Management of Information System Journal

Rancang Bangun Media Pembelajaran Quiz Edukatif Bahasa Arab Berbasis Web di TPQ Athoyyibin Kabupaten Wakatobi

Shinta Esabella, Muh NurHidayatullah, Farida Idifitriani — Mon, 20 Apr 2026 23:07:29 +0000

This research aims to design and develop a web-based Arabic educational quiz media that integrates gamification elements (points, levels, badges, and leaderboards) to create a more interactive and engaging learning experience. The research method uses qualitative and quantitative approaches with data collection through observation, interviews, and literature study. Software development is carried out using the Software Development Life Cycle (SDLC) Agile model. The application is built using the Laravel framework (PHP), MySQL database, and Tailwind CSS and Alpine.js for the user interface. System functionality testing is conducted using the User Acceptance Testing (UAT) method involving 17 respondents consisting of 3 admins, 4 teachers, and 10 students. The results show that the web-based Arabic educational quiz media Quiz was successfully developed with three user levels (admin, teacher, and student) and gamification features that increase student engagement and learning motivation. UAT results show an overall acceptance rate of 4.40 out of a scale of 5 (Good category), with students giving the highest rating of 4.76 (Very Good), especially in the motivation and learning aspect which obtained a Score of 4.80. This application is expected to be an alternative solution in supporting more effective and attractive Arabic language learning at TPQ Athoyyibin.

Estimasi Sudut Kedatangan yang Ditingkatkan dengan CNN pada Array Antena MIMO Menggunakan Data Sinyal IoT Dunia Nyata

Abdul Karim, Andi Ernawati — Mon, 20 Apr 2026 23:13:40 +0000

− This study proposes the application of a Convolutional Neural Network (CNN)–based approach to analyze signals in Internet of Things (IoT)–based MIMO antenna systems, with the aim of enhancing the understanding of system performance characteristics, particularly in predicting latency parameters. The CNN model is trained using real-world IoT signal data that have undergone comprehensive preprocessing stages, including data normalization, missing value handling, and feature engineering to ensure compatibility with the model input format. Experimental results on previously unseen test data demonstrate that the proposed model achieves a test loss of 1.4410, represented by the Mean Squared Error (MSE), and a Mean Absolute Error (MAE) of 0.9395. These results indicate that the model attains a relatively low prediction error and effectively captures the nonlinear relationships between signal features and system responses.

Visualization of the testing results reveals a strong correlation between actual and predicted latency values, although some dispersion remains due to channel complexity and the inherent variability of IoT signals. The distribution of prediction errors is centered around zero, indicating the absence of significant systematic bias in the model. Overall, the findings confirm the potential of CNN as a reliable approach for modeling and performance analysis of IoT-based MIMO antenna systems, while also highlighting opportunities for further development in spatial parameter estimation and intelligent wireless communication system optimization.

Analisis Efektivitas Sistem Berbasis Data Penjualan dan Penyediaan Barang

Masyita Risna, Nurkhalik Wahdanial Asbara, Nurul Istiqamah — Mon, 20 Apr 2026 00:00:00 +0000

This study aims to analyze the effectiveness of a data-based system in the areas of sales and inventory provision at Master Stokist Takalar of PT Mega Gloryoung International (MGI). The study employed a mixed-method approach by integrating qualitative and quantitative data. Primary data were obtained through interviews, observations, and questionnaires administered to 20 respondents, while secondary data were collected from sales reports, transaction records, and inventory data. Quantitative analysis was conducted using descriptive statistics through effectiveness percentages and efficiency comparisons, whereas qualitative analysis was carried out through data reduction, data display, and conclusion drawing. The findings indicate that the data-based system is effective in the sales aspect, as reflected by an average effectiveness rate of 89%, reduced time required for transaction recording, data retrieval, and report preparation, as well as a 12% upward trend in sales. However, in the inventory provision aspect, the system’s effectiveness has not yet been optimal because stock management is still conducted manually, stock monitoring is not yet real-time, and demand forecasting remains reactive. These conditions indicate that the effectiveness of the system at Master Stokist Takalar is still partial, being strong in sales transactions but weak in inventory control. Therefore, stronger integration between the sales system and the inventory system is necessary to enhance distribution stability and reduce the risk of stockouts

