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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pendidikan Terbuka Dan Jarak Jauh SENTIA 2015 JURNAL PETIK Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Informatika Polinema (JIP) Jurnal ilmiah teknologi informasi Asia
Mayang Anglingsari Putri, Mayang Anglingsari
Universitas Terbuka
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences

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Data Encryption and Security in Data Storage Management Information System Using Blowfish Algorithm Putri, Mayang Anglingsari; Trihapningsari, Denisha; Hapsani, Anggi Gustiningsih; Putri, Chandra Sina
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 16, No 2 (2024): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v16i2.28893

Abstract

Documents and archives is an important part of BPAD (Badan Perpustakaan Arsip dan Dokumentasi) Malang because the main task is the management of archives. But in its management, mail archiving, as well as the approval letter is still done manually and there is no security of its data. With this system is expected to help to manage and document all messages are in BPAD (National Library of Archives and Documentation) Malang. Both incoming and outgoing mail. Letters contained in the system is also secured by means of encryption using the Blowfish algorithm to secure data archive important letters so that data is safe and away from the risk of this manipulation. Aplication can simplify the process of collecting data, archive storage and secure image archive in poor districts BPAD use blowfish algorithm so that data is safe and away from the risk of misuse.
Evaluating User Experience (UX) on Universitas Terbuka’s Website: A Combined Survey and GTMetrix Performance Analysis Putri, Mayang Anglingsari; Trihapningsari, Denisha; Nurdiana, Dian
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.32094

Abstract

The Universitas Terbuka (UT) website serves as the primary platform for providing academic services and information to students, lecturers, and the general public. However, as the number of users and the complexity of digital services increase, User Experience (UX) becomes a crucial aspect that influences the effectiveness and user satisfaction in accessing information and utilizing available features. This study aims to evaluate and analyze the user experience of the Universitas Terbuka website using a combined approach, incorporating survey questionnaires and web performance analysis. The urgency of this research lies in the need to ensure that the UT website delivers an optimal experience for its users, particularly in terms of ease of navigation, access speed, information clarity, and responsiveness across different devices. With the growing reliance on digital systems in distance learning, UX evaluation becomes a strategic step in identifying challenges and opportunities for improvement. The novelty of this study lies in its holistic approach, which integrates subjective user feedback from surveys with objective web performance analysis. The findings of this research are expected to provide concrete recommendations for enhancing the UX quality of the Universitas Terbuka website, thereby supporting the effectiveness of distance learning and improving access to academic services.
Comparison of the SAW (Simple Additive Weighting), AHP (Analytic Hierarchy Process) and Wieghted Product (WP) Methods in Catering Vendor Selection Sufandi, Unggul Utan; Putri, Mayang Anglingsari; Satria Junianto, Mochamad Bagoes; Minrohayati, Minrohayati
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.31854

Abstract

This study aims to develop a Decision Support System (DSS) for selecting the most suitable catering vendor for the UT Business Center by employing three decision-making methods: Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP), and Weighted Product (WP), alongside expert evaluation. Selecting an appropriate catering vendor is crucial to supporting university operations and events; therefore, the decision-making process must be based on objective and efficient criteria. Given the differences in the working principles of these three methods, it is essential to conduct a comparative analysis between AHP, SAW, and WP to determine the most suitable approach for catering vendor selection at the UT Business Center. The results of the study indicate varying levels of accuracy depending on the weighting scenario: Scenario 1 (Uniform Criterion Weights): Accuracy levels were AHP (83.33%), SAW (100%), and WP (100%). Scenario 2 (Expert-Determined Criterion Weights): Accuracy levels were AHP (58.83%), SAW (66.67%), and WP (66.67%).
Comparison Various Analytical Approaches to Find The Most Efficient and Effective Method for Peak Hour Identification Hapsani, Anggi Gustiningsih; Putri, Mayang Anglingsari
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 2 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i2.29193

Abstract

The Peak hour sales identification is essential to manage staff, inventory, and service capacity in coffee shop operations. This study compares an exploratory heatmap with two forecasting models, linear regression and Seasonal ARIMA (SARIMA) using six months of hourly transaction data from a coffee shop (1 March–17 August 2024) . The heatmap offers rapid visual recognition of high traffic periods but provides no predictive capability. For prediction, this study trained a linear regression and a SARIMA specification tuned by standard diagnostics; model performance was assessed on a held out set using MAE, RMSE, and MAPE. Linear regression yielded RMSE = 6.68, MAE = 5.40, and MAPE = 138.06%, indicating inadequate fit for intraday demand dynamics. In contrast, SARIMA achieved RMSE = 0.828, MAE = 0.557, and MAPE = 40.34%, substantially reducing error by explicitly modeling autocorrelation and recurrent seasonal cycles. The results show that seasonality aware time series modeling delivers actionable, interpretable forecasts for near term operational planning (such as staffing and product preparation). Overall, the proposed pipeline, heatmap for rapid situational awareness plus SARIMA for prediction, constitutes a practical baseline for peak hour identification in small scale retail.
Co-Authors Dwi Astuti Aprijani Hapsani, Anggi Gustiningsih Hasan Basri Indra Dharma Wijaya Indra Dharma Wijaya Indra Dharma Wijaya, Indra Dharma Irpan Kusyadi Irpan Kusyadi Ismiarta Aknuranda Junianto, Mochamad Bagoes Satria Minrohayati . Mochamad Bagoes Satria J Mutiara Ulfah Nurdiana, Dian Pardamean Daulay Putri, Chandra Sina Rosadi, Raesita Rakhmawati Setia Budi, Agung Siwi Pradini, Risqy Syaikhu, Ahmad Trihapningsari , Denisha Trihapningsari Trihapningsari, Denisha Unggul Utan Sufandi Wayan Firdaus Mahmudy Zikriyani, Hikmah