检索结果-内蒙古大学图书馆

7th IEEE International Conference of computer science and Information Technology, ICOSNIKOM 2023

作者： Siregar, Rahmadani Hartono Roslina Zarlis, Muhammad Wanayumini Universitas Potensi Utama Computer Science Postgraduate Study Program Medan Indonesia Politeknik Negeri Medan Computer Science Postgraduate Study Program Medan Indonesia University of Bina Nusantara Computer Science Postgraduate Study Program Jakarta Indonesia

ISBN: (纸本)9798350360752

Disease detection in rice plants at the Padang Lawas District Agriculture Service is carried out every year by collecting data from the Agriculture Service. Therefore, it is necessary to carry out classification to determine the best percentage of training data and test data in determining rice plant diseases and a comparison between testing data and training data for accurate accurate predictions. So data mining algorithms are needed that must be used to classify these diseases. Classification is carried out to group data into categories or groups so that objects from the same data are more similar to data objects from different groups. In this study, disease classification was processed using the C4.5 algorithm using disease data collection on rice plants from 2017 to 2020 which had a total of 248 data. The results of testing data and training data will be compared to see accuracy performance. © 2023 IEEE.

关键词： Agriculture

来源：评论

学校读者我要写书评

暂无评论

New Student Prediction Using Algorithm Naive Bayes and Regression Analysis in Universitas Potensi Utama 4

New Student Prediction Using Algorithm Naive Bayes and Regre...

引用

4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Aditya, Elsa Situmorang, Zakarias Hayadi, B. Herawan Zarlis, Muhammad Wanayumini Universitas Potensi Utama Computer Science Postgraduate Study Program Medan Indonesia Saint Thomas Catholic University Computer Science Postgraduate Study Program Medan Indonesia University of Sumatera Utara Computer Science Postgraduate Study Program Medan Indonesia

ISBN: (纸本)9781665453950

Universitas Potensi Utama has various study programs, and also has various facilities to support student learning activities. However, the main obstacle in higher education is the uncertainty of the interest of students who register, so that sometimes the facilities are inadequate. To overcome these problems, there must be activities to predict prospective new student applicants to improve facilities and interest of prospective students to choose to study at the Universitas Potensi Utama. Forecasting is the most important thing that must be applied to a company. With this forecasting, companies can see the opportunities that exist to generate sales predictions in the future based on the results of past sales data. Naive Bayes is a classification using probability and statistical methods, the Naive Bayes algorithm can be used in scientific fields, one of which is predicting future opportunities based on previous experience. Linear regression method can be used for forecasting with the assumption that the correlation between variables will continue in the future. Linear Regression is a Regression Method where the resulting equation is linear. Based on the resulting equation, predictions can be calculated by entering the values of the predictor variables in the equation. Based on this process, the predictive value of the response variable can be generated. In this study, the author explains more about how to determine new student predictions using a combination of the two algorithms where the Naïve Bayes algorithm is used to state which study programs have a lot of interest in the coming year, and the Linear Regression algorithm is used to show which study programs are most in demand based on the number of students who registered in the previous year, In the description that has been stated above, the author makes a paper with the title: 'Predictions of New Student Registration Using the Naive Bayes Algorithm and Regression Analysis at the Universitas Potensi Utama'. ©

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Publication of the society's sensitive personal data in the legitimate site of the general election committee 2

Publication of the society's sensitive personal data in the ...

