发布求助
文献互助 智能选刊 最新文献

Journal of Systems Engineering and Information Technology (JOSEIT)最新文献

筛选
英文 中文
Comparative Analysis of Naïve Bayes and Decision Tree Algorithms in Data Mining Classification to Predict Weckerle Machine Productivity Naïve贝叶斯与决策树算法在数据挖掘分类预测韦克尔机生产率中的比较分析
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-09-25 DOI: 10.29207/joseit.v1i2.3439
Fried Sinlae, Anugrah Sandy Yudhasti, Arief Wibowo
{"title":"Comparative Analysis of Naïve Bayes and Decision Tree Algorithms in Data Mining Classification to Predict Weckerle Machine Productivity","authors":"Fried Sinlae, Anugrah Sandy Yudhasti, Arief Wibowo","doi":"10.29207/joseit.v1i2.3439","DOIUrl":"https://doi.org/10.29207/joseit.v1i2.3439","url":null,"abstract":"The level of data accuracy in everyday life is necessary because it is reflected in the ever-advancing development of information technology. Analysis of data processing in information that can provide knowledge with the help of data mining systems. Algorithms commonly used for prediction are Naive Bayes and Decision Trees. The purpose of this study is to compare the Nave-Bayes algorithm and the decision tree algorithm in terms of the accuracy of predicting the productivity of the Weckerle machine at PT XYZ. The method used is a literature study from various related sources and understanding of the data in the source related to the subject of the classification method of the Naive Bayes algorithm and the decision tree into the data mining system. The results of this study are a classification using the Nave-Bayes algorithm with a higher level of confidence than the decision tree algorithm.","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130591913","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 Counting and Yolo Object Detection Methods for Identification Degree of Road Saturation 道路饱和度识别的计数和Yolo目标检测方法的实现
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-03-25 DOI: 10.29207/joseit.v1i1.1965
Rico Aditya Utama
{"title":"Implementation Counting and Yolo Object Detection Methods for Identification Degree of Road Saturation","authors":"Rico Aditya Utama","doi":"10.29207/joseit.v1i1.1965","DOIUrl":"https://doi.org/10.29207/joseit.v1i1.1965","url":null,"abstract":"Identification of road conditions such as congestion at this time still requires manual efforts in getting results. The congestion parameters certainly need to be monitored, especially in crowded areas and big city business centers, such as on Jalan Jendral Sudirman, Central Jakarta. Many parameters to identify the level of road congestion, one of them is by observing the value of the degree of road saturation. The purpose of this study is to propose a system that can calculate the value of the degree of saturation quickly and accurately using a camera. The method that is being proposed is to combine the Computer Vision with YOLO Object Detector techniques based on Deep Learning and the Object Counting method to get the value of traffic flow in the observed area. The results obtained by this system are quite good, this is supported by the error value obtained by the system around 3-4%.","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126218488","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
Determination of Sub-Contractors Using AHP and SAW Method 运用层次分析法和SAW法确定分包商
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-03-25 DOI: 10.29207/joseit.v1i1.1834
Arif Zikri, Adam Syahputra Cristanto, Imelda Imelda
{"title":"Determination of Sub-Contractors Using AHP and SAW Method","authors":"Arif Zikri, Adam Syahputra Cristanto, Imelda Imelda","doi":"10.29207/joseit.v1i1.1834","DOIUrl":"https://doi.org/10.29207/joseit.v1i1.1834","url":null,"abstract":"One factor in the durability of a contractor company is its sub-contractor. The management of sub-contractors for companies engaged in construction services is one aspect of the company's durability to be able to complete the project that the selection is doing manually by viewing one single file That is sent by the company who wants to be a sub-contactor, it is of course besides very troublesome also inefficient and time consuming quite a while. In determining the winner of the Procurement Committee is still having difficulty to determine the standard of the company that will become a sub-contractor, not to mention the assessment is subjective so that the elected candidate is not the best candidate. The methods used in this research use Analytical Hierarchy Process (AHP) for weighting of criteria and for calculation of value using Simple Additive Weighting (SAW) of the results of the research obtained from the SAW method used Obtained by the best sub-contractor of PT. 4Cipta with a total of 0.962 from 5 alternatives listed","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115558958","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: 1
Implementation of Decision Tree for Making Decision of Claim Product from Steel Production 决策树在钢铁产品索赔决策中的应用
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-03-25 DOI: 10.29207/joseit.v1i1.2233
A. Lestari, Saruni Dwiasnati
