{"title":"系统专家诊断基于Web的皮肤问题的方法Naive Bayes Classifier","authors":"Caesar Iskandar Mawikere","doi":"10.47233/jsit.v1i2.115","DOIUrl":null,"url":null,"abstract":"As we all know, the world of technology and information has become very advanced in recent years. This has led to numerous new ideas that make it easier for a person or organization to do their work and achieve their goals. Progress in technology and information greatly affects all areas, from culture and education to the economy, health, and even beauty. So, in this study, the researcher brought up a problem at a beauty clinic in Maguwoharjo, DIY, called Emila Aesthetic Solution. The problem is that consulting with patients is still done face-to-face. In other words, the clinic does not have a computerized system to help with consultations so that patients do not have to wait in line and can get treatment right away based on the results of their consultation. As a result, this study focused on developing an expert system to diagnose skin problems using the naïve Bayes classifier method.In this study, the system was made using the naïve Bayes classifier and the waterfall model for system development. The model was then coded into the system to be used. The goal of making this expert system was to make it easier for patients to get advice and for the clinic to handle patients.Based on the patient history data obtained, namely 20 patient data that experts have tested, this expert system, by implementing the naïve Bayes classifier method, yielded results indicating that the system's accuracy was 100 percent.","PeriodicalId":302680,"journal":{"name":"Jurnal Sains dan Teknologi (JSIT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sistem Pakar Diagnosis Masalah Kulit Yang Berbasis Web Dengan Metode Naive Bayes Classifier\",\"authors\":\"Caesar Iskandar Mawikere\",\"doi\":\"10.47233/jsit.v1i2.115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As we all know, the world of technology and information has become very advanced in recent years. This has led to numerous new ideas that make it easier for a person or organization to do their work and achieve their goals. Progress in technology and information greatly affects all areas, from culture and education to the economy, health, and even beauty. So, in this study, the researcher brought up a problem at a beauty clinic in Maguwoharjo, DIY, called Emila Aesthetic Solution. The problem is that consulting with patients is still done face-to-face. In other words, the clinic does not have a computerized system to help with consultations so that patients do not have to wait in line and can get treatment right away based on the results of their consultation. As a result, this study focused on developing an expert system to diagnose skin problems using the naïve Bayes classifier method.In this study, the system was made using the naïve Bayes classifier and the waterfall model for system development. The model was then coded into the system to be used. The goal of making this expert system was to make it easier for patients to get advice and for the clinic to handle patients.Based on the patient history data obtained, namely 20 patient data that experts have tested, this expert system, by implementing the naïve Bayes classifier method, yielded results indicating that the system's accuracy was 100 percent.\",\"PeriodicalId\":302680,\"journal\":{\"name\":\"Jurnal Sains dan Teknologi (JSIT)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Sains dan Teknologi (JSIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47233/jsit.v1i2.115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Sains dan Teknologi (JSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47233/jsit.v1i2.115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sistem Pakar Diagnosis Masalah Kulit Yang Berbasis Web Dengan Metode Naive Bayes Classifier
As we all know, the world of technology and information has become very advanced in recent years. This has led to numerous new ideas that make it easier for a person or organization to do their work and achieve their goals. Progress in technology and information greatly affects all areas, from culture and education to the economy, health, and even beauty. So, in this study, the researcher brought up a problem at a beauty clinic in Maguwoharjo, DIY, called Emila Aesthetic Solution. The problem is that consulting with patients is still done face-to-face. In other words, the clinic does not have a computerized system to help with consultations so that patients do not have to wait in line and can get treatment right away based on the results of their consultation. As a result, this study focused on developing an expert system to diagnose skin problems using the naïve Bayes classifier method.In this study, the system was made using the naïve Bayes classifier and the waterfall model for system development. The model was then coded into the system to be used. The goal of making this expert system was to make it easier for patients to get advice and for the clinic to handle patients.Based on the patient history data obtained, namely 20 patient data that experts have tested, this expert system, by implementing the naïve Bayes classifier method, yielded results indicating that the system's accuracy was 100 percent.