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Media Jurnal Informatika
Published by Universitas Suryakancana
ISSN : 20882114     EISSN : 24772542     DOI : https://doi.org/10.35194/mji.v12i2
Core Subject : Science,
Computer Science & IT
Media Jurnal Informatika merupakan oleh jurnal yang diterbitkan oleh Program Studi Teknik Informatika Universitas Suryakancana Cianjur yang terbit setiap 6 Bulan pada Juni dan Desember. Media Jurnal Informatika mulai terbit dengan versi cetak pada tahun 2009 dan terbit satu kali dalam satu tahun, namun kemudian frekuensi terbit dinaikan menjadi dua kali dalam satu tahun. Fokus dan lingkup bidang Media Jurnal Informatika meliputi Geography Information System Security Network Big Data Information System Enterprise Resource Planning Internet of Things, Cloud Computing Artificial Intelligent Soft Computing Multimedia dan Game Human Computer Interaction
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 206 Documents
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AI-Based Testing Using NLP Algorithm On Eggsperts Website Functionality Using Boundary Value Analysis Technique Harahap, Zolla Perdana Putra; Alfarizi, Akhfa Bagas; Ferddinansya, Rio; Andi, Adrian Fardan; Nasir, Muhammad; Indriasari, Sofiyanti
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5884

Abstract

The poultry farming subsector plays a crucial role in national food security, yet remains constrained by manual recording and efficiency constraints. Digital transformation offers solutions such as the Eggspert website, designed to assist farmers in managing production and sales data quickly and in an integrated manner. This study aims to test the reliability and functionality of the Eggspert system and assess the effectiveness of integrating Artificial Intelligence (AI) into the software testing process. Unlike previous AI-assisted testing studies that primarily focus on generic software applications, this research emphasizes the application of NLP-based AI Testing within a domain-specific digital livestock management system, addressing the lack of empirical testing frameworks tailored to the poultry farming sector. This research is an experimental quantitative approach using Black Box Testing and Boundary Value Analysis (BVA) techniques, combined with Natural Language Processing (NLP)-based AI Testing. The process follows the Software Testing Life Cycle (STLC) stages to ensure systematic and measurable testing. Of the 42 test cases executed, 33 passed and 9 failed, resulting in a success rate of 78.57%. Each test case was executed repeatedly under consistent test conditions to ensure functional stability, with failures indicating specific validation weaknesses rather than random system behavior. Most system functions met specifications, although minor deficiencies remained in text validation and zero pricing. The integration of AI Testing has been shown to improve error detection efficiency. The combination of BVA and AI Testing effectively verified the functionality of the Eggspert system, increased the reliability and efficiency of the testing process, and has the potential to serve as a basis for developing an AI-based testing system in the digital livestock sector.
ANALYSIS OF BKD SAVINGS AND LOAN ADMINISTRATION INFORMATION SYSTEM septiani, hanum dwi
Media Jurnal Informatika Vol 17, No 1a (2025): Special Issue Information System Media Jurnal Informatika (On Progress)
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i1a.5485

Abstract

Savings and Loan Cooperative (KSP) of Village Credit Agency (BKD) Kaligayam Unit plays an important role in supporting the rural economy through microfinance services, such as saving funds and providing loans. However, the administration system currently used is still manual and not integrated, resulting in various obstacles such as recording errors, late reporting, and the risk of data loss. This study aims to analyze the ongoing savings and loan information system, identify weaknesses in the administration process, and provide recommendations for designing a more effective and efficient digital system. The research methods used are direct observation, interviews with related parties, and literature studies. The results of the analysis show that system digitalization is needed to support service improvements, both in terms of recording accuracy, service speed, and customer data security. The proposed system will later be designed to be easy to use by officers, support automatic reporting, and have appropriate access rights settings. With the implementation of a computerized information system, it is hoped that cooperative management will become more modern, transparent, and able to compete with other financial institutions.
A Solution Recommendation System Based on Application Constraint History Using Cosine Similarity and Gemini AI Nathasia, Novi Dian
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5940

Abstract

Problems with applications are potentially to disrupt business operational processes, especially in companies that depend entirely on applications. Therefore, speed and accuracy in handling every application problem that occurs is needed. One way to deal with various application problems effectively is to look for similar issues that have occurred before, and then take the handling solution as a reference for handling the current issue. This research aims to develop a recommendation system for handling application problems that can help the performance of the support services team. This system uses a cosine similarity algorithm with Term Frequency-Inverse Document Frequency weighting to find similar constraints based on the description. Before processing, the constraint description is summarized first using Gemini AI. Solutions to the obstacles found are used as a reference for handling current obstacles. The result of this research is that the system can summarize descriptions of issues and search for similar issues based on the dataset that has been trained. The recommendation system for handling application problems was well received by users, as evidenced by a score of 93.1% from 30 respondents who filled out the User Acceptance Test questionnaire.
Development of Web-based Employee Performance Appraisal Information System with SAW Method at PT Muawanah Al Ma'soem Grisela, Dina; Darmanto, Tedjo; Hermanto, Moch Irwan
Media Jurnal Informatika Vol 17, No 1a (2025): Special Issue Information System Media Jurnal Informatika (On Progress)
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i1a.5646

