Jurnal PROCESSOR

Analisis Keamanan Aplikasi Web Menggunakan Penetration Testing Berdasarkan Standar OWASP Pada DVWA

2026-02-17T08:22:18+07:00

Web-based applications currently serve as the vital infrastructure for public and private services. However, this widespread adoption is often not matched by adequate security standards, creating a digital ecosystem vulnerable to exploitation by malicious actors. This study aims to analyze the exploitation mechanisms of critical web application vulnerabilities and formulate effective mitigation strategies to prevent cyber attacks. The research utilizes the Damn Vulnerable Web App (DVWA) simulated in a local server environment using a Black Box Testing approach. This study adopts the Penetration Testing Execution Standard (PTES), which includes information gathering, vulnerability scanning, exploitation, and reporting stages. The testing focuses on two of the most critical attack vectors according to the OWASP Top 10 standard: SQL Injection and Stored Cross-Site Scripting (XSS). The results indicate that at the 'Low Security' level, the application is highly susceptible to injection attacks. SQL Injection attacks successfully exposed all user data within the database, threatening confidentiality, while Stored XSS attacks succeeded in permanently embedding malicious scripts that could attack other users from the client-side. This study concludes that application security must be strengthened from the source code level (secure coding), rather than relying solely on network infrastructure. Recommended mitigation solutions include the implementation of Prepared Statements to prevent query manipulation and Input Sanitization using the htmlspecialchars function to prevent foreign script execution.

Analisis Komparatif K-Means dan DBSCAN pada Data Nilai Siswa SMP Bina Bangsa Surabaya

2025-12-22T10:56:52+07:00

This study aims to analyze and compare the effectiveness of the K-Means and DBSCAN algorithms in clustering student score data for Grade VIII B students at SMP Bina Bangsa Surabaya. The dataset consists of 24 students and includes three main subjects: Mathematics, Indonesian Language, and Natural Sciences (IPA). Using a quantitative approach with a comparative experimental method, data preprocessing, normalization, and algorithm implementation were conducted on the Google Colab platform. The results show that the K-Means algorithm performs optimally with three clusters representing low, medium, and high academic performance, supported by the highest Silhouette Score at k = 3. Meanwhile, DBSCAN generated two main clusters, namely Remedial (17 students) and Non-Remedial (6 students), and identified two noise data points representing students with significantly different score patterns. These findings indicate that clustering methods are effective in helping teachers identify students’ learning needs and design more targeted academic interventions. Overall, the application of clustering proves beneficial in managing academically heterogeneous classrooms and enhancing the efficiency of instructional strategies..

Optimizing the Selection of 250cc Motorcycles in the Automotive Industry Using the AHP and TOPSIS Methods

2024-08-29T14:13:07+07:00

This research aims to optimize the selection of the best 250cc motorbike using the Analytical Hierarchy Process (AHP) method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Specification data from six 250cc motorbike models from various brands such as Yamaha MT25, Yamaha R25, Honda CBR 250RR, Kawasaki All New Ninja, Kawasaki ZX25R, and Suzuki Gixxer SF 250 were used as the basis for the analysis. Each model is evaluated based on criteria such as motorbike type, engine specifications, engine cooling, maximum power, maximum torque, frame type, front suspension, rear suspension and tank capacity. The AHP method is used to determine criteria weights through pairwise comparisons which produce a comparison matrix and relative weights for each criterion. Next, TOPSIS is used to determine the motor rating based on the distance from the positive and negative ideal solutions. This process involves normalizing the decision matrix, weighting, and calculating the Euclidean distance of each motor alternative to the ideal solution. To simplify analysis and calculations, a web-based system was developed. This system allows users to enter motorbike specification data, perform AHP and TOPSIS calculations, and display ranking results in real-time. The research results show that the combination of AHP and TOPSIS can provide comprehensive and accurate recommendations in selecting the best 250cc motorbike, thereby helping consumers make more informative and optimal decisions.

