the digital era, particularly concerning operational efficiency and customer satisfaction. Manual business processes still implemented by CV. Lembaga, ranging from ordering to customer data management and delivery schedule arrangements, have proven to be time-consuming for consumers and potentially lead to errors. This research aims to design and develop a web-based e-catering system for CV. Lembaga Palembang as an innovative solution. Adopting the iterative cycle of the prototype method, this study involves stages of planning and requirements analysis, system design, initial prototype construction, testing and evaluation, and implementation. System design will be visualized using Unified Modeling Language (UML), including Use Case Diagrams for user functionality, Activity Diagrams for process flows, and Class Diagrams for data structures. This process aligns with the need for rapid validation and adaptation to changes. System acceptance by users will be analyzed using the Technology Acceptance Model (TAM), focusing on Perceived Usefulness and Perceived Ease of Use as key determinants of adoption. The resulting e-catering design is expected to automate CV. Lembaga's business processes , enhance operational efficiency , expand its market reach , and provide convenience, thereby improving customer satisfaction through integrated digital services.
Prototipe  Sistem  Tiket Layanan  Digital  Di  PLN UP 3 Ampera  Palembang Arya Puje Arsane, Kadek; Abdillah, Leon A.
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/zartr316

Abstract

Digital transformation has become a crucial strategy in improving public service quality across various sectors, including the energy and electricity industry. This article describes the creation of a prototype digital service ticket system at PLN UP 3 Ampera Palembang, which aims to improve the efficiency and accuracy of customer service administration.  The current manual procedure frequently resulted in delays, data discrepancies, and issues monitoring service requests. In this regard, PT PLN (Persero) S2JB Ampera Branch in Jakabaring has taken an innovative step by designing and implementing a digital ticketing system. This system was specifically developed to replace the previously manual service process, which was often slow, inefficient, and lacked transparency. Using a prototype development method, the system was built in an iterative manner, involving end users directly during the testing phase. The implementation results demonstrate that the digital ticketing system successfully streamlines customer service workflows, enhances customer satisfaction, and simplifies the tasks of field officers in recording and responding to reports or complaints.
Optimasi Kontras Dan Ketajaman Citra Pada Pengenalan Makanan Indonesia Berbasis Machine Learning Ummah, Khanun Roisatul; Priyawati, Diah; Badriyah, Jamilatul
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/g9afej42

Abstract

Indonesia has a rich culinary diversity, encompassing various types of food from different regions. In the current era of technological advancement, the application of artificial intelligence has grown significantly across multiple sectors, including in the identification of Indonesian food images. This research provides the impact of various image preprocessing techniques on the AI-based food identification system. The preprocessing methods examined include Zero Component Analysis (ZCA), Histogram Equalization (HE), Contrast Stretching, and Image Sharpening. The evaluation of these preprocessing methods was conducted to determine which technique provides the best performance in assisting the identification of Indonesian food using a Convolutional Neural Network (CNN) with a ResNet-50 transfer learning model. Performance measurement was carried out using a confusion matrix by calculating Accuracy, precision, recall, and F1-score. The results of this research show that the use of the Image Sharpening method yields higher accuracy and precision on the testing data compared to other methods, those are 0.9748 and 0.98, respectively. Next, a high level of accuracy was also demonstrated by the Contrast Stretching method, with an accuracy score of 0.9712.
Contextualized Word Embedding Untuk Ekstraksi Kutipan Berita Indonesia Khairina, Syifa; Saffa, Nayara; Lieharyani, Djoko Cahyo Utomo; Hutahaean, Jonner
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/2ayqqa48

