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Deny Zainal Arifin
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Jurusan Teknik Informatika Fakultas Sains dan Teknologi Universitas Islam Negeri Maulana Malik Ibrahim Malang Jalan Gajayana 50 Malang, Jawa Timur, Indonesia 65144
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MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology)
Published by Universitas Islam Negeri Maulana Malik Ibrahim Malang
ISSN : 1978161X     EISSN : 24772550     DOI : https://doi.org/10.18860/mat
Core Subject : Science,
Computer Science & IT
MATICS is a scientific publication for widespread research and criticism topics in Computer Science and Information Technology. The journal is published twice a year, in March and September by Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia. The journal publishes two regular issues per year in the following areas : Algorithms and Complexity; Architecture and Organization; Computational Science; Discrete Structures; Graphics and Visualization; Human-Computer Interaction; Information Assurance and Security; Information Management; Intelligent Systems; Networking and Communication; Operating Systems; Platform-Based Development; Parallel and Distributed Computing; Programming Languages; Software Development Fundamentals; Software Engineering; Systems Fundamentals; Social Issues and Professional Practice.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 8 Documents
 1 
Search results for , issue "Vol 15, No 2 (2023): MATICS" : 8 Documents clear
Comparative Analysis of Kidney Disease Detection Using Machine Learning DIQI, MOHAMMAD; ORDIYASA, I WAYAN; HISWATI, MARSELINA ENDAH
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.21468

Abstract

This research aimed to compare the performance of ten machine learning algorithms for detecting kidney disease, utilizing data from UCI Machine Learning Repository. The algorithms tested included K-Nearest Neighbour, RBF SVM, Linear SVM, Neural Net, Decision Tree, Naïve Bayes, AdaBoost, Random Forest, Gaussian Process, and QDA. The evaluation metrics used were accuracy, precision, recall, and F1-score. The findings revealed that AdaBoost was the most effective algorithm for all evaluation metrics, achieving an accuracy, precision, recall, and F1-score of 1.00. Random Forest and RBF followed closely, while Naïve Bayes and QDA had the lowest performance. These results suggest that machine learning algorithms, especially ensemble methods such as AdaBoost, can significantly improve the accuracy and efficiency of detecting kidney disease. This can lead to better patient outcomes and reduced healthcare costs.
Performance Analysis of Devops Practice Implementation Of CI/CD Using Jenkins Kusumadewi, Rismanda; Adrian, Ronald
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.17091

Abstract

Continuous Integration and Continuous Delivery (CI/CD) are methods used in agile development to automate and speed up the process of building, testing, and validating services. To support and simplify all development and deployment processes, several methods such as containerized and CI/CD automation are needed. In this research, a DevOps Practice is carried out which includes process integration, deployment, and testing automatically using a tool called Jenkins. These tools are open source automation servers to help the Continuous Integration and Continuous Deployment process. Jenkins is equipped with various open source plugins that can be used to simplify and assist CI/CD automation and testing processes. The implementation of CI/CD in performance testing makes the testing process integrated, automated, and can be run on a regular basis. 
DESIGNING E-BUKHARY SHOP APPLICATION USING THE BUSINESS TO-BUSINESS (B2B) MODEL BASED ON A WEBSITE RM, Rusman; As’ad, Ihwana; Alwi, Erick Irawadi
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23377

Abstract

Ongoing technological developments have brought progress in the form of online sales applications. This online sales technology is often also referred to as E-Commerce. Services at the Sinar Bukhari Store for resellers who want to buy goods are still manual and simple, the sales process still uses the WhatsApp group, making it difficult for resellers and also for the shop if there are purchases of goods simultaneously. Resellers also have trouble ordering if the admin they contact is inactive, if new items are sent via the WhatsApp group, the old items will be buried in the group, making it difficult for resellers to order items that have been stockpiled. Then the solution to the problem where the E-Bukhary shop application will be made with a website-based business to business (B2B) model uses the application of prototyping techniques which make plans quickly and gradually so that potential users tend to be quickly assessed. In the E-bukhary shop application, there is a shop feature that involves admins and resellers to simplify the sales process according to the items available. through trials using black box testing in terms of interface scale 1-5 the value is 88% with very good assessment criteria, in terms of application performance a score of 88.8% is included, including very good criteria. in terms of the application database, a score of 86.6% was generated which included very good assessment criteria, then on the missing or damaged application function aspect, a value of 90% was produced in very good criteria, the last on the termination aspect resulted in a value of 86.2% or in very good criteria
Utilizing the K-Means Algorithm for Breast Cancer Diagnosis: A Promising Approach for Improved Early Detection Fitriyah Ayu Tunjung Sari, Nur; Nabela, Maharini; Falah Abdurrohman, Muhammad
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23644

