Articles
<![CDATA[Knearst Algorithm Analysis – Neighbor Breast Cancer Prediction Coimbra ]]>
<![CDATA[Prahmana, I Gusti]]>;
<![CDATA[Annatasia Br Sitepu, Kristina]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 3 (2022): June 2022 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v1i3.97
<![CDATA[A process to explain the results of the KNN algorithm analysis with the prediction of Breast Cancer Coimbra disease (Breast Cancer). The prediction output of the KNN algorithm will be added with the Simple Linear Regression algorithm modeling to measure the predictive data through a straight line as an illustration of the correlation relationship between 2 or more variables. Linear regression prediction is used as a technique for the relationship between variables in the prediction process of the Breast Cancer Coimbra data set (Breast Cancer). for the value of K in analyzing the KNN algorithm, take the nearest neighbor with the ranking results with K = 5 nearest neighbors which are taken in the KNN calculation. Which is where the output of the KNN algorithm classification will be analyzed with the Simple Linear Regression algorithm with Dependent (Cause) and Independent (effect) variables. The test results determine that the patient has breast cancer and the number of predictions based on age with glucose means that the patient is predicted to have breast cancer. analyze the KNN algorithm with Simple Liner Regression modeling with Python programming language.]]>
<![CDATA[Identification Identification of land and water Centella asiatica leaf herbal plants using digital imagery with the Sobel Edge Detection algorithm ]]>
<![CDATA[Prahmana, I Gusti]]>;
<![CDATA[Br Sitepu, Kristina Annatasia]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 2 (2023): February 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v2i2.158
<![CDATA[Centella asiatica leaves or gotu kola leaves are wild plants that grow in Asian countries such as China, Indonesia, Japan and India. Since thousands of years ago, this gotu kola leaf has been known to treat various diseases. This plant is even used as a traditional herbal medicine in China and India. Centella asiatica is an annual herbaceous plant that grows and flowers throughout the year. Plants will thrive if the soil and environment are suitable to be used as a ground cover. Types of gotu kola that are often found are red gotu kola and green gotu kola. Centella asiatica is also known as antanan taman or antanan batu because it is found in rocky, dry and open areas. Centella asiatica grows with stolons and has no stems, but has rhizomes (short rhizomes). Meanwhile, green gotu kola is often found in rice fields and on the sidelines of the grass. Based on this problem, a study is needed to develop a system to determine the shape of leaf fiber density with a comparison of ground gotu kola and water gotu kola using image processing techniques to find the diameter. This measurement process uses the Matlab application and tests with the Sobel edge detection method and image processing to see edges that are more clearly visible. The results showed that the developed system was capable of obtaining images and identifying the fiber density of Centella asiatica leaves. The system was designed with Jupyter Notebook Python-based programming language analysis with image data taken via internet sources as research material.]]>
<![CDATA[Analysis Sentiment On Social Media Instagram Towards Metaverse Games Saindbox Aplha 2 With Support Vector Machine Algorithm ]]>
<![CDATA[Prahmana, I Gusti]]>;
<![CDATA[Br Sitepu, Kristina Annatasia]]>;
<![CDATA[Selfira]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 2 (2024): February 2024 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i2.230
<![CDATA[Metaverse is part from development technology in the metaverse SandBox Alpha 2 Game world taking place worldwide , games in the virtual world like real very possible thing done . metaverse now Already in progress for can be implemented most affected technology to opinion from particular society _ enthusiasts game metaverse saydbox alpha 2. where game can create her world alone and various game For look for missions and coins can make money to sell _ in metaverse sandbox alpha. since emergence exists game that has been appeared on facebook that has been replaced be meta, create attention world public increasingly highlight technology this , someone _ welcome game the with good and some have _ worries to development technology the . So study This will dig analysis sentiment public Indonesia against development and use metaverse technology uses method algorithm Algorithm Support Vector Machine. analysis sentiment that will done on social media Facebook. Programming language used _ is Language Jupyter Notebook Python. Study This get results opinion public Indonesia to metaverse technology that shows behave neutral , negative and positive .]]>
<![CDATA[Grouping Number of Library Members For Determining the Location of Socialization Using Clustering Method ]]>
<![CDATA[Dwi Pratiwi, Sella]]>;
