TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi

Analisis Kepuasan Mahasiswa Universitas Riau terhadap Website Wayground Menggunakan Pendekatan Webuse

Sun, 17 May 2026 00:00:00 +0700

The development of technology in the world of education has encouraged the use of digital platforms such as Wayground to support the learning process. However, there has not been much research evaluating the level of student satisfaction with the use of the platform. This study aims to analyze the satisfaction of Riau University students with the Wayground website using the WEBUSE (Website Usability Evaluation) approach. The research method used is a quantitative survey with a questionnaire instrument based on the WEBUSE dimensions, which include aspects of usability, information quality, user interaction, and technical performance. The data collected were tested using validity and reliability analysis, with the results showing that all instrument items have a level of validity and reliability that is included in the excellent category. Based on the results of the analysis, most students are satisfied with the performance and ease of use of the Wayground website. In conclusion, this platform is considered effective and worthy of continued use in online learning activities. This study is expected to be a reference in the development of an e-learning platform that is more responsive to user needs.

Perancangan Sistem Informasi Layanan pada CU Saut Maju Nauli Berbasis Web

Livvran Parulian Pakpahan, Eva Julia G. Harianja, Rena Nainggolan — Sun, 17 May 2026 00:00:00 +0700

The advancement of information technology has driven various sectors to adopt digital solutions, including financial institutions such as Credit Unions (CUs). CU Saut Maju Nauli, located in Humbang Hasundutan Regency, still operates using a manual system to manage member data and savings-loan transactions. This manual process is prone to data entry errors, data loss, and slow service delivery. This study aims to design a web-based service information system to improve the efficiency and effectiveness of CU operations. The research adopts the Waterfall development method, with a case study approach and data collection through interviews, observations, and literature review. The system is designed to manage membership data, savings, loans, and installment payments in a structured manner. The result of this research is expected to assist CU administrators in providing faster, more accurate, and more efficient services.

Literature Review Implementasi Algoritma AES (Advanced Encryption Standard) 256-bit untuk Meningkatkan Keamanan Data pada Layanan Cloud Storage

Sun, 17 May 2026 00:00:00 +0700

The rapid development of cloud storage services within cloud computing technology offers significant convenience for storing and managing digital data. However, this development also raises serious data security challenges, including risks of data leakage, theft, and unauthorized access. One widely used solution to address these issues is the implementation of cryptographic techniques, particularly the Advanced Encryption Standard (AES) algorithm with a 256-bit key length. This study aims to analyze the implementation of the AES 256-bit algorithm in enhancing data security in cloud storage services through a literature review approach. The study reviews ten relevant national and international journal articles discussing the application of AES-256 in digital storage systems and cloud computing environments. The results indicate that the AES 256-bit algorithm is effective in maintaining data confidentiality and integrity during both storage and transmission. The 256-bit key length provides a high level of security and strong resistance to cryptanalytic attacks. However, several studies also identify challenges related to processing time efficiency and encryption key management. Therefore, it can be concluded that AES 256-bit is a reliable solution for improving data security in cloud storage services, provided that its implementation is adapted to system requirements and supported by effective key management.

Perbandingan Metode K-Means dan DBSCAN untuk Clustering Teks Pesan Menfess di Telegram

Oktama Pangestu, Abdul Hamid Arribathi, Nur Azizah, Rahmat Hidayat — Sun, 17 May 2026 00:00:00 +0700

Menfess messages on Telegram are a form of anonymous communication that generates large amounts of informal text data with linguistic characteristics such as slang, abbreviations, and spelling variations, posing challenges for computational text analysis. This study compares the performance of K-Means and DBSCAN in clustering menfess messages using Sentence-BERT embedding through the paraphrase-multilingual-MiniLM-L12-v2 model across three text length scenarios: short (0–20 words), medium (55–128 words), and long (129–283 words), derived via word count clustering. Evaluation uses the Silhouette Score and Davies-Bouldin Index. For short texts, K-Means achieves 0.0804 and 3.8451, while DBSCAN produces 2 clusters with 0.3186, 1.3714, and 71.60% noise. For medium texts, K-Means obtains 0.1403 and 3.6490, while DBSCAN forms 1 cluster with 0.0450, 3.3405, and 74.60% noise. For long texts, K-Means obtains 0.0593 and 3.4552, while DBSCAN produces 2 clusters with 0.5492, 1.1069, and 79.67% noise. Results show that DBSCAN outperforms on short and long texts by evaluation metrics but produces very high noise across all scenarios, while K-Means demonstrates more stable performance by clustering all data without noise in every scenario.