Abstract

Breast cancer is a pressing non-communicable disease, especially affecting women, with its incidence on the rise. In 2020, it ranked among the most common cancers in Indonesia. Timely detection and precise diagnosis are pivotal for effective breast cancer management. To enhance diagnostic accuracy, the K-means clustering method is applied to group patients based on shared attributes. This research aims to contribute significantly to breast cancer diagnosis by leveraging the K-means method, potentially improving patient survival rates.The research process involves data collection, preprocessing, K-means application, evaluation, and visualization. A dataset of 569 breast cancer patient records with 32 attributes from Kaggle is utilized. The K-Means algorithm is assessed using accuracy, yielding a value of 0.8457, signifying good performance. Malignant cases (211) and benign cases (301) are visualized in a scatter plot, distinguishing between them.In conclusion, this study presents an initial step in utilizing the K-means algorithm for breast cancer diagnosis, offering promising results. Further research and the development of more advanced models are imperative to address the global health challenge posed by breast cancer among women.Index Terms—breast cancer; clustering; K-Means Algorithm 
Development of Web-Based Teleoperation VOCAFE Service Robot Atmoko, Rachmad Andri; Alfarhisi, Zikrie Pramudia
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23754

Abstract

The design and implementation of a service robot that communicates effectively via the MQTT Protocol is presented in this research. This study focuses on creating a web-based application to control and monitor the movement of restaurant service robots in one of the university's cafes called VOCAFE. This research uses the MQTT communication protocol which allows smooth interaction between the robot and the operator. The design and construction of service robots, including their mechanical parts and communication systems, is described in the engineering section. The test results show the response time of the robot's navigation system, showing performance within a reasonable range. The conclusion highlights the importance of additional testing and research to improve the system. Overall, this research advances the creation of teleoperated restaurant service robots with reliable and effective communication using MQTT.
The Implementation of Semantic Annotation Recognizing Technique in the Scraper Engine on the E-Publishing Website of the National Research and Innovation Agency (BRIN) Indonesia Ni'am, Muhammad Izzun; Frimansyah, Muhammad Haris; Alfarhisi, Zikrie Pramudia
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23755

Abstract

The increasing need for swift information dissemination in line with modern technological advancements has emphasized the importance and significant impact of data analysis and processing as relevant academic disciplines. These processes encompass data acquisition from various sources, either through direct collection or extraction methods. Among the most crucial and widely utilized techniques for extracting data from the internet is web scraping, particularly when gathering data for research maintenance during the consolidation of multiple institutions into BRIN (National Research and Innovation Agency). Challenges emerge in effectively integrating existing research into a unified system without proper upkeep, as neglecting maintenance can lead to system degradation and hinder access to stored research. Successful maintenance necessitates centralized repositories for researchers' work data. The implementation of semantic annotation recognizing techniques within the web scraping feature of the E-Publishing website holds the potential to expedite this process. The use of web scraping promises to significantly simplify research data collection, while semantic annotation recognizing techniques are poised to streamline implementation, particularly due to the XML data foundation within the Open Archives Initiative (OAI) system. In the context of institution merging and research sustainability, technologies like web scraping and semantic annotation recognizing play pivotal roles in addressing these challenges.
Comparison of Different Classification Techniques to Predict Student Graduation Subarkah, Aan Fuad; Kusumawati, Ririen; Imamudin, M
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.24095

Abstract

Every year, the number of students accepted at the Maulana Malik Ibrahim State Islamic University of Malang continues to increase. Still, not all students can graduate on time according to the specified study period, resulting in a buildup of students who have not graduated according to their graduation period. One of the aspects evaluated in the Study Program accreditation process is the student graduation rate. Apart from that, for each semester, Study Programs are also required to report educational data to DIKTI, and student graduation is one of the factors considered in the report. There is an imbalance between the number of students graduating each year and the number of new students accepted. To overcome this problem, it is necessary to predict student graduation to determine whether they will graduate on time. In science and data analysis, predictions are often used to make predictions based on existing data and information. Classification models in predicting student graduation include the Nave Bayes method, Support Vector Machine SVM, and Random Forest, as well as the level of accuracy of these three methods. From the results of experiments and model evaluations carried out, with data from 458 Informatics Engineering Study Program students with details of 366 training data and 92 testing data, it was obtained that the SVM model had the highest accuracy, reaching around 87% and Random Forest also had good accuracy, around 82%. At the same time, the Naïve Bayes model has lower accuracy, around 76%.
Fuzzy Logic Controller Design for Smart Watering System of Rose Cultivation Arifin, Samsul; Mukti, Fransiska Sisilia; Aziz, Aynan Salsabilah
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23876

Abstract

The traditional methods of rose cultivation often rely on manual irrigation practices, which may not always be precise or efficient. Additionally, the cost associated with implementing automated irrigation systems has been a limiting factor for many farmers. This research addresses these challenges by exploring the integration of Fuzzy Logic Controller (FLC) technology and low-cost electronic devices to develop an automated irrigation system tailored for rose cultivation, aiming to enhance precision and accessibility in agricultural practices. The study demonstrates the effectiveness of this approach in optimizing watering practices, showcasing a notable level of accuracy in providing irrigation recommendations. Moreover, the implementation of low-cost electronic devices enhances the accessibility and feasibility of such smart irrigation systems. The research lays a foundation for advancements in precision agriculture, particularly in the domain of rose cultivation, with potential implications for broader agricultural practices.

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