引用

2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Parwata, A. Aryanto, K.Y.E. Divayana, D.G.H. Study Program of Computer Science Postgraduate Program Ganesha University of Education Singaraja Indonesia

It is highly important to protect the society's sensitive personal data. The reason is that many personal data are published by the government institution without paying attention to the prevailing regulations. In this current study, the search for the data in the form of hyperlink with its contents in the legitimate site of the General Election Committees was conducted with the assistance of Crawling Web. The obtained contents were preprocessed using the Preprocessing Text, which were then weighted using the TF-IDF method before they were classified using the Nayve Bayes method. After that, an analysis on the types of the published sensitive personal and the extent of the publication based on the area groups was conducted. Out of 6,700 instances of the personal data which were analyzed, 6.430 were published. The personal data which were published were full name, place and date of birth, religion, marital status, ID Number of the government civil servants, identity card number, number of the tax payer, account number, mobile number, e-mail, address, position, and face photo. The level of publication based on the total data found was as follows: 11.45% in the Central General Election Committee, 21.60% in the eastern area, 17.01% in the central area and 49.94% in the eastern area. The accuracy of the Nave Bayes method averaged 96.99%. Prior to publication, the General Election Committee is recommended to respect someone's personal data as privacy and the data which would be published should obtain approval and an easily-contacted contact person. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Hypertext systems

来源：评论

学校读者我要写书评

暂无评论

Optimization of artificial neural networks to improve accuracy of vocational competence selection of vocational school students using nguyen-widrow 2

Optimization of artificial neural networks to improve accura...

引用

2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Christyaditama, I.G.P. Candiasa, I.M. Gunadi, I.G.A. Study Program of Computer Science Postgraduate Program Ganesha University of Education Singaraja Indonesia

The present study used Neural Network Backpropagation combined with Nguyen-Widrow to optimize the disadvantages of ANN causes, which is the difficulty in initializing initial weights. The test was conducted on a dataset of values in semesters 1 and 2. The test results show that the best performance in training model of artificial neural networks with Nguyen-widrow is the smallest average MSE error of 0.002 and the highest average accuracy of 96.38%. Training on artificial neural network model training data with Nguyen-widrow has the smallest MSE error, 0.000996 and the highest accuracy is 97.49% on architecture ANN 9-9.1 with training function parameters: traingdx, epoch: 1000, learning rate: 0.1, and error: 0.001. The best performance was also seen in testing the testing of artificial neural network models with Nguyen-widrow with the smallest average error-MSE of 0.026 and the highest average accuracy of 87.85%. Training data testing on artificial neural network models with Nguyen-widrow has the smallest error-MSE which is 0.004436 and the highest accuracy is 94.50% on architecture ANN 9-9.1 with training function parameters: traingdx, epoch: 1000, learning rate: 0.1, and error: 0.001. The artificial neural network model with Nguyen-widrow has an accuracy difference of 8.53% smaller than the artificial neural network model with an accuracy difference of 9.28%. It can be concluded that the Artificial Neural Network with Nguyen-Widrow can overcome the ANN problem in determining initial weights so that it gives an increase in the accuracy of the prediction of students' competency selection better than the Artificial Neural Network without Nguyen-Widrow. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Evaluation of governance financial management information system (SIPKD) with framework of COBIT 5 in the government of Denpasar city 2

Evaluation of governance financial management information sy...

引用

2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Vergantana, I.W.S.M. Dantes, I.G.R. Aryanto, K.Y.E. Study Program of Computer Science Postgraduate ProgramGanesha University of Education Singaraja Indonesia

Denpasar City Government is one of the government agencies that hav implemented the Regional Financial Management Information System (SIPKD). SIPKD is an integrated application that is used as a tool for regional governments for improving the effectiveness of the implementation of various regulations in the field of regional financial management based on the principles of efficiency, economic, effective, transparent, accountable and auditable. Research Evaluation of SIPKD governance in Denpasar City Government was conducted based on the framework of the COBIT 5 (Control Objective for Information & Related Technology) framework of ISACA 2012, which was modified according to the conditions at the study site. The research method used was descriptive-quantitative evaluation and cascading evaluation method at the COBIT 5 stage, by distributing questionnaires to each admin as many as 40 respondents, to get scores in the form of numbers and conducting structured interviews with BPKAD leaders to obtain the expected capability level conditions. Evaluation of SIPKD governance with COBIT 5 uses the PAM (Process Assessment Model) analysis as a reference in determining its attributes, with the results of the capability level currently at the level 3 established process in the APO01 process of 77% achieved, APO012 of 78% achiaved, DSS04 by 77% mostly achiaved, EDM03 by 78% largely achieved, and MEA03 by 77% largely achieved, which means that in the management of SIPKD the Denpasar City Government has been well established in managing SIPKD conducted by all SIPKD administrators and operators along with BPKAD leaders in Denpasar. And the results of the interview the desired results are at level 4 predictable process. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Interactive Multimedia Kolb Experiential Learning Model Using Logistic Regression Algorithm to Improve Student Cognitive

