{"title":"Sistem Pakar Diagnosa Tingkat Depresi Pada Lansia Di Balai Sosial Tresna Werdha Menggunakan Metode Certainty Factor","authors":"M. AzhariMalindo, A. Chandra","doi":"10.47233/jsit.v1i2.116","DOIUrl":"https://doi.org/10.47233/jsit.v1i2.116","url":null,"abstract":"Depressive disorder in the elderly is a clinical and public health issue that has yet to be addressed. \u0000The elderly who live at home with their families have better physical, psychological, and environmental health than those who live in orphanages. Mental health issues, particularly depression, frequently go undiagnosed in the elderly. This is because older people who are depressed often have physical symptoms like insomnia, loss of appetite, stomach problems, and headaches. When older people are depressed, their bodies tend to hurt more. It is hard to tell whether someone is complaining about their body or mind, so depression is often found too late. To anticipate these issues, an expert system was created that can take the place of an expert in solving the problem. A clinical psychologist is an expert in the field of elderly depression. This study classified elderly depression into three levels: mild depression, moderate depression, and major depression. This study was carried out with the help of a case study from the Tresna Werdha Pakem Social Center in Sleman, DI Yogyakarta.The Certainty Factor method was used to make an expert system for determining how depressed an older person is. This is because it is a sure thing based on evidence or an expert's opinion. The goal of developing an expert system for diagnosing depression in the elderly is for expert and non-expert officers to diagnose the level of depression in the elderly. Based on 10 elderly data that the system and experts have tested by applying the Certainty Factor method, the accuracy was 98%.","PeriodicalId":302680,"journal":{"name":"Jurnal Sains dan Teknologi (JSIT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126627843","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}
{"title":"Peningkatan Rasio Kompresi Algoritma RLE Menggunakan Transormasi bwt","authors":"Rian Syahputra","doi":"10.47233/jsit.v2i1.133","DOIUrl":"https://doi.org/10.47233/jsit.v2i1.133","url":null,"abstract":"In file compression, especially image files, it is expected that the results obtained using a compression method will be smaller than before, because usually storage for image files uses a lot of memory capacity. To get better results, a combination of compression methods is used, namely BWT with RLE. To produce a better compression ratio, 2 scenarios are used, the first using the results from the second and third stages of the BWT algorithm. From the RLE algorithm, it was found that the size increased by 10%, with the results of the second stage of the BWT algorithm, the size ratio decreased by 58.33% and with the results of the third stage of the BWT algorithm, the size ratio increased by 44.44%.","PeriodicalId":302680,"journal":{"name":"Jurnal Sains dan Teknologi (JSIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129554500","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}
{"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":"https://doi.org/10.47233/jsit.v1i2.115","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":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121077014","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}
{"title":"Sistem Pendukung Keputusan Pemilihan Supplier Bahan Baku Daging Menggunakan Metode Weighted Aggregated Sum Product Assesment (Waspas) (Studi Kasus : Kawasan Kuliner Sekar Mataram)","authors":"I. Agustin, P. Prasetyaningrum","doi":"10.47233/jsit.v2i3.203","DOIUrl":"https://doi.org/10.47233/jsit.v2i3.203","url":null,"abstract":"Individuals or businesses that supply or sell raw materials to other parties, whether individuals or businesses, so that they can be transformed into finished goods or services are referred to as suppliers. Suppliers must also make raw materials available to those who require them. Furthermore, the supplier must ensure that the raw materials are delivered to the buyer in good condition. The Sekar Mataram Culinary Area is located in Bantul City, Yogyakarta, specifically in Bangunjiwo Village. It is one of the business units owned by Village Owned Enterprises in Mbangun Kamulyan Bangunjiwo Village, which is growing and has received many offers from suppliers to supply raw meat materials to the Sekar Mataram Culinary Area. \u0000So far, the Sekar Mataram Culinary Area management has chosen raw meat suppliers through manual selection. Using the Weighted Aggregated Sum Product Assessment (WASPS) method, a Decision Support System will be built to determine the best raw material supplier and meet the restaurant's needs. This study requires criteria and alternatives to obtain a solution for making decisions on raw material supplier selection. This Decision Support System is web-based, making it more effective and efficient.","PeriodicalId":302680,"journal":{"name":"Jurnal Sains dan Teknologi (JSIT)","volume":"25 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120913438","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}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