Optimalisasi Convolutional Neural Network Kontra VGG16 Klasifikasi Citra Daun Sawi

Sun, 17 May 2026 00:00:00 +0700

Manual detection of pests on mustard greens (caisim) is a major constraint in reducing harvest productivity, as manual methods are inefficient, time-consuming, and require specialized expertise. Furthermore, deep learning models often suffer from overfitting when applied to limited agricultural datasets. This study aimed to develop and compare the effectiveness of a Convolutional Neural Network (CNN) from scratch model versus the VGG16 transfer learning architecture for automatic classification of healthy and pest-affected mustard leaf images. A dataset of 1,000 images was used for training and testing across four experimental scenarios (A to D), with Percobaan C being the optimized CNN from scratch model (using data augmentation) and Percobaan D using VGG16. The results showed that the VGG16 transfer learning model achieved the highest test accuracy of 95.0% (F1-score: 0.95), while the optimized CNN from scratch model achieved 92.0% (F1-score: 0.92). Therefore, transfer learning with VGG16 is the most effective and optimal approach, demonstrating superior performance and efficiency by achieving high accuracy without complex data augmentation.

Aplikasi Segmentasi Jenis Makanan Berdasarkan Kandungan Gizi Menggunakan Algoritma K-Means

Sun, 17 May 2026 00:00:00 +0700

Public understanding of food nutrition remains limited due to the lack of accessible educational tools. This study aims to develop a web-based food segmentation system capable of clustering food items based on their nutritional characteristics using the K-Means algorithm. The research employs the Food Composition Dataset, focusing on key attributes including nitrogen factor, fat factor, and specific gravity. The methodology consists of data preprocessing, determining the optimal number of clusters using the Elbow Method, and visualizing the clustering outcomes through Principal Component Analysis (PCA). The results indicate that the optimal number of clusters is K = 3, with clear separation demonstrated by PCA, which shows an explained variance of 82%. The resulting clusters represent groups of foods with similar nutritional profiles, such as high-protein, high-fat, or high-density items. The clustering results were implemented into an interactive Streamlit-based web application, allowing users to explore and interpret the segmentation results easily. The study concludes that the K-Means algorithm is effective for grouping foods based on nutritional attributes, and the developed system can serve as a practical tool for nutritional education and balanced diet analysis.

Perancangan Sistem Informasi Pengarsipan pada Dinas Perhubungan Provinsi Sumatera Utara Berbasis Website

Sun, 17 May 2026 00:00:00 +0700

Mail archive management is an important part of supporting smooth administration in government agencies. However, manual archiving often causes various problems, such as delays in document retrieval, the risk of losing archives, and low work efficiency. This study aims to design a website-based document archiving information system for the North Sumatra Provincial Transportation Agency. The research methods used include observation, interviews, and literature study. The system design was carried out using Data Flow Diagrams (DFD), Entity Relationship Diagrams (ERD), database design, and user interface design. The results of the study show that the designed information system is capable of improving document storage security. Thus, this system is expected to support improved administrative performance within the North Sumatra Provincial Transportation Agency.

Perancangan Sistem Informasi Penyewaan Karangan Bunga pada Delima Florist Menggunakan Metode Prototype

Khairul Fajri Ilahi, Boy Sandy Dwi Nugraha H., Herlina H. — Sun, 17 May 2026 00:00:00 +0700

Delima Florist is a company engaged in flower board rental services, currently focusing on providing flower board rentals in Padang. At present, Delima Florist is able to serve flower board orders from customers both within Padang and from outside the city. Currently, the flower board ordering process at Delima Florist is still carried out conventionally by using a communication application, after which the orders are manually recorded in an order ledger. This has led to several serious issues, such as customer orders frequently not being properly recorded, resulting in the flower boards not being produced by the Florists. Another issue is the frequent loss of flower boards after the rental period, caused by customers failing to return them to Delima Florist. The purpose of developing this flower board rental information system is to automate the processes of ordering, production recording, and flower board returns. This system is expected to make it easier for staff to monitor orders, deliveries, and returns of flower boards. The flower board rental information system will be developed using the Prototype method, while the process flow and system design will utilize Unified Modeling Language (UML).

Analisis Perbandingan DFA dan NFA Dalam Pencocokan String

Tue, 02 Jun 2026 00:00:00 +0700

String matching is a fundamental process in pattern recognition systems and large-scale text processing, where computational efficiency significantly affects system performance. This study analyzes the comparison between Deterministic Finite Automata (DFA) and Non-deterministic Finite Automata (NFA) in string matching using the pattern (a|b)*abb. The research was implemented through a web-based simulator developed with JavaScript, HTML, and CSS and evaluated using eight short test strings representing accepted and rejected inputs, as well as longer strings to observe execution time differences. The results indicate that DFA and NFA produce identical acceptance outcomes for all test cases, indicating that both automata recognize the same language. However, DFA demonstrates better computational efficiency because each input symbol is processed through a single deterministic transition, whereas NFA requires tracking a set of active states, which increases computational overhead. For longer strings, the execution time gap becomes more pronounced, with DFA remaining consistently faster than NFA. These findings suggest that DFA is more suitable for string matching applications requiring time efficiency, while NFA offers greater flexibility in transition design.