Interactive Multimedia Kolb Experiential Learning Model Usin...

引用

7th International Conference on Advances in Visual Informatics, IVIC 2021

作者： Khoirunnisa, Azizah Nurul Munir Rasim Rahman, Eka Fitrajaya Dewi, Laksmi Curriculum Development Study Program School of Postgraduate Studies Indonesia University of Education Bandung Indonesia Computer Science Education Study Program Department of Computer Science Education Indonesia University of Education Bandung Indonesia

ISBN: (纸本)9783030902346

The differences of each student become a challenge for educators in delivering learning materials. More often than not, students often find it difficult to process study materials. Conventional study-based learning may not always have a profound impact on students. Consideration of interactive multimedia as a tool for student-centered learning has not been widely discussed in scientific research. In this paper, the authors investigate interactive multimedia using Kolb’s experiential learning model in improving students’ cognitive abilities. This study uses a pre-experimental method and one-group pre-and post-test design type with the research population in class XI RPL and a sample of SMK students in Bandung. The results show that the application of interactive multimedia using Kolb’s experiential learning model is effective in improving students’ cognitive abilities. On the other hand, it is found that combining abstract learning materials with interactive visuals and activities that involve students’ participation could create exceptionally positive feedback from students. © 2021, Springer Nature Switzerland AG.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Determination of C4.5 Algorithm Performance Based on Training Data and Testing Data in Determining Diseases in Rice Plants

Determination of C4.5 Algorithm Performance Based on Trainin...

引用

International Conference of computer science and Information Technology

作者： Rahmadani Siregar Hartono Roslina Muhammad Zarlis Wanayumini Computer Science Postgraduate Study Program Universitas Potensi Utama Medan Indonesia Computer Science Postgraduate Study Program Politeknik Negeri Medan Medan Indonesia Computer Science Postgraduate Study Program University of Bina Nusantara Jakarta Indonesia

关键词：

来源：评论

学校读者我要写书评

暂无评论

New Student Prediction Using Algorithm Naive Bayes And Regression Analysis In Universitas Potensi Utama

New Student Prediction Using Algorithm Naive Bayes And Regre...

引用

International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Elsa Aditya Zakarias Situmorang B. Herawan Hayadi Muhammad Zarlis Wanayumini Computer Science Postgraduate Study Program Universitas Potensi Utama Medan Indonesia Computer Science Postgraduate Study Program Saint Thomas Catholic University Medan Indonesia Computer Science Postgraduate Study Program University of Sumatera Utara Medan Indonesia

ISBN: (纸本)9781665453967

Universitas Potensi Utama has various study programs, and also has various facilities to support student learning activities. However, the main obstacle in higher education is the uncertainty of the interest of students who register, so that sometimes the facilities are inadequate. To overcome these problems, there must be activities to predict prospective new student applicants to improve facilities and interest of prospective students to choose to study at the Universitas Potensi Utama. Forecasting is the most important thing that must be applied to a company. With this forecasting, companies can see the opportunities that exist to generate sales predictions in the future based on the results of past sales data. Naive Bayes is a classification using probability and statistical methods, the Naive Bayes algorithm can be used in scientific fields, one of which is predicting future opportunities based on previous experience. Linear regression method can be used for forecasting with the assumption that the correlation between variables will continue in the future. Linear Regression is a Regression Method where the resulting equation is linear. Based on the resulting equation, predictions can be calculated by entering the values of the predictor variables in the equation. Based on this process, the predictive value of the response variable can be generated. In this study, the author explains more about how to determine new student predictions using a combination of the two algorithms where the Naïve Bayes algorithm is used to state which study programs have a lot of interest in the coming year, and the Linear Regression algorithm is used to show which study programs are most in demand based on the number of students who registered in the previous year, In the description that has been stated above, the author makes a paper with the title: “Predictions of New Student Registration Using the Naive Bayes Algorithm and Regression Analysis at the Universitas Potensi Utama”.

