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10th Annual International conference of Information and communication Technology (IcIcT)

作者： Wang, Huan-Bin Gao, Yang-Jun Airforce Engn Univ Coll Equipment Management & Unmanned Aerial Vehic Xian 710051 Shanxi Peoples R China

By analyzing the shortcomings of c4.5 decision tree algorithm, this paper combines MapReduce parallel model in Hadoop platform with c4.5 decision tree algorithm, so that c4.5 algorithm can be executed in parallel, so as to improve the efficiency of the algorithm. The improved c4.5 algorithm implementation process is given and the process is analyzed. Finally, the c4.5 algorithm improved experimental environment configuration is explained. (c) 2021 The Authors. Published by Elsevier B.V.

关键词： MapReduce Data mining c4.5 algorithm Parallelization

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Research on c4.5 algorithm improvement strategy based on MapReduce

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Procedia computer Science 2021年 183卷 160-165页

作者： Huan-Bin Wang Yang-Jun Gao College of Equipment Management And Unmanned Aerial Vehicle Engineering of Airforce Engineering University ShanXi Xi’an 710051 China

关键词： MapReduce Data mining c4.5 algorithm Parallelization

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Design of Decision Support System with c4.5 algorithm Methods in Determining Results Vaname Shrimp cultivation 5

Design of Decision Support System with C4.5 Algorithm Method...

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5th International conference on New Media Studies (cONMEDIA)

作者： Tobing, Fenina Adline Twince Dzulhaq, Muhammad Iqbal Overbeek, Marlinda Vasty Setiawan, Eko Anto Univ Multimedia Nusantara Informat Dept Fac Tech & Informat Tangerang Banten Indonesia STMIK Bina Sarana Global Informat Tech Depatrment Tangerang Banten Indonesia

ISBN: (纸本)9781728107264

Water quality has a very important role in the success of shrimp farming. Water as a living medium for shrimp, has a direct effect on the health and growth of shrimp. Water quality determines the existence of various types of organisms in the pond ecosystem, both for shrimp and other biota. Water quality that is far from the optimal value can cause cultivation failure, while optimal water quality can support shrimp growth. This study aims to build a decision support system to help companies manage water quality to get good shrimp farming results. The attributes used are water height, salinity, DO, pH, temperature, alkalinity and target size attributes of shrimp. The data used were 93 data partitioned into 76 training data and 17 testing data. Based on the classification results using the c4.5 algorithm, accuracy was 76.47%, precision was 72.72% and recall was 88.88%. From this study it was proven that the decision support system with the c4.5 algorithm can be used to determine the results of vaname shrimp farming.

关键词： Shrimp cultivation Decision Support System c4.5 algorithm

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Nutritional Status of Infants classification by calculating Anthropometry Through c4.5 algorithm

Nutritional Status of Infants Classification by Calculating ...

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International conference on Electrical, Electronics and Information Engineering (IcEEIE)

作者： Wirawan, I. Made Widiyaningtyas, Triyanna Nurwakiah, Siti B. Univ Negeri Malang Dept Elect Engn Malang Indonesia Univ Negeri Malang Informat Engn Malang Indonesia

ISBN: (纸本)9781728141602

According to the research by Directorate General of Public Health, Ministry of Health Republic of Indonesia in 2015, a nutritional issue in Indonesia is still occurring. In accordance with the standard stipulated by WHO, ideally the prevalence of lean and short infants in certain area should be less than 25%. However, in Indonesia, 17.2% infants (0-60 months infants) have obese, lean, and very lean body compare to BB/U (weight index) index. A number of 29 % infants (0-60 months infants) have short and very short body compare to TB/U (height index) index. A number of 20.4% infants (0-60 months infants) are lack of nutrition or malnutrition. The stages of this research were (1) collecting data, (2) preprocessing data with data transformation, (3) classification process using c4.5 algorithm, and (4) evaluation testing results using c4.5 algorithm to calculate accuracy, precision, recall, and error rate through confusion matrix. Hence, in this research, the nutritional status of infants is classified according to Body Weight and Height indices using c4.5 algorithm. The results indicate that the average score of accuracy was 93.60% and the error rate was 6.40%.