Analisis Risiko Keamanan Pada Aplikasi Mobile Banking Dan Strategi Mitigasi

Abdul Sakti, Ahmad Naswin , Sulkifli — Mon, 27 Apr 2026 07:44:04 +0000

This study aims to analyse security risks in mobile banking applications and their mitigation strategies. A qualitative approach using descriptive methods was employed, with data collected through literature reviews, documentation, and analysis of scientific literature relating to cybersecurity and mobile banking. The study focuses on identifying the types of risks, their sources, the resulting impacts, and the mitigation strategies implemented by banking institutions. The analysis was conducted systematically through the stages of data reduction, data presentation, and drawing conclusions, and was validated through triangulation of sources. The research findings indicate that the primary threats to mobile banking applications include phishing, malware, man-in-the-middle attacks, data breaches, and the use of weak passwords. Technical factors such as system and network vulnerabilities, as well as human factors—particularly user security awareness—are the main causes of these risks. Effective mitigation strategies include the implementation of multi-factor authentication, data encryption, real-time system monitoring, user education, and the development of applications based on secure coding. The combination of security technology, system monitoring, and user literacy has been proven to enhance mobile banking security, making the service safer, more reliable, and adaptable to evolving risks.

Algoritma Data Mining Menggunakan Metode Decision Tree Untuk Memprediksi Pola Penjualan Produk Springbed Mengggunakan Algoritma C4.5

Donny Sanjaya, Amir Saleh, Sri Novida Sari, Surizar Rahmi Danur — Tue, 05 May 2026 14:34:14 +0000

Problems that often occur in the world of spring bed sales business are frequent ups and downs in predictions, the difficulty of detecting patterns in what can increase sales from buyers makes spring bed sales business people often experience losses, this also happens because business people don't know the strategy. Certainly in increasing sales, it is necessary to make predictions with a high level of accuracy, one of which is with the help of the application of computer science data mining using the C4.5 method. The C4.5 method used in this research is able to produce an optimal decision tree, with the ability to sort out the most relevant attributes in predicting springbed sales. The use of this data mining algorithm is expected to provide insight to springbed business players in making strategic decisions, such as stock management, production planning and more effective marketing campaigns. The experimental steps in this research include collecting springbed sales data. Experimental results show that the Decision Tree algorithm using the C4.5 method is able to provide spring bed sales predictions with an adequate level of accuracy. This model can help Springbed sales business players in planning more appropriate business strategies based on estimated market demand to increase the ups and downs of sales

Analisa Perbandingan Algoritma Shannon Fano Dan Algoritma Stout Code Pada Kompresi File Teks

Dito Putro Utomo, Abdul Karim, Muhammad Syahrizal — Tue, 05 May 2026 14:49:38 +0000

The rapid development of technology today attracts a lot of attention from the wider community. The dynamic development of computers is accompanied by the ability to get information very quickly. Data compression is a technique to reduce the amount of data in the original data. Data compression is usually applied to computer machines. This happens because each symbol displayed on the computer has a different bit value. The large size of text files will be a problem for storage space. Because the need for text files is very important, we tend to collect data in the form of text files, and often without realizing it, we store it in large sizes. This causes the need for storage media to be large. To overcome this problem, text files that have a larger size are used by compressing text files. Large data will be compressed into a small size, which will reduce storage. After applying the comparison of the Shannon Fano Algorithm and the Stout Code algorithm, compressing the text file has proven that the text file has been successfully compressed. After performing the text file compression process, the author can conclude that the Shannon Fano algorithm is better at performing the compression process.