Abstract

Employee performance appraisal at PT Muawanah Al Ma'soem is still done manually, causing problems of efficiency, accuracy, and objectivity. This research is focused on designing a web-based information system used to assess employee performance, with the aim of increasing the effectiveness and efficiency of the evaluation process. To produce an objective assessment based on a number of criteria, the Simple Additive Weighting (SAW) method is used, while the Rapid Application Development (RAD) approach is applied to accelerate system development through an iterative process and the use of prototypes. The result of the research is a web-based system with features of employee data management, assessment criteria, and automatic ranking. Tests show that the system runs well and helps speed up the assessment process and improve the accuracy of the results. The system that has been developed is proven effective in accelerating the appraisal process while maintaining objectivity in employee performance evaluation.
DECISION SUPPORT SYSTEM FOR OIL PALM SEED SELECTION USING THE SIMPLE ADDITIVE WEIGHTING METHOD Situngkir, Silvia Wulandari
Media Jurnal Informatika Vol 17, No 1a (2025): Special Issue Information System Media Jurnal Informatika (On Progress)
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i1a.5367

Abstract

Oil palm is one of the most important plantation commodities in Indonesia's plantation development. According to the Indonesian Ministry of Agriculture (2014), the total area of oil palm plantations in Indonesia is 11 million hectares, double the area in 2000. Indonesia is one of the largest palm oil producers in the world, providing employment for 16 million people, both directly and indirectly. The use of superior seeds is one of the important factors that determine the growth of oil palm. Maximum production can be achieved if the plants come from good quality seeds. Decision Support System is an interactive system that supports decisions in the decision-making process through alternatives obtained from the results of data processing, information and model design. By utilizing data processing technology that can provide solutions for farmers in choosing good seeds. In this research, the Decision Support System was developed with the Simple Additive Weighting Method where this system will assist farmers in determining quality seedlings ready for planting based on the criteria of the number of leaves, the age of the seedling in months, the height of the seedling in centimeters, and the diameter of the stem. With the results of the type of seedling DxP PPKS 718 3 is the most superior type of seedling for planting with a preference value obtained of 100, while the type of palm seedling DxP PPKS 239 1 is the worst quality seedling among 24 alternatives with a total preference of 24.
Multi-Class Fault Detection under Class-Imbalance in Wireless Sensor Network Using Random Undersampling and Extra Trees Saputra, David Yusup; Wardhani, Luh Kesuma; Nanang, Herlino
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5959

Abstract

Wireless Sensor Networks (WSNs) are widely used in various monitoring applications, including environmental observation, smart infrastructure, and Internet of Things (IoT) systems. Despite their widespread adoption, WSNs are highly susceptible to data errors caused by sensor degradation, hardware malfunctions, environmental disturbances, and communication issues. These faults can significantly reduce data reliability and lead to incorrect system decisions if not properly handled. This study proposes a multi-class data-fault detection approach for WSNs under imbalanced data conditions by integrating Random Undersampling (RUS) with the Extra-Trees classification algorithm. The proposed framework aims to address the class imbalance problem commonly found in sensor fault datasets while improving fault detection performance across multiple fault types. Experiments were conducted using a WSN dataset containing temperature and humidity measurements, in which three fault types: Bias, Drift, and Spike were analyzed alongside normal sensor data. The experimental results demonstrate that Random Undersampling leads to a substantial improvement in classification performance. Without RUS, the Extra-Trees classifier achieved an accuracy of 48% and failed to detect spike faults. After applying RUS, classification accuracy increased to 91%, accompanied by balanced precision, recall, and F1-score values across all classes. These findings indicate that the combination of Random Undersampling and Extra-Trees provides an effective and reliable solution for multi-class data fault detection in WSN environments.
Development Of A CNN Model For Recognizing The Indonesian Sign Language (BISINDO) Alphabet Nuriah, Sinta Siti; Sidiq, Ahmad Zamakhsyari; Akbar, Zulkaida
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5936