关键词： c4.5 algorithm infants nutrition anthropometry

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The Research and Analysis in Decision Tree algorithm Based on c4.5 algorithm 3

The Research and Analysis in Decision Tree Algorithm Based o...

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3rd IEEE Advanced Information Technology, Electronic and Automation control conference (IAEAc)

作者： Hao, Huan chen, Tieming Lu, Jing Liu, Jie Ma, Xiaodan Xian High Tech Inst Tongxin Rd 2 Xian Shaanxi Peoples R China

ISBN: (纸本)9781538645093

On the base of introducing the Decision Tree, this article lists two main algorithms of Decision Tree. After describing the principle of briefly, it reveals the essential idea and the computing process of c4.5 algorithm in detail. As constructing a Decision Tree on a group of instance data with the two algorithms, we get the principle of classification about the data. By comparing the two algorithms during the process of constructing the tree, we analysis the advantages and disadvantages of them finally. With the conclusion of the applied scope of each algorithm, it provides a theoretical basis for choosing an appropriate method in practical application.

关键词： The Decision Tree c4.5 algorithm ID3 algorithm

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Analysis of Students Graduation Target Based on Academic Data Record Using c4.5 algorithm case Study: Information Systems Students of Telkom University 6

Analysis of Students Graduation Target Based on Academic Dat...

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6th International conference on cyber and IT Service Management (cITSM)

作者： Putri, Dela Youlina Andreswari, Rachmadita Hasibuan, Muhammad Azani Telkom Univ Sch Ind Engn Study Program Informat Syst Jl Telekomunikasi 01 Bandung 40257 West Java Indonesia

ISBN: (纸本)9781538654330

Study program of Information Systems is one of the existing study programs at Telkom University which has produced many graduates until 2017. However, not all graduates produced successfully completed the study period during four years of normal study period in which may cause the decrease of study programs quality and affect the assessment of study program if there is an audit or evaluation so it can affect the achievement level of the study program. To solve the problem can be by making a prediction model of student graduation that can be obtained from data classification process using decision tree with algorithm c4.5 and implement it to the academic data record of existing student so that got two group of student, that is student which predicted pass on time and student predicted to pass late. From the results of the classification of student data can be done an analysis of what factors that can affect the graduation of students who are predicted to pass on time and plan appropriate strategies for groups of students who may not pass on time. The data classification process is done with the help of open source based tools using RapidMiner application. The result of the classification is a prediction model that has an accuracy value of 82.24% and states that the most influential factor in predicting students' graduation is GPA in the second year. The result of the student's graduation classification is expected to be used as the reference base to support the academic planner in making the right decision to the student groups generated so that all students can graduate on time.

关键词： student passing prediction data classification decision tree c4.5 algorithm RapidMiner

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Factors Affecting Household Electrical Usage Using c4.5 algorithm 6

Factors Affecting Household Electrical Usage Using C4.5 Algo...

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6th International conference on cyber and IT Service Management (cITSM)

作者： Nasari, Fina Dewi, Rofiqoh Fujiati Univ Potensi Utama Jl KL Yos Sudarso Km 6-5 3 A Medan 20241 Indonesia

ISBN: (纸本)9781538654330

this paper is part of the classification, focusing on the classification of high household electrical usage. Electricity needs are increasing while availability is getting smaller, requiring solution in its utilization to be more effective and efficient. It is important to classify factors that lead to high electricity consumption among households using the c4.5 algorithm. The c4.5 algorithm is a fairly effective algorithm to help shape decision trees. This research is able to classify the high usage of household electricity. The result of this research get the main factor of high household electric usage is the number of family member with the value of gain 84,2%. Testing of rules generated with average test result 81.69%. It is hoped that the future will become the basis for the wider use of electricity.