<![CDATA[Fauzi, Achmad]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.270
<![CDATA[The high use of smartphones at this time led to a decline in public interest in reading books in the library directly. Especially students and students. This is certainly a problem for the Langkat Regency Archives and Libraries Office. Socialization is needed to increase efforts to read interest in the community. The right socialization location must have several criteria so that the socialization carried out is right on target. The existence of a database for each member of the library will facilitate the location selection process. Data mining techniques can classify the number of library members based on the results of large data analysis into information in the form of patterns. The clustering method is a method in data mining that can analyze data with the aim of grouping data based on the same characteristics. The K-Means algorithm is a simple algorithm for classifying a large number of objects with certain attributes into clusters which are usually used in data mining.]]>
<![CDATA[Sentiment Analysis Using Text Mining Techniques On Social Media Using the Support Vector Machine Method Case Study Seagames 2023 Football Final ]]>
<![CDATA[Rifa'i, Muhammad]]>;
<![CDATA[Buaton, Relita]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.274
<![CDATA[This thesis aims to analyze sentiment on text data from social media related to the 2023 SEA Games, especially in the final match of the soccer sport. The method used is the Text Mining Technique with the SVM (Support Vector Machine) algorithm to classify user sentiment as positive or negative regarding the match. Text data is retrieved from various social media platforms during and after the match. The results of the sentiment analysis are expected to provide insight into the public's view of the sporting event. This research can contribute to the understanding of public sentiment towards the 2023 SEA Games final football match through the analysis of text data from social media.]]>
<![CDATA[Categorying Sugarcane Production Based On Factors Affecting Productivity With The K-Nearest Neighbor Algorithm ]]>
<![CDATA[Pratiwi, Anggi]]>;
<![CDATA[Pardede, A M H]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.295
<![CDATA[Sugarcane (Saccharum Officanarum is an annual plantation crop, which has its own characteristics, because the stem contains sugar. To classify the results of sugarcane production, currently still using the manual method by only looking at the current conditions of sugarcane production. This is less efficient because there is no calculation process in grouping sugarcane. So that mistakes can occur in grouping sugarcane production to get good results or not in the assessment of sugarcane grouping at PTPN II Kwala Madu. For this reason, the author will create an alternative application system that can group sugarcane production with the K-Nearest Neighbor algorithm to find out the best type of sugarcane production based on the factors. The application made by the author uses the PHP programming language and uses the MySQL database as data storage. The system is made as easy as possible to make it easier for users to use and understand later.]]>
<![CDATA[The potential and perception of sawah lukis ecotourism ]]>
<![CDATA[Selfira, Selfira]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ Junal Ilmu Manajemen Vol 7 No 2 (2024): April: Management Science and Field ]]>
Publisher : <![CDATA[Institute of Computer Science (IOCS) ]]>
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DOI: 10.35335/jmas.v7i2.482
<![CDATA[The aim of this research is to determine public perceptions and the potential that exists in Sawah Lukis ecotourism. The population of the research is the local community. The research sample used Purposive Random Sampling technique with a total of 55 people. Data collection methods are carried out in several ways, namely observation, in-depth interviews, and questionnaires. The data was then analyzed using qualitative descriptive analysis methods. Based on the results of observations and interviews, Sawah Lukis ecotourism actually has economic value and the potential for further development. For the sustainability of the existence of ecotourism, institutional-based promotional activities and collaboration are needed to improve the quality of promotion.]]>
<![CDATA[The Training of Canva-Based Interesting Learning Content Creation for Students at SMK Putra Anda Binjai ]]>
<![CDATA[Prahmana, I Gusti]]>;
<![CDATA[Tioria Pasaribu]]>;
<![CDATA[Husnul Khair]]>;
<![CDATA[Zira Fatmaira]]>
<![CDATA[ International Journal of Community Service Implementation Vol. 2 No. 1 (2024): IJCSI JUNE 2024 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijcsi.v1i5.213
