Journal of Artificial Intelligence and Engineering Applications (JAIEA)最新文献_第8页

APPLICATION OF CASE BASED REASONING (CBR) METHOD IN DISTRIBUTION TRAFO DAMAGE EXPERT SYSTEM AT PLN UP3 BINJAI 基于案例推理(cbr)方法在配电交通损伤专家系统中的应用

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-10-15 DOI: 10.59934/jaiea.v2i1.111

Aris Wahyono, Akim Manaor Hara Pardede, Rahmadani, Stmik Kaputama, Jl. Veteran, Sumatera Utara

{"title":"APPLICATION OF CASE BASED REASONING (CBR) METHOD IN DISTRIBUTION TRAFO DAMAGE EXPERT SYSTEM AT PLN UP3 BINJAI","authors":"Aris Wahyono, Akim Manaor Hara Pardede, Rahmadani, Stmik Kaputama, Jl. Veteran, Sumatera Utara","doi":"10.59934/jaiea.v2i1.111","DOIUrl":"https://doi.org/10.59934/jaiea.v2i1.111","url":null,"abstract":"In the world of electricity, transformers are widely used, both in the field of electric power and electronics. The use of transformers in the electric power system is used for each of its needs, for example the need for high voltage in the delivery of electrical power over long distances. Electrical equipment transformers are expensive and are very vital equipment. If the transformer is disturbed or in an abnormal condition, there may be an unexpected temporary cessation of electricity distribution and will cause losses for PLN and consumers who use electricity by disrupting the activities carried out. The Case Based Reasoning (CBR) method is a case-based reasoning system that uses previous experiences or cases so that they can solve new problems or cases. There are several stages in the case based reasoning method, including retrieve, reuse, revise, and retain. Case-based Reasoning (CBR) collects previous cases that are similar to the new problem and tries to modify the solution to fit the new case. The basic idea of Case-Based reasoning is the assumption that similar problems have similar solutions. While this assumption is not always true, it does depend on many practical domains. Where the previous case experienced an overvoltage transformer damage, using the CBR method will look for similarities to the previous case with existing characteristics, the CBR method will look for the same case on the existing Knowladge so that the damage is quickly detected. From the characteristics of the damage that is on the transformer, it is easy to diagnose transformer damage using the CBR method and the results of the CBR method will find a ranking that is almost similar to the existing case.","PeriodicalId":320979,"journal":{"name":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125577570","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}

引用次数: 0

Implementation of the Importance Performance Analysis Method in Measuring the Level of Community Satisfaction with Service Performance 重要性绩效分析法在社区服务绩效满意度测评中的应用

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-10-15 DOI: 10.59934/jaiea.v2i1.112

Efrida_R Haumetan, D. Nababan

{"title":"Implementation of the Importance Performance Analysis Method in Measuring the Level of Community Satisfaction with Service Performance","authors":"Efrida_R Haumetan, D. Nababan","doi":"10.59934/jaiea.v2i1.112","DOIUrl":"https://doi.org/10.59934/jaiea.v2i1.112","url":null,"abstract":"Service can be said to be satisfactory, if the service can meet community satisfaction. A satisfaction is achieved if the service received by the community is in accordance with what is expected. To determine the level of community satisfaction with service performance at the Department of Population and Civil Registration, North Central Timor Districts, it is necessary to have a system to measure the level of community satisfaction. The measurement of community satisfaction is carried out using the Importance Performance Analysis (IPA) method which considers the level of interest or expectations of the respondents, with indicators or dimensions in the form of physical tangibles, reliability, responsiveness, assurance, and empathy. The result of this research is the construction of a website-based Measurement System that is able to determine the level of community satisfaction with the performance of the services provided. Measurement using the IPA method, obtained performance that must be improved or reduced based on its quadrant mapping with 25 attributes, which are divided into 4 quadrants, namely quadrant I (main priority) 8attributes, quadrant II (maintain achievement) 3 attributes, quadrant III (low priority) 3 attributes, and quadrant IV (excessive) 11 attributes.","PeriodicalId":320979,"journal":{"name":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123337505","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}