Abstract

This study aims to develop a Named Entity Recognition (NER) model based on Recurrent Neural Networks (RNN) to extract direct quotes from Indonesian news articles, with a focus on enhancing the Medmon system by Kabayan Group, which is used to monitor the public image of public figures and brands. The study is limited to Indonesian news articles and does not include other languages or news sources. Two models are compared in this research: one utilizing static word embedding Word2Vec and the other using contextual word embedding BERT. The experiment was conducted using PFSA-ID corpus, which consist 1,018 Indonesian news articles annotated for direct quotes using BILOU scheme. Both models were trained and evaluated using Python programming libraries such as Pytorch and Hugging Face Transformers. The results show that the BERT model outperforms Word2Vec, with an F1-Score difference of 14.03 points. The BERT model achieved a highest F1-Score of 92.28%, while Word2Vec only reached 78.05%. This research contributes to the field of online media monitoring by improving the efficiency and accuracy of direct quote extraction in Indonesian news, offering practical value for media analysts and organizations relying on automated media analysis
Evaluation of Computer Lab at XYZ Institution using BAI & DSS Domains of COBIT 2019 Febriawan, Dimas; Kamayani, Mia; Imanda, Rahmi
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/wsbeqv24

Abstract

This research aims to measure the IT governance implementation in the computer laboratory at XYZ Institution using COBIT 2019 framework. Based on the scope and the problems that were identified, BAI and DSS aspects are the domains chosen to measure the implementation of the IT governance. The methods for this research are focus group discussion and field assessment. The BAI and DSS domains consist of 16 objectives, which are then divided into 104 practices and then divided further into 535 activities. These 535 activities are the processes that we have to determine for each capability level. After determining the capability levels for each process, we summarized the values and then evaluated the average values for each objective. These average values are the values that we used to determine the capability levels for each objective. We presented the result of our self assessment using a radar diagram. XYZ Institution is still in the starting phase of having good IT governance. This condition is reflected by the achievement of each objective’s capability levels ranging from 1 to 2. In addition to this condition, there is only one objective that meets the Institution’s capability level target of 3.
Analisis Tren Historis Dan Prediksi Beban Listrik Pada Tenaga Listrik Menggunakan Artificial Neural Network Dengan Metode Backpropagation: Systematic Literature Review Septient Malini, Regina; Sahroni, Alvin; Setiawan, Hendra
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/8kyfgz81

Abstract

Electric load forecasting is a critical step in ensuring the reliability of power systems amid rising energy demand driven by digitalization, industrialization, and urbanization. This article presents a Systematic Literature Review (SLR) on the application of Artificial Neural Networks (ANN) with backpropagation algorithms for load prediction based on historical data, employing the PRISMA framework for study screening and selection. The review analyzes nine relevant national journals to identify trends in accuracy, network configurations, and model effectiveness. Findings indicate that ANN with backpropagation can achieve low prediction error rates, such as a Mean Absolute Percentage Error (MAPE) of 0.05% in industrial sectors and up to 99.88% accuracy in specific cases. ANN also demonstrates strong capability in capturing dynamic changes in energy consumption, making it a reliable method for supporting operational planning and efficient electricity distribution. Despite promising performance, several aspects remain underexplored, including more complex ANN architectures, hyperparameter tuning techniques, limited cross-regional validation, and insufficient comparative analysis with alternative methods such as ensemble learning or deep learning-based algorithms. This review offers comprehensive insights into the integration of artificial intelligence in power systems and lays the groundwork for developing more adaptive, precise, and broadly generalizable load forecasting strategies in the future.
Sistem Informasi Penstabilan Distribusi Sembako Pengendalian Inflasi pada Pasar Tradisional  di  Minahasa Utara Sahulata, Reynoldus Andrias
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/zfex2x61