Abstract

Deaf people in Indonesia face communication barriers due to the limited understanding of Indonesian Sign Language (BISINDO) among the general public. This results in limited social interaction between deaf people and their surroundings. This study aims to develop a Deep Learning and Computer Vision-based BISINDO alphabet translator model using the Convolutional Neural Network (CNN) method, addressing the limited availability of publicly documented BISINDO datasets for alphabet recognition . The method used involves training the model with a dataset of 3,120 BISINDO alphabet images, covering the letters A to Z. The dataset was divided into 80% for training and 20% for testing. The training process included model architecture design, parameter tuning, selection of the best model based on accuracy, and performance evaluation. The evaluation results showed that the developed CNN model achieved an accuracy of 99.84% in classifying BISINDO letters; however, challenges remain in generalizing the model to variations in lighting, hand orientation, and user differences. Nevertheless, the high accuracy achieved indicates the model’s potential to support effective BISINDO translation and improve communication accessibility. This research also opens up opportunities for further development towards comprehensive translation of gestures or sentences in BISINDO.
DESIGNING AN ANDROID-BASED EMPLOYEE INDIVIDUAL ASSISTANT APPLICATION (ASIKA) (CASE STUDY: AT MADTIVE STUDIO) Nugraha Pratama, Agie Nugraha
Media Jurnal Informatika Vol 17, No 1a (2025): Special Issue Information System Media Jurnal Informatika (On Progress)
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i1a.5810

Abstract

This research is based on the process and analysis conducted at one of the software houses in Cianjur district named Madtive Studio. Madtive Studio is a software house engaged in Information Technology, Systems and Branding which was established in 2015. The main focus of this company is the development of application systems for all types of companies ranging from retail, services, distributors and manufactures. This is done in order to become a benchmark for the author in carrying out research. The author found 3 factors as follows: (1) Input and reporting of data still use conventional methods. (2) Confusion when controlling work. (3) Difficulty in reporting work. For this reason, a HR management program is needed so that the ongoing procedures are well-systematic and will make it easier for owners and employees to input and report data. Making the system usually begins with an analysis process, but the process of gathering system requirements is not always found in the analysis process. In this study, the system design that the author uses is the extreme programming (XP) method. Method (XP) is needed to design a system that will be made by taking into account the needs and desires of users. In (XP) feedback from users becomes one of the important values. The result of the research is a system design with only one display, which is based on Android with a firebase database. This will make the user more simple but useful
Course Schedule Optimization Using a Java-Based Ant Colony Optimization Pongsumarre, Theo Buana; Wahyuni, Wahyuni; Fahmi, Muhammad
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5961

Abstract

Course timetabling in higher education is a complex combinatorial problem due to constraints related to lecturer availability, limited classroom resources, and fixed weekly time-slot structures. As the number of courses and class sections increases, manual scheduling becomes increasingly inefficient and prone to conflicts, particularly room clashes and overlapping lecturer assignments. This study develops and evaluates an automatic course scheduling system based on the Ant Colony Optimization (ACO) algorithm and implements it as a Java-based desktop application to generate feasible timetables under real institutional conditions. An experimental computational approach is employed, in which artificial ants construct candidate schedules through probabilistic selection influenced by pheromone trails and heuristic information. Timetable quality is evaluated using a weighted cost function that prioritizes hard-constraint satisfaction, such as preventing lecturer and room clashes, while also incorporating soft-constraint penalties related to lecturer forbidden timeslots and schedule distribution balance. The system is tested using real academic data from an undergraduate study program, including courses, lecturers, classrooms, and predefined weekly timeslots. Experimental results show that the proposed system consistently generates conflict-free timetables, achieving a conflict value of zero across all repeated runs under the selected parameter configuration. Beyond feasibility, the optimization process continues to refine timetable quality by reducing soft-constraint penalties, as indicated by the convergence behavior observed across repeated executions. This repeated-run evaluation provides insight into the stochastic optimization characteristics of the ACO-based approach under fixed parameter settings. These findings indicate that the Java-based ACO approach effectively supports automated university course scheduling and provides a practical solution for producing feasible and well-structured timetables.
Design of a Web-Based OSIS E-Voting System Using the Waterfall Method at SMPN 3 Naringgul Amrullah, Aziz Stiawan; Darmanto, Tedjo; Hermanto, Moch Irwan
Media Jurnal Informatika Vol 17, No 1a (2025): Special Issue Information System Media Jurnal Informatika (On Progress)
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i1a.5766

Abstract

Background: The election of the Student Council President (Ketua OSIS) at SMPN 3 Naringgul has so far been conducted manually, which often causes errors in vote counting and delays in announcing results. Objective: This study aims to develop a web-based E-Voting System to improve the efficiency, accuracy, and transparency of OSIS elections. Method: This research used a structured Waterfall Methodology for software development, covering requirement analysis, system design with UML diagrams, implementation using PHP/MySQL, and system testing using Black-Box Testing for verification. Results: The resulting e-voting system has features such as secure voter login, a candidate selection interface, real-time vote counting, and an admin panel for data management. Testing results show that the system can speed up the election process, minimize human error, and increase result transparency. Conclusion: The developed system effectively supports the digitalization of school election management and provides a faster and more reliable alternative compared to manual election methods.

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