JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi

Evaluasi Kinerja Tata Kelola Teknologi Informasi pada Perpustakaan Daerah Kota Salatiga Menggunakan Framework COBIT 2019

2026-05-08T04:37:25+00:00

Evaluation of Information Technology (IT) governance is necessary to ensure that technology utilization within an organization is effective, efficient, and aligned with established strategic objectives. This study aims to analyze the performance of IT governance at the Salatiga City Regional Library using the COBIT 2019 framework. The data collection process was conducted through interviews with parties involved in the management of IT services within the library environment. The data obtained were then analyzed using the SWOT approach to identify strengths, weaknesses, opportunities, and threats in the implementation of information technology governance. The study focused on the BAI05 (Managed Organizational Change) process within the COBIT 2019 framework. The analysis was conducted by comparing the current state of IT governance with the expected level of capability. The evaluation results show that the measurement of process capabilities not only refers to the COBIT 2019 standard indicators, but is also adjusted to the library's operational needs, such as collection digitization, implementation of library automation systems, and development of online-based information services. Based on the analysis results, it is recommended that the Salatiga City Regional Library form a special team for IT governance implementation that is able to ensure alignment between the organization's vision and the utilization of information technology. In addition, it is necessary to improve communication and socialization of IT strategies to all stakeholders to support the transformation of technology-based library services.

Deteksi Malware IoT Menggunakan K-Nearest Neighbor pada Dataset IoT-23

2026-05-08T04:30:45+00:00

The development of the Internet of Things (IoT) has increased the number of interconnected devices across various
sectors; however, it also introduces security challenges due to limited resources and weak protection mechanisms.
These conditions make IoT devices vulnerable to cyberattacks such as malware, botnets, and Distributed Denial
of Service (DDoS). Therefore, an effective and efficient intrusion detection system is required. This study aims to
analyze the characteristics of malware traffic and evaluate the performance of the K-Nearest Neighbor (KNN)
algorithm in detecting malicious traffic using the IoT-23 dataset based on network flow. The method employed is
supervised machine learning with preprocessing stages including data cleaning, label transformation, feature
encoding, and normalization using MinMaxScaler. The dataset is classified into two classes, namely benign and
malicious. The experimental results show that KNN is able to achieve an accuracy of up to 97%, with optimal
performance at K = 5, which provides the best balance between precision, recall, and F1-score. The ROC-AUC
value of 0.97 indicates that the model has a very good capability in distinguishing between normal and malicious
traffic. These results indicate that KNN based on network flow is effective and has the potential to be implemented
in intrusion detection systems in IoT environments.

Systematic Literature Review Pengembangan Document Management System (DMS) untuk Pengelolaan Dokumen Jaminan Kredit

2026-05-08T06:14:20+00:00

The digital transformation of the banking sector demands efficient and secure document management, positioning the Document Management System (DMS) as a strategic solution, particularly for managing credit collateral documents. This study conducts a Systematic Literature Review (SLR) of 30 articles published between 2015 and 2025 using the PRISMA methodology.[1]. The analysis identifies five major research themes: integration of emerging technologies (blockchain, OCR, cloud computing), security and regulatory compliance, business process efficiency and decision-making, DMS applications in the public and banking sectors, and evaluation of effectiveness and Return on Investment (ROI). While previous studies confirm that DMS improves accuracy, transparency, and processing speed, limited research has examined DMS integration with core banking systems, ROI assessment, and its impact on credit risk. This study recommends developing an integrated DMS model connected to banking APIs (Application Programming Interface) and enhanced with blockchain and Optical Character Recognition (OCR) / Natural Language Processing (NLP) technologies to support automated verification and strengthen the security of collateral documents.

