scholarly journals PENENTUAN TALENTA KARYAWAN BERDASARKAN MENGGUNAKAN KONSEP DATA MINING

2016 ◽  
Vol 2 (1) ◽  
pp. 34
Author(s):  
Ni G.A.P. Harry Saptarini
Keyword(s):  
Data Mining ◽  
Human Resources ◽  
Decision Maker ◽  
Conventional Method ◽  
Input Data ◽  
Linguistic Terms ◽  
Linguistic Term ◽  
C4.5 Algorithm ◽  
The Right

The human resources competency is one aspect that most affect company performances. Knowing its competence will help the decision maker to place the right man on the right place. However it can be done by analyzing the human talent. One of the conventional method that common to use is C4.5 algorithm. Conventional C4.5 method uses data crisp. In this study, it used a linguistic term as an input data because the talent test expressed using the language (linguistic term) and it is a set of data in fuzzy form. To generate the input data in the form of fuzzy was done by fuzzify the data preprocessing and further preprocessing of data results will be used for the construction of decision trees using C4.5 algorithm is then the process is called fuzzy C4.5. The result of this research is that the number of linguistic terms of attribute effect directly and significantly to system accuracy. The accuracy of Fuzzy C4.5 algorithm with 5 linguistic terms (90.1099%) is less than Fuzzy C4.5 accuracy with 3 linguistic terms (96.7033%). Fuzzy C4.5 accuracy with 3 linguistic terms has the same accuracy with conventional C4.5 (96.7033%), so we can use as an alternative solution to build classification of employee talent in PNB.

scholarly journals DECISION TREE C4.5 ALGORITHM FOR TUITION AID GRANT PROGRAM CLASSIFICATION (CASE STUDY: DEPARTMENT OF INFORMATION SYSTEM, UNIVERSITAS TEKNOKRAT INDONESIA)

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heni Sulistiani ◽  
Ahmad Ari Aldino
Keyword(s):  
Decision Tree ◽  
Classification Model ◽  
Grant Program ◽  
C4.5 Algorithm ◽  
Long Time ◽  
The Right ◽  
Short Time ◽  
Tuition Fee

In pandemic era, almost everyone struggles for their life. College students are such example. They have difficulty in paying tuition fee to continue their study. Based on this problematic situation, Universitas Teknokrat Indonesia grants the students who have good academic performance with tuition fee aid program. Many variables used for determining the grant made it hard to make a decision in a short time or even takes very long time. To make it easier for management to decide who is the right student to get grant, it needs classification model. The purpose of this study is the classification of grant recipients by using decision tree C4.5 algorithm. That can determine whether a potential student can be accepted as an awardee or not. Then, the results of the classification are validated with ten-fold cross validation with an accuracy, precision and recall with the score of 87 % for all part. It means the model perform quite well to be implemented into system.

scholarly journals Penerapan Algoritma C5.0 Untuk Prediksi Kelulusan Pembelajaran Mahasiswa Pada Matakuliah Arsitektur Sistem Komputer

2021 ◽  
Vol 5 (3) ◽  
pp. 1166
Author(s):  
Muchamad Sobri Sungkar ◽  
M Taufik Qurohman
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Extraction Process ◽  
Study Program ◽  
Data Set ◽  
C4.5 Algorithm ◽  
Previous Algorithm ◽  
Process Prediction ◽  
Computer System Architecture

Computer system architecture is one of the subjects that must be taken in the informatics engineering study program. In the study program the graduation of each student in the course is one of the important aspects that must be evaluated every semester. Graduation for each student / I in the course is an illustration that the learning process delivered is going well and also the material presented by the lecturer in charge of the course can be digested by students. Graduation of each student in the course can be predicted based on the habit pattern of the students. Data mining is an alternative process that can be done to find out habit patterns based on the data that has been collected. Data mining itself is an extraction process on a collection of data that produces valuable information for companies, agencies or organizations that can be used in the decision-making process. Prediction of graduation with data mining can be solved by classifying the data set. The C5.0 algorithm is an improvement algorithm from the C4.5 algorithm where the process is almost the same, only the C5.0 algorithm has advantages over the previous algorithm. The results of the C5.0 algorithm are in the form of a decision tree or a rule that is formed based on the entropy or gain value. The prediction process is carried out based on the classification of the C5.0 algorithm by using the attributes of Attendance Value, Assignment Value, UTS Value and UAS Value. The final result of the C5.0 algorithm classification process is a decision tree with rules in it. The performance of the C5.0 algorithm gets a high accuracy rate of 93.33%

scholarly journals Identification of Poison using C4.5 Algorithm

2020 ◽  
pp. 218-222
Author(s):  
Lai Lai Yee ◽  
Myo Ma Ma
Keyword(s):  
Data Mining ◽  
Test Data ◽  
Knowledge Worker ◽  
Training Data ◽  
Independent Data ◽  
Classification Rules ◽  
Natural Evolution ◽  
C4.5 Algorithm ◽  
Other Information