Visualisasi dan Penelusuran Relasi Jabatan Akademik Menggunakan Algoritma Breadth First Search Berbasis Web

2026-03-11T13:53:07+07:00

This study implements the Breadth First Search (BFS) algorithm to visualize university organizational structures, simplifying the tracing of command lines. The primary issue is the difficulty of understanding position relationships in complex static charts. Utilizing the CodeIgniter 4 framework, the BFS algorithm is applied to process hierarchical data level-by-level from a relational database. The results demonstrate that the integration of BFS and pathfinding functions successfully identifies the shortest coordination paths accurately. The system dynamically isolates and highlights the path from top leadership to the target position. This study concludes that BFS effectively improves bureaucratic tracing efficiency and simplifies the understanding of organizational relationships through interactive visualization.

Analisis Kepuasan Mahasiswa terhadap Pembelajaran ERP Menggunakan Software Odoo pada Prodi Manajemen Teknologi Rekayasa

2026-02-17T08:19:52+07:00

This study aims to analyze student satisfaction with Enterprise Resource Planning (ERP) learning using the Odoo software in the Manajemen Teknologi Rekayasa Study Program. ERP learning plays an increasingly important role in higher education as the system has been widely implemented acroos various industries, making it necessary to evaluate how well the learning process meets student needs, making it necessary to evaluate how well the learning process meets student needs. The research instrument adopts the End User Computing Satisfaction (EUCS) model, consisting of five dimensions: Content, Accuracy, Format, Ease of Use, and Timeliness. Primary data were collected through a questionnaire distributed to 53 students who had participated in the Odoo-based ERP practicum. Validity testing using the Pearson Product-Moment correlation shows that all items are valid, while reliability testing using Cronbach’s Alpha produced a value of 0.873, indicating a high level of internal consistency. The percentage analysis reveals that all dimensions fall into the satisfied category, with an overall satisfaction average of 65.95%. These findings indicate that ERP learning using Odoo provides a satisfactory learning experience for students. This study serves as an initial reference for improving ERP learning implementation and provides foundational insights for future research on factors influencing user satisfaction in information-system-based learning environments.

Implementation of Steganography Encryption and Decryption Methods on Digital Images in Web-Based Applications

2025-11-14T21:11:07+07:00

The sending and receiving of messages through information technology often faces the threat of cyber-attacks that could potentially result in the modification or theft of sensitive information, especially in corporate environments. To address such risks, cryptography and steganography techniques have become effective solutions in protecting data during transmission. This research aims to implement a steganography-based encryption and decryption method on digital images through a web-based application, using the Least Significant Bit (LSB) approach. This method is designed to hide secret messages in images without significantly affecting their visual quality. The research was conducted using a quantitative approach with experiments aimed at developing and testing web-based software.The test results show that the developed method has a very small margin of error, which is 0.000220, based on the calculation of Mean Squared Error (MSE). In addition, the Peak Signal-to-Noise Ratio (PSNR) value of 84.7 proves that the quality of the steganography image is very close to the original image. These findings show that the developed software is not only effective in hiding information, but also able to maintain the visual quality of the image very well. This research makes a significant contribution to the development of web-based data security solutions, while offering a practical approach to protecting sensitive information in the digital age.

Designing a Low-Latency, Adaptive Cybersecurity Simulator: A Hybrid Architecture of Stochastic Generation and Deterministic Validation

2026-04-08T11:29:20+07:00

Cybersecurity training is usually plagued by a lack of individuality when it comes to the scenarios presented, which tends to make students memorize instead of understand. In this paper is presented NODEZERO, a browser based simulator to automatically create new educational content. Using Design Science Research We created a lightweight Single Page Application that fused a two-part procedural generation algorithm with a deterministic Finite State Machine (FSM). The hybrid design randomises network topologies and encryption settings and the FSM verifies what the users are doing using a state-based tool selection system. Results show that NODEZERO produces unique missions (no noticeable delay); frame times are below 16 ms. Functional tests have shown that Difficulty Multiplier adjusts the complexity of each mission for difficulty: experts receive difficult levels and beginners receive easy levels. The research shows that the combination of stochastic creation of environment and deterministic validation is an scalable "infinite drilling" solution that avoids manual content creation.