<![CDATA[Technology is the main need in today's world of education because it is able to produce many applications that can be used as digital learning media. One of them is the Canva application which can be used to design learning displays or teaching materials as visual media in the teaching and learning process. This Community Service (PkM) aims to describe the training activities for creating interesting learning content with the Canva application for students at SMK Putra Anda Binjai which was held on March 15, 2024. The material of the training activities was delivered through presentations and questions and answers located in the Hall of SMK Putra Anda Binjai. This activity was carried out on the basis that most students still do not have insight and knowledge in developing and using applications that can be used in learning, lack of student creativity in designing innovative learning media in designing learning to be more interesting and fun, and students have difficulties in utilizing learning media applications, such as the Canva application, due to lack of information and training on the use of IT-based learning media. The methods used in this service are lectures, discussions, questions and answers, and finally evaluating activities using google forms. The result of this activity is that students have a broader knowledge of learning media, especially on the Canva application so that they are able to create learning content that is interesting, easy to understand, and fun.]]>
<![CDATA[Application of the Monte Carlo Method in Modeling and Simulation of Service Queuing Systems at PT. Pos Indonesia Persero Binjai ]]>
<![CDATA[Yusrina, Eli]]>;
<![CDATA[Buaton, Relita]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ International Journal of Informatics, Economics, Management and Science Vol 2 No 2 (2023): IJIEMS (August 2023) ]]>
Publisher : <![CDATA[Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta ]]>
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DOI: 10.52362/ijiems.v2i2.1181
<![CDATA[Queues are events that we often encounter in various places that provide services to the public, one of which is the Post Office. Service to customer satisfaction is a very important thing, so that improving the quality of customer service must always be done. A good queuing system will affect consumer behavior and satisfaction. PT. Pos Indonesia Persero Binjai is a service company where the purpose of PT. Pos Indonesia (Persero) itself is customer satisfaction oriented. The problems that occurred at PT. Pos Indonesia Persero Binjai caused long queues to build up in queues. To overcome these problems, it is necessary to improve the system such as applying the queuing model application by applying the queuing model method and Monte Carlo simulation. Monte Carlo is a probabilistic simulation method that generates random input to mimic the existing conditions of a problem by estimating the same distribution and in accordance with reality. So that with the improvement of the system, the application of the queuing model can be applied, directing customers to take queue numbers, and monitoring the queue card arrangement, adding tellers to serve customers, enlarging the waiting room so that customers are comfortable waiting and also determine the characteristics and performance measures of the queuing system in part of the payment counter and delivery of goods that will help PT. Pos Indonesia Binjai Company.]]>
<![CDATA[Public Sentiment towards the Medan-Binjai Water Pipeline Excavation using the Naïve Bayes Method ]]>
<![CDATA[Turnip, Liana Tasya]]>;
<![CDATA[Manurung, Hotler]]>;
<![CDATA[Prahmana, I Gusti]]>
<![CDATA[ International Journal of Informatics, Economics, Management and Science Vol 3 No 1 (2024): IJIEMS (January 2024) ]]>
Publisher : <![CDATA[Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta ]]>
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DOI: 10.52362/ijiems.v3i1.1237
<![CDATA[The work on this project received sharp scrutiny from Non-Governmental Organizations (NGOs) because it was suspected that it was not in accordance with the Work Operation Standards (SOP) and not in accordance with the Technical Instructions (Guidelines for Implementation) and Juknis (Technical Instructions) .Naive Bayes is based on a simplified estimate that attribute values are conditionally independent of each other when given output values. Obtain an accuracy value of 0.75, with a negative precision classification of 0.75, negative recall1.00 f1-score negative0.86 and a negative3 support value. Precision classification Positive 0.00 positive recall 0.00 f1-score positive 0.00 and positive support value 1. This means that the performance of the system's success in retrieving information that has a positive value in the document is very low. -Binjai using the Naive Bayes algorithm method, it can be concluded as follows: 1) The accuracy level produced by the naïve Bayes classifier is 75%. 2) The advantages of this study are that it has good accuracy, precision and recall values, so that it is enough to be used in a system. 3) The deficiency in this research is in the performance of the system in finding the success of the system to find back information in the positive class, which is equal to 0.00%. This is because the amount of training data in the positive class is less than the negative class or it can be said that the training data used in this study is not balanced.]]>