Data mining is the task of discovering interesting patterns from large amounts of data where the data can be stored in databases, data warehouses or other information repositories. This can be viewed as a result of the natural evolution of information technology. The key point is that data mining is the application of these and other AI and statistical techniques to common business problems in a fashion that makes these techniques available to the skilled knowledge worker as well as the trained statistics professional. This paper is classification system for Toxicology using C4.5. Firstly, the input data are randomly partitioned into two independent data, a training data and a test data. And then two third of the data are allocated to the training data and the remaining one third is allocated to the test data. Final step is C4.5 Algorithm Process, the training data is used to derive C4.5 algorithm. Classification Process, test data are used to estimate the accuracy of the classification rules. If the accuracy is considered acceptable the rules can be applied to the classification of new data.

scholarly journals Feature Selection in Classification of Blood Sugar Disease Using Particle Swarm Optimization (PSO) on C4.5 Algorithm

2020 ◽  
Vol 4 (3) ◽  
pp. 569-575
Author(s):  
Dwi Meylitasari Tarigan ◽  
Dian Palupi Rini ◽  
Samsuryadi
Keyword(s):  
Data Mining ◽  
Particle Swarm Optimization ◽  
Blood Sugar ◽  
Blood Sugar Level ◽  
Public Awareness ◽  
Particle Swarm ◽  
Data Mining Technique ◽  
Swarm Optimization ◽  
C4.5 Algorithm

Diabetes Mellitus (DM) is a disease caused by blood sugar level increased were higher than the maximum limit. Food consumed tends to contain uncontrolled sugar which could cause the drastic increase of blood sugar level. It is necessary to efforts, to increasing the public awareness to controlling blood sugar and the risks of increasing blood sugar level so as to determine of preventive and early detection measures One of used of data mining technique is information technology in the health sector which used a lot as a decision maker to predicting and diagnosing a several disease.  This research aims to optimizing the features on classification of the data mining with the C4.5 algorithm using Particle Swarm Optimization (PSO) to detect the blood sugar level in patient. The dataset used is the effect of physical activity to the Blood Sugar Level at H. Abdul Manan Simatupang Kisaran Regional Public Hospital.  The amount of dataset used is 42 record with 10 attributes.  The result of this research obtained that the Particle Swarm Optimization (PSO) may increasing the accuracy performance of C4.5 from 86% to 95%.  Whereas the evaluation result of the AUC Value increasing from 0,917 to 0,950. From those 10 attributes which are then selection with using PSO into 7 attributes used to determine the prediction of sugar level.  Therefore the Algorithm C4.5 using the Particle Swarm Optimization (PSO) may provide the best solution to the accuracy of detection blood sugar levels.

scholarly journals Penentuan Materi Layanan Bimbingan TIK Menggunakan Algoritma C4.5

KOMTEKINFO ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 19-28
Author(s):  
Montesna ◽  
Yuhandri ◽  
Jufriadif Na’am
Keyword(s):  
Data Mining ◽  
Computer Technology ◽  
Questionnaire Data ◽  
Unit Level ◽  
Information And Computer Technology ◽  
C4.5 Algorithm ◽  
Guidance Needs ◽  
The Right

Changes in curriculum from KTSP (Education Unit Level Curriculum) to 2013 Curriculum result in changes in Information and Computer Technology (ICT) subjects to ICT Guidance (BTIK). These subjects are not scheduled in general, so students need to be guided by questionnaires. To find out the right guidance needs data mining is needed. So this research is done in determining the accuracy of the guidance needs in accelerating the process of questionnaire data. The method used is C4.5 Algorithm. The results of the study have an accuracy of 90%, so it can be recommended in determining guidance material for students.

scholarly journals Analisa Kepuasan Pelanggan Menggunakan Klasifikasi Data Mining

2020 ◽  
Vol 2 (1) ◽  
pp. 41-48
Author(s):  
F Fauziah ◽  
Dedy Hartama ◽  
Irfan Sudahri Damanik
Keyword(s):  
Data Mining ◽  
Customer Satisfaction ◽  
Accuracy Rate ◽  
Level Of Satisfaction ◽  
C4.5 Algorithm ◽  
Data Source

The research objective was to obtain a model of rules in classifying the level of customer satisfaction at Indiis Cafe Pematangsiantar. By knowing the level of customer satisfaction, the owner of Indiis Cafe can improve the service if it is not good and further improve the service when the level of satisfaction is good. This study measures the level of customer satisfaction at Indiis Cafe Pematangsiantar. The method used in this study is the C4.5 Algorithm, where the data source used is a questionnaire / questionnaire given to customers at Indiis Cafe Pematangsiantar. The variables used include (1) Product, (2) Price, (3) Place (4) Promotion and (5) Service. The results of the study obtained 15 rules for the classification of customer satisfaction levels with 8 satisfied status rules and 7 unsatisfied rules. The C4.5 algorithm can be used in the case of customer satisfaction levels with an accuracy rate of 98.00%. From the results of the analysis is expected to be applied so that it can be used as a decision to improve service to customers.