{"title":"Implementation of Decision Tree for Making Decision of Claim Product from Steel Production","authors":"A. Lestari, Saruni Dwiasnati","doi":"10.29207/joseit.v1i1.2233","DOIUrl":"https://doi.org/10.29207/joseit.v1i1.2233","url":null,"abstract":"Product Claims is requests from consumers for products purchased from suppliers in accordance with agreements agreed by both parties. Products that have been claimed from consumers produce historical data sets that can be used as evaluations for producers to produce higher quality products. This study aims to process production data and shipment data then classify the types of products claimed based on the results of claim report from consumers. Data mining can be extracted information from a very large amount of data with specific methods to obtain information or new science. The method used in this study is the C4.5 algorithm method using the production code attribute as a claim or non-claim label attribute. This study produced a decision tree of 4 variables, there are thick of product, width of product, weight of product, destination of product, and type of product claim as label. This decision tree concept collects data which then calculates the value of entropy and gain to determine the rule. The conclusion from this study is the C4.5 algorithm helps classify the product claims and form a decision tree that can provide information about production results and can ensure with consumers related to product limits that may be claimed according to the agreed agreement. Evaluation of the results obtained that the algorithm C4.5 is 99.9% accuracy.","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134472640","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 Analytic Network Process Algorithm in E-Lowker System 解析网络处理算法在E-Lowker系统中的实现
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-03-25 DOI: 10.29207/joseit.v1i1.1901
Herry Derajad Wijaya, Wawan Gunawan
{"title":"Implementation of Analytic Network Process Algorithm in E-Lowker System","authors":"Herry Derajad Wijaya, Wawan Gunawan","doi":"10.29207/joseit.v1i1.1901","DOIUrl":"https://doi.org/10.29207/joseit.v1i1.1901","url":null,"abstract":"Job vacancies information system at this time that there are still many companies that use the manual method to get the best employees and the number of job applicants who have not used the internet as a medium of information, but in this case the research aims to facilitate companies in getting the best employees, namely using the ANP Method in a web-based job information system and facilitate job applicants in utilizing internet media as a source of information that has been provided by the company. The ANP method is to find the weighted sum of the performance ratings for each alternative on all attributes, in this study the programming languages ​​used are PHP, MySQL database, CSS and Java Script. The criteria used in this study are education, experience, age and expertise. In this study shows that the Implementation of the ANP Method in the Web-Based Job Vacancy Information System is able to produce the best prospective workers for the company in accordance with the criteria","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130213512","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
Comparative Analysis of Deep Learning Models for Vehicle Detection 车辆检测中深度学习模型的比较分析
Journal of Systems Engineering and Information Technology (JOSEIT) Pub Date : 2022-03-25 DOI: 10.29207/joseit.v1i1.1960
Rendi Nurcahyo, M. Iqbal
{"title":"Comparative Analysis of Deep Learning Models for Vehicle Detection","authors":"Rendi Nurcahyo, M. Iqbal","doi":"10.29207/joseit.v1i1.1960","DOIUrl":"https://doi.org/10.29207/joseit.v1i1.1960","url":null,"abstract":"Deep Learning techniques are now widely used instead of traditional Computer Vision. There are many Deep Learning model algorithms for each use case such as Object Detection has several models, including Faster R-CNN, SSD, and YOLO v3. The performance and results of each Deep Learning model have advantages and disadvantages. Therefore, we must determine which model is suitable for the use cases and datasets that we have so that we can make the best Deep Learning model. Based on this need, this paper will make a comparative analysis of the Deep Learning model for Vehicle Detection (the spesific of Object Detection) from the models mentioned, namely, Faster R-CNN, SSD (Single Shot Detector), and YOLO v3 (You Only Look Once) to see the advantages and the disadvantages and which ones are the best. And after a comparison, it was concluded that of the three models mentioned only YOLO v3 model is able to be used as real time detection because it has low latency due to YOLO v3 only performs single convolution process so that it makes the process simpler and faster without reduce the accuracy.","PeriodicalId":367560,"journal":{"name":"Journal of Systems Engineering and Information Technology (JOSEIT)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123243498","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: 1
首页 上一页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信
小红书