Pub Date : 2023-10-24DOI: 10.18860/mat.v15i2.17091
Rismanda Kusumadewi, Ronald Adrian
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.
{"title":"Performance Analysis of Devops Practice Implementation Of CI/CD Using Jenkins","authors":"Rismanda Kusumadewi, Ronald Adrian","doi":"10.18860/mat.v15i2.17091","DOIUrl":"https://doi.org/10.18860/mat.v15i2.17091","url":null,"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.","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"46 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.18860/mat.v15i2.23754
Rachmad Andri Atmoko, Zikrie Pramudia Alfarhisi
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.
{"title":"Development of Web-Based Teleoperation VOCAFE Service Robot","authors":"Rachmad Andri Atmoko, Zikrie Pramudia Alfarhisi","doi":"10.18860/mat.v15i2.23754","DOIUrl":"https://doi.org/10.18860/mat.v15i2.23754","url":null,"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.","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"EM-28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.18860/mat.v15i2.23755
Muhammad Izzun Ni'am, Muhammad Haris Frimansyah, Zikrie Pramudia Alfarhisi
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.
{"title":"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","authors":"Muhammad Izzun Ni'am, Muhammad Haris Frimansyah, Zikrie Pramudia Alfarhisi","doi":"10.18860/mat.v15i2.23755","DOIUrl":"https://doi.org/10.18860/mat.v15i2.23755","url":null,"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.","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"2015 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.18860/mat.v15i2.23377
Rusman RM, Ihwana As’ad, Erick Irawadi Alwi
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
{"title":"DESIGNING E-BUKHARY SHOP APPLICATION USING THE BUSINESS TO-BUSINESS (B2B) MODEL BASED ON A WEBSITE","authors":"Rusman RM, Ihwana As’ad, Erick Irawadi Alwi","doi":"10.18860/mat.v15i2.23377","DOIUrl":"https://doi.org/10.18860/mat.v15i2.23377","url":null,"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","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135413960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.18860/mat.v15i2.21468
MOHAMMAD DIQI, I WAYAN ORDIYASA, MARSELINA ENDAH HISWATI
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.
{"title":"Comparative Analysis of Kidney Disease Detection Using Machine Learning","authors":"MOHAMMAD DIQI, I WAYAN ORDIYASA, MARSELINA ENDAH HISWATI","doi":"10.18860/mat.v15i2.21468","DOIUrl":"https://doi.org/10.18860/mat.v15i2.21468","url":null,"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.","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"36 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135414162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.18860/mat.v15i2.23644
Nur Fitriyah Ayu Tunjung Sari, Maharini Nabela, Muhammad Falah Abdurrohman
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
{"title":"Utilizing the K-Means Algorithm for Breast Cancer Diagnosis: A Promising Approach for Improved Early Detection","authors":"Nur Fitriyah Ayu Tunjung Sari, Maharini Nabela, Muhammad Falah Abdurrohman","doi":"10.18860/mat.v15i2.23644","DOIUrl":"https://doi.org/10.18860/mat.v15i2.23644","url":null,"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","PeriodicalId":497787,"journal":{"name":"Matics: Jurnal Teknik Informatika","volume":"29 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135413841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：