Enterprise human resource management based on big data mining technology of internet of things

2021 ◽  
pp. 1-7
Author(s):  
He Ma
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Resource Management ◽  
Decision Tree ◽  
Human Resources ◽  
Human Resource Management ◽  
Human Resource ◽  
Information Technologies ◽  
Mining Technology ◽  
C4.5 Algorithm

Human resource management is an important part of business management. Through a set of scientific and effective management methods, human resource management for all employees and business owners of the enterprise. This research aims to explore how to use a large number of data mining and information technologies to solve the problems existing in the company’s human resource management. This course mainly studies the application of a large number of data mining theories, human resource management theory, the technical background of data mining, data mining process and analysis methods, analysis of their potential relationships, and existing problems, to improve the enterprise human resource management department the decision-making ability provides a reference. First, summarize the characteristics of the human resources market business, and compare the existing data mining algorithms. Here, a C4.5 algorithm in the decision tree algorithm is used to apply the job search information of the company’s recruitment of talents to scientifically analyze the information, during the selection and processing, and then the processing results are given to the C4.5 algorithm, and the corresponding decision tree is obtained. The results of this article show that the use of data mining technology can well solve corporate human resource management problems, such as the wages and benefits of corporate employees. Through big data analysis, it is easy to know that the salary of most doctoral diplomas is about 9,500 yuan, and the most salary for a college diploma is about 3,000 yuan (in remote areas). And according to your diploma, your major and benefits are different. Therefore, the human resources department of the enterprise can better discover talents.

Awareness and Decision Making in Professional Ethics

2000 ◽  
Vol 5 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Ronny Swain
Keyword(s):  
Decision Making ◽  
Professional Ethics ◽  
Ethical Decision Making ◽  
Code Of Ethics ◽  
Professional Autonomy ◽  
Ethical Awareness ◽  
Ethical Decisions ◽  
The Right ◽  
Aid Decision

The paper describes the development of the 1998 revision of the Psychological Society of Ireland's Code of Professional Ethics. The Code incorporates the European Meta-Code of Ethics and an ethical decision-making procedure borrowed from the Canadian Psychological Association. An example using the procedure is presented. To aid decision making, a classification of different kinds of stakeholder (i.e., interested party) affected by ethical decisions is offered. The author contends (1) that psychologists should assert the right, which is an important aspect of professional autonomy, to make discretionary judgments, (2) that to be justified in doing so they need to educate themselves in sound and deliberative judgment, and (3) that the process is facilitated by a code such as the Irish one, which emphasizes ethical awareness and decision making. The need for awareness and judgment is underlined by the variability in the ethical codes of different organizations and different European states: in such a context, codes should be used as broad yardsticks, rather than precise templates.

Contemporary Machiavellian theses "The strategy of the role of the absurd state as a model"

2020 ◽  
pp. 3
Author(s):  
Ali Hussein Hameed ◽  
Saif Hayder AL.Husainy
Keyword(s):  
International Relations ◽  
Decision Maker ◽  
Turning Point ◽  
Information Revolution ◽  
Main Hypothesis ◽  
The Subject ◽  
Area Of Influence ◽  
The Right ◽  
Modern Technologies

In the anarchism that governs the nature and patterns of international relations characterized by instability and uncertainty in light of several changes, as well as the information revolution and the resulting developments and qualitative breakthroughs in the field of scientific and advanced technological knowledge and modern technologies.  All of these variables pushed toward the information flow and flow tremendously, so rationality became an indispensable matter for the decision maker as he faces these developments and changes. There must be awareness and rationality in any activity or behavior because it includes choosing the best alternative and making the right decision and selecting the information accurately and mental processing Through a mental system based on objectivity, methodology, and accumulated experience away from idealism and imagination, where irrationality and anarchy are a reflection of the fragility of the decision-maker, his lack of awareness of the subject matter, his irresponsibility, and recklessness that inevitably leads to failure by wasting time and Effort and potential. The topic acquires its importance from a search in the strategies of the frivolous state and its characteristics with the ability to influence the regional, and what it revealed is a turning point in how to adapt from the variables and employ them to their advantage and try to prove their existence. Thus, the problem comes in the form of a question about the possibility of the frivolous state in light of the context of various regional and international events and trends. The answer to this question stems from the main hypothesis that (the aim which the frustrating state seeks to prove is that it finds itself compelled to choose several strategies that start from the nature of its characteristics and the goals that aim at it, which are centered in the circle of its interests in the field of its struggle for the sake of its survival and area of influence).

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

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