Abstract

The increasing demand for basic necessities in North Minahasa, North Sulawesi, has not been matched by adequate supply, resulting in high inflation in three traditional markets: Airmadidi (28.5%), Sukur (24.3%), and Kauditan (32.5%). Price hikes indicate the urgent need for effective distribution strategies to stabilize staple food availability. Efforts to address this issue began with the immediate distribution of sufficient supplies, successfully reducing inflation to 18.5% in Airmadidi, 15.2% in Sukur, and 22.1% in Kauditan. Further improvements through continuous distribution lowered inflation to 3.2%, 2.8%, and 4.1% respectively. When supply eventually exceeded consumer demand, inflation rates shifted into deflation, recorded at -2.1% in Airmadidi, -1.8% in Sukur, and -2.5% in Kauditan. These results demonstrate that systematic and sustainable supply chain management can effectively stabilize market conditions. The study was conducted between January 2024 and May 2025, using data from the Central Statistics Agency (BPS) of North Sulawesi in the form of the Consumer Price Index (CPI/IHK), complemented by data from the Minahasa Regency Trade Office, and field surveys and interviews with 50 traders in each market. Based on these findings, an Information System for Stabilizing the Distribution of Staple Foodstuffs and Controlling Inflation in Traditional Markets in North Minahasa is proposed as a strategic solution to support regional economic stability.
Perancangan UI/UX Aplikasi Mobile Marketplace Barbershop Barbergo Dengan Metode User Centered Design Nasywa Zahira Ramadhani; Seftin Fitri Ana Wati; Anindo Saka Fitri
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/4j3qxa16

Abstract

This research aims to produce interface design solutions and user experience for the mobile application of the BarberGo barbershop marketplace using the User Centered Design method. The research method used involves four main stages of User Centered Design consisting of Understand and Specify The Context of Use, Specify The User Requirements, Produce Design Solutions, and Evaluate The Design Against Requirements. Data collection through literature study methods and interviews with each of the five customer and barbershop respondents. The interview results were then processed and analyzed to obtain interface design solutions that have good usability values. The results of this study show a significant comparison between the results of the usability evaluation in the first and second stages. In the results of the usability level evaluation, from the customer side there was an increase in usability value of 18.16% with a final result of 80.74% and the barbershop experienced an increase in usability value of 17.19% with a final result of 82.28%. In the evaluation results of the System Usability Scale (SUS), from the customer side, there was an increase in value of 27 with a final result of 93 and the barbershop experienced an increase in value of 26 with a final result of 94. Based on these results, it shows that the interface design of the BarberGo barbershop marketplace mobile application has a good level of usability, and can be accepted and is suitable for use by users.
Penerapan Model Machine Learning untuk Memprediksi Serangan Jantung Dini Mandias, Green Ferry; Manoppo, Ivanna Junamel
Jurnal Ilmiah Matrik Vol. 27 No. 2 (2025): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/2cg02a51

Abstract

Heart disease is one of the leading causes of death worldwide, and early detection is crucial in reducing mortality rates. In Indonesia, heart disease is a primary cause of death, exacerbated by limited access to healthcare, especially in rural areas. Traditional diagnostic methods, such as physical examinations and EKG, often lack accuracy in predicting heart attacks. This research aims to develop an early prediction model for heart attacks using machine learning, specifically Random Forest and Support Vector Machine (SVM). These models were trained using a dataset containing various medical variables, including age, gender, blood pressure, cholesterol levels, and ECG results. The study finds that the Random Forest model outperforms SVM, with an accuracy of 90% and a recall of 93% for heart disease detection, making it more reliable for early detection of at-risk patients. The results suggest that machine learning can significantly enhance early heart attack detection, offering a potential solution to reduce heart disease-related mortality.
Development of a Web-Based Free Homecoming Registration System by the Department of Transportation of South Sumatra Province Sahfitri, Vivi
Jurnal Ilmiah Matrik Vol. 26 No. 3 (2024): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/nxc8xs75

Abstract

This research aims to design and develop a web-based free homecoming registration system for the Department of Transportation of South Sumatra Province. The website is designed to assist administrators in managing and monitoring registrant data according to their travel routes, streamline the filtering process, and facilitate the storage and retrieval of large volumes of data. This improvement enables a more efficient registration process and accommodates an increasing number of participants each year. The development process employs Macromedia Dreamweaver 8 as the text editor, PHP as the programming language, phpMyAdmin for database management, and Google Chrome as the testing browser. The resulting website provides an integrated and user-friendly platform that enhances administrative efficiency and accessibility for registrants. The findings of this study are expected to contribute to better data management and service delivery within the Department of Transportation of South Sumatra Province

Page 44 of 45 | Total Record : 449

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