关键词： Uncertainty Linear regression Companies Prediction algorithms Mathematical models Classification algorithms Naive Bayes methods

来源：评论

学校读者我要写书评

暂无评论

Technology of Holobox Augmented Reality Grebeg Pancasila rite for Mathematics learning in Elementary School 2

Technology of Holobox Augmented Reality Grebeg Pancasila rit...

引用

2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Septinaningrum, S. Hakam, K.A. Setiawan, W. Agustin, M. Sopandi, W. Surur, A.S. Study Program of Elementary Education Postgraduate Program Universitas Pendidikan Indonesia Bandung Indonesia Department of Islamic Elementary Teacher Education State Institute of Tulungagung for Islamic Studies Tulungagung Indonesia Department of Character and General Education Faculty of Social Science Education Universitas Pendidikan Indonesia Bandung Indonesia Department of Computer Science Education Universitas Pendidikan Indonesia Bandung Indonesia Department of Early Childhood Education Universitas Pendidikan Indonesia Bandung Indonesia

The use of technology in learning needs to be encouraged starting from the elementary school level. Another thing that needs to be encouraged is local wisdom-based media to support character learning. This study aims to develop holobox augmented reality technology media of local wisdom of the Grebeg Pancasila rite for mathematics learning in elementary schools. This research produces multimedia based on technology Holobox Augmented Reality (AR) with the content of material Grebeg Pancasila for learning mathematics and building spaces in elementary schools. The method in media development using the Development Life Cycle developed by Luther consists of six stages, namely: concept, design, material collection, assembly, testing, and distribution. The media produced meets the standard of feasibility and can provide information and knowledge about understanding the concept of flat and space structures through the flag and gunungan symbols in the Rite Grebeg Pancasila. The implication of this study is that cultural diversity in local wisdom of the Rite Grebeg Pancasila can be used as a medium for learning mathematics in elementary schools (MI/SD) through Technology Holobox. Augmented Reality. © Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Publication of the society's sensitive personal data in the legitimate site of the general election committee

引用

Journal of Physics: Conference Series 2020年第1期1516卷

作者： A Parwata K Y E Aryanto D G H Divayana Study Program of Computer Science Postgraduate Program Ganesha University of Education Singaraja Indonesia

It is highly important to protect the society's sensitive personal data. The reason is that many personal data are published by the government institution without paying attention to the prevailing regulations. In this current study, the search for the data in the form of hyperlink with its contents in the legitimate site of the General Election Committees was conducted with the assistance of Crawling Web. The obtained contents were preprocessed using the Preprocessing Text, which were then weighted using the TF-IDF method before they were classified using the Naїve Bayes method. After that, an analysis on the types of the published sensitive personal and the extent of the publication based on the area groups was conducted. Out of 6,700 instances of the personal data which were analyzed, 6.430 were published. The personal data which were published were full name, place and date of birth, religion, marital status, ID Number of the government civil servants, identity card number, number of the tax payer, account number, mobile number, e-mail, address, position, and face photo. The level of publication based on the total data found was as follows: 11.45% in the Central General Election Committee, 21.60% in the eastern area, 17.01% in the central area and 49.94% in the eastern area. The accuracy of the Naїve Bayes method averaged 96.99%. Prior to publication, the General Election Committee is recommended to respect someone's personal data as privacy and the data which would be published should obtain approval and an easily-contacted contact person.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：