关键词： electricity c4.5 algorithm clasification Decision tree

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Rainfall Forecasting in Bandung Regency using c4.5 algorithm 6

Rainfall Forecasting in Bandung Regency using C4.5 Algorithm

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6th International conference on Information and communication Technology (IcoIcT)

作者： Suyatno, Joko Azhari Nhita, Fhira Rohmawati, Aniq Atiqi Telkom Univ Computat Sci Bandung 40257 Indonesia

ISBN: (纸本)9781538645727

Bandung regency is one of Indonesian city that majority of the people are farmers. Farmers need weather information to determine the planting season. Weather forecasting become an orientation in agriculture sector to determining the beginning of planting season, and also quality and quantity of their harvest. One of the factors that affecting the harvest is rainfall. In this research, we make a classification model using c4.5 algorithm for rainfall forecasting at Bandung regency. Then, the postpruning method is used to optimize pruning on the model. We used a weather data from BMKG (Meteorological, climatological, and Geophysical Agency) in 2005 to 2016 period. The result of average accuracy testing without pruning is 60% and using pruning is 93.33%.

关键词： rainfall c4.5 algorithm pruning data mining

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Application of c4.5 classification algorithm for chronic Kidney Disease Diagnosis

Application of C4.5 Classification Algorithm for Chronic Kid...

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International conference on Electrical, Electronics and Information Engineering (IcEEIE)

作者： Wati, Masna Pakpahan, Herman Santoso Prafanto, Anton Akbar, Fahmi Haviluddin, Haviluddin Boernama, Ade Widyatama Dian Mulawarman Univ Dept Informat Engn Samarinda Indonesia

ISBN: (纸本)9781728141602

The data from Ministry of Health Indonesia in the report infoDATIN 2017 mention that the chronic kidney disease was the 27th leading cause of death globally then upward to 18th in 2010. In the report also states that chronic kidney disease prevalence increases with the rising in elderly population and also the increased cases of diabetes mellitus and hypertension. The difficulty of early detection is one reason for the study of the disease. The c4.5 algorithm is used to obtain a model for detecting chronic kidney disease. The classification model was built using 400 patient data as a dataset and 24 attributes in the form of symptoms suffered by patients. The c4.5 algorithm generates the decision tree so that it is simple to implement the classification model formed into the software with the ways a decision tree translated into classification rules. This algorithm was chosen because some other research in the same study case also shows the results that the c4.5 algorithm has an accuracy rate above 50%. The results of the model testing produced by the c4.5 algorithm show the accuracy rate is 97.50% and a precision rate is 97.33% with a ROc curve (AUc) of 0.978. Thus, the software was built using the c4.5 classification model for diagnose chronic kidney disease diagnosis has an excellent classification category.

关键词： chronic Kidney Disease c4.5 algorithm classification ROc

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Improvement and Application of Decision Tree c4.5 algorithm

Improvement and Application of Decision Tree C4.5 Algorithm

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2018 International conference on computer,communication and Network Technology(ccNT 2018)

作者： Jie YE Li-duo HOU School of Computer and Engineering Guizhou University of Commerce School of Computer Science and Technology Guizhou University

The c4.5 algorithm as the most popular decision tree algorithm, there are still some deficiencies, c4.5 algorithm uses post-pruning to solve the over-fitting problem, but increase the modeling overhead, in response to this problem the idea of combining over-fitting branches ahead of time in the process of creating a decision tree is proposed and improved on the original c4.5 algorithm, which solves the problem of long decision-making time and large models of the decision tree. Experimental verification shows that the improved algorithm has a significant improvement in model simplification and model accuracy. The improved algorithm is applied to the "Engineering Quality Decision Support System" to provide supervision and decision-making support for the supervisory department.

关键词： Decision tree c4.5 algorithm Information entropy Pruning Engineering quality supervision

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