Analisis Risiko Penggunaan Sistem Pembayaran UKT Virtual Account Mahasiswa UIGM Menggunakan ISO 31000

2026-06-22T04:09:22+00:00

The application of information technology through a Virtual Account system in the payment of Single Tuition Fees (UKT) at Universitas Indo Global Mandiri aims to increase efficiency and transparency in the transaction process. However, in its implementation there are still a number of operational risks that can hinder the payment administration process. This study aims to analyze and provide risk mitigation suggestions in the Virtual Account-based UKT payment system by implementing the ISO 31000 method. The research method used is a quantitative descriptive through a case study approach, involving 40 student respondents. Data collection techniques were carried out through observation, literature studies, and questionnaire distribution. The results of the study indicate there are five main risks, namely system disruptions, late payments, failed transactions, unverified payments, and Virtual Account input errors. Based on the analysis results, most risks are in the high category (High), where the risk of system disruption recorded the highest value of 12.61. Therefore, preventive measures are needed in the form of routine system maintenance, server monitoring, and improving transaction verification mechanisms to reduce the risks that occur.

Analisis Manajemen Risiko TI Menggunakan ISO31000 Pada PT ABC

2026-06-15T09:51:15+00:00

PT ABC is a pawn-based financial service company that relies on information technology to support operational activities at the head office and branches. This study aims to analyze IT risk management using the ISO31000 framework. The research used a qualitative case study approach through interviews, observation, and internal document review. The risk management process included communication and consultation, scope and criteria determination, risk assessment, risk treatment, recording and reporting, and monitoring and review. The results identified 21 IT risks related to hardware, software, networks, security, and operational procedures. Based on the risk evaluation matrix, 4 risks were classified as High, namely server down, slow system performance, 502 gateway, and server overload, while 17 risks were classified as Medium. The recommended risk treatments include increasing server capacity, monitoring system performance, strengthening network security, improving SOPs, managing access rights, and conducting regular risk review.

Key Words: Information Technology, ISO31000, Qualitative Study, Risk Management, Risk Treatment

Analisis Prioritas Risiko Penggunaan Aplikasi GOJEK Menggunakan Metode FMEA Pada Mahasiswa UIGM

2026-06-25T01:43:02+00:00

For students, the Gojek app is an instant and efficient way to carry out daily activities without having to leave the house. Although Gojek offers many conveniences for students, this application still has risks that can be detrimental to both users and service providers. The purpose of this study is to identify and analyze risks in the Gojek application using the Failure Mode and Effects Analysis (FMEA) method. Using this method, we can determine the level of risk management through a value called the risk priority number. This study uses a descriptive quantitative approach by collecting respondents of 100 students. Data collected through questionnaires were analyzed based on Severity, Occurrence, and Detection to obtain the Risk Priority Number (RPN) value. The results show that the highest risk is driver refusal to accept the location. Other high risks include OTP fraud, failed GoPay refunds, GoSend delays, and unilateral order cancellations. These results indicate that operational risks are the top priority, followed by security and financial aspects, so improvements are needed to improve service quality, system security, and transaction transparency. This research makes a meaningful contribution to understanding the risk management of the Gojek application, by providing appropriate analysis on real data to be used in improving the Gojek application.

Confidential Virtual Machines Untuk Keamanan Data Sensitif Desain Arsitektur, Overhead Kinerja, Dan Strategi Penempatan Beban Kerja

2026-06-25T01:44:28+00:00

Virtualization is a key foundation of modern cloud computing, yet the multi-tenant model in conventional virtualized environments still leaves weaknesses in protecting data in use, namely data being processed in memory. This study develops and evaluates a secure virtualization model based on Confidential Virtual Machines (CVMs) by focusing on three aspects: CVM architecture design, performance overhead under heterogeneous workloads, and a security-aware workload placement strategy based on data sensitivity. A quantitative experimental approach compares conventional virtual machines and CVMs on CPU-intensive, memory-intensive, I/O-intensive, and sensitive-data workloads. Three placement strategies are also evaluated: random placement, performance-based placement, and security-aware placement. The results show that CVMs strengthen data-in-use protection by reducing host visibility into guest memory and supporting attestation. From a performance perspective, CVM overhead remains relatively low for compute-dominant workloads, but becomes more visible for memory- and I/O-sensitive workloads, particularly network-intensive execution. The placement evaluation shows that security-aware placement provides the best balance between security and performance by prioritizing sensitive workloads on CVM-enabled environments without excessive loss of system efficiency. Thus, selective CVM adoption based on data sensitivity is a practical approach for supporting secure virtualization in modern cloud infrastructures.