引用次数: 0

Model of the Independent Learning Campus Internal Quality Assurance System Program based on Artificial Intelligence 基于人工智能的自主学习校园内部质量保证体系方案模型

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-10-15 DOI: 10.59934/jaiea.v2i1.117

Muhammad Zarlis, Elviwani, Ami Dilham, Relita Buaton

{"title":"Model of the Independent Learning Campus Internal Quality Assurance System Program based on Artificial Intelligence","authors":"Muhammad Zarlis, Elviwani, Ami Dilham, Relita Buaton","doi":"10.59934/jaiea.v2i1.117","DOIUrl":"https://doi.org/10.59934/jaiea.v2i1.117","url":null,"abstract":"Research on models of internal quality assurance systems in tertiary institutions online and digitally based on artificial intelligence in supporting the Merdeka Learning Campus Merdeka program in accordance with the cycle of determination, implementation, evaluation, control and improvement. The system is supported by an artificial intelligence approach to determine the implementation and achievement of the Merdeka Learning Campus Merdeka standard and to help universities detect early the impact of the implementation of Merdeka Learning Kampus Merdeka on the development of student competence. The implementation of the Merdeka Learning Campus Merdeka program is recorded in a database with cycles of Determination, Implementation, Evaluation, Control and Improvement to analyze compliance with the establishment, implementation, evaluation, control and improvement of standards for one cycle each year. At the evaluation stage, standard achievement will be produced whether it exceeds, is achieved or deviates to be followed up at the control and improvement stage. With this application, it helps tertiary institutions carry out the standards for the Merdeka Learning Campus Merdeka program standards to be carried out and developed according to the cycle of Determination, Implementation, Evaluation, Control and Improvement","PeriodicalId":320979,"journal":{"name":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127754474","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}

引用次数: 0

The Application of ANN Predicts Students' Understanding of Subjects During Online Learning Using the Backpropagation Algorithm at SMAN 1 Perbaungan 在SMAN 1 Perbaungan使用反向传播算法预测在线学习过程中学生对学科的理解

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.87

Rendiarno Rendiarno, H. Fahmi

引用次数: 1

EXPERT SYSTEM FOR HYPOTHYROIDISM DIAGNOSIS USING CASE BASED REASONING METHOD (CASE STUDY OF MELATI II Public Health Center) 基于案例推理方法的甲状腺功能减退诊断专家系统(以MELATI II公共卫生中心为例)

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.88

Dewinda Rimanti, H. Fahmi

引用次数: 0

WEB-BASED STICKER ORDERING INFORMATION SYSTEM 基于web的贴纸订购信息系统

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.108

Rabiatul Adwiya

引用次数: 0

Impact of Educational Games To Introduction Tourist Destination In Central Java On Elementary School Student 教育游戏对中爪哇地区小学生旅游目的地介绍的影响

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.106

Budi Satria

引用次数: 0

DECISION SUPPORT SYSTEM FOR DETERMINING THE BEST TEACHER USING TOPSIS METHOD (CASE STUDY : SMP NEGERI 1 GALANG) 运用topsis法确定最佳教师的决策支持系统(案例研究:SMP negeri 1 galang)

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.89

Iinvera Niar, H. Fahmi

引用次数: 1

IMAGE DETECTION EDGE IMAGE USING CANNY EDGE ALGORITHM 图像边缘检测采用canny边缘算法

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.109

Romanus Damanik

引用次数: 1

Knearst Algorithm Analysis – Neighbor Breast Cancer Prediction Coimbra Knearst算法分析-邻近乳腺癌预测科英布拉

Journal of Artificial Intelligence and Engineering Applications (JAIEA) Pub Date : 2022-06-15 DOI: 10.59934/jaiea.v1i3.97

I. G. Prahmana, Kristina Annatasia Br Sitepu

{"title":"Knearst Algorithm Analysis – Neighbor Breast Cancer Prediction Coimbra","authors":"I. G. Prahmana, Kristina Annatasia Br Sitepu","doi":"10.59934/jaiea.v1i3.97","DOIUrl":"https://doi.org/10.59934/jaiea.v1i3.97","url":null,"abstract":"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.","PeriodicalId":320979,"journal":{"name":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116266342","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}

引用次数: 0