Perbandingan Kinerja Filter Citr Evaluasi Filter Spasial untuk Reduksi Noise dan Deteksi Tepi pada Citra CCTV

2026-06-01T08:40:59+00:00

Digital images generated by Closed Circuit Television (CCTV) cameras play an important role in security systems. However, these images often experience quality degradation due to noise interference, complicating the identification process. Therefore, this study aims to compare the effectiveness of three spatial filtering methods: Gaussian Filter, Median Filter, and Sobel Filter. The comparative experiment uses the Python programming language and OpenCV library. The testing applies low-pass filters (Gaussian and Median) to reduce noise, and a high-pass filter (Sobel) for edge detection. Image quality is evaluated objectively using Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) parameters. The results indicate that filtering performance depends heavily on the type of noise. The Median Filter is superior in reducing impulsive noise while preserving details, whereas the Gaussian Filter is optimal for normally distributed noise. Meanwhile, the Sobel Filter is highly effective in extracting object boundary lines after the image smoothing stage. In conclusion, selecting the appropriate filtering method based on noise characteristics is crucial to produce optimal surveillance image quality.

Analisis Komparatif Representasi Frekuensi dan Kualitas Rekonstruksi Citra Digital Menggunakan Algoritma FFT dan DWT Haar

2026-06-23T02:36:29+00:00

Image processing in the spatial domain has limitations in computation and detailed analysis, so transformation to the frequency domain is a solution. This study aims to compare the Haar Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) methods on the frequency representation and quality of digital image reconstruction. The test was conducted using the Python programming language on Cameraman and Lena grayscale images with dimensions of 256x256 pixels. The quality of the reconstruction image was evaluated quantitatively using the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) parameters. Visual results show that FFT effectively concentrates intensity globally on the DC Coefficient but loses spatial information, whereas DWT Haar is able to maintain its original spatial structure in the Approximation sub-band. At the reconstruction stage, both methods were proven to reconstruct the image perfectly (lossless) with an MSE error of 0.0000. The FFT method yielded a PSNR value of 324.14 dB, slightly higher than the DWT of 316.22 dB. In conclusion, although FFT has a slight advantage quantitatively, DWT Haar is considered more adaptive and functional for modern image processing applications such as compression and noise reduction due to its ability to localize object details.

Implementasi Pencocokan Citra Menggunakan Metode ORB untuk Deteksi Logo Kemasan Produk

2026-06-16T03:52:01+00:00

This study evaluates the reliability of the Oriented FAST and Rotated BRIEF (ORB) algorithm for image matching and logo detection on product packaging in dynamic real-world environments. In modern industry, object detection is closely related to logo identification for automation. Testing was conducted through a series of systematic experiments covering variations in rotation, drastic scale changes, and background clutter. Pre-processing was done with grayscale conversion, followed by feature extraction using ORB, and matching using the Brute-Force Matcher with Hamming Distance. To filter out false matches, this algorithm was optimized with K-Nearest Neighbor (KNN), Lowe's Ratio Test, and RANSAC geometric filtering. Experimental results show that ORB optimization with KNN and RANSAC drastically reduces computation time to 0.2412 seconds and produces 51 valid inliers. However, despite being highly efficient for real-time applications, the ORB method remains fundamentally limited when facing extreme scale variance. Therefore, this system is optimally recommended only in controlled environments like factory conveyors. Alternative approaches using Deep Learning or scale-invariant algorithms (SIFT/SURF) are highly suggested for dynamic environment implementation.