SISTEM PAKAR DIAGNOSA PENYAKIT JANTUNG KORONER DENGAN METODE PROBABILISTIC FUZZY DECISION TREE

2018 ◽  
Vol 4 (2) ◽  
pp. 106
Author(s):  
Wizra Aulia
Keyword(s):  
Blood Pressure ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chest Pain ◽  
Expert System ◽  
Decision Tree ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Id3 Algorithm ◽  
Anticipatory Action

<p><em>Di Indonesia, penyakit jantung koroner menempati posisi pertama sebagai penyakit yang paling banyak mengakibatkan kematian. Jika gejala penyakit jantung koroner  dikenali sejak dini maka dapat dilakukan tindakan antisipasi. Diagnosa dilakukan berdasarkan 6 gejala penyakit jantung koroner yaitu sakit dada, tekanan darah tinggi, kolesterol, kadar gula darah, hasil EKG dan jumlah denjut jantung. Metode yang dipakai adalah Probabilistic Fuzzy Decision Tree (PFDT) dengan algoritma  Probabilistic Fuzzy  ID3. Hasil keakuratan sistem pakar diagnosa penyakit jantung koroner dengan metode PFDT mencapai 95%.</em><em></em></p><p><em>In Indonesia, coronary heart disease the first position as the disease that most resulted in death. If symptoms of coronary heart disease are recognized early on, anticipatory action may be taken. Diagnosis is based on 6 symptoms of coronary heart disease  chest pain, high blood pressure, cholesterol, blood sugar, ECG results and </em>heartbeat<em>. The method used is Probabilistic Fuzzy Decision Tree (PFDT) with Probabilistic Fuzzy ID3 algorithm. The result of accuracy of expert system of diagnosis of coronary heart disease by PFDT method reached 95%.</em></p>

Chest pain is inversely associated with blood pressure during exercise among individuals being assessed for coronary heart disease

2007 ◽  
Vol 44 (2) ◽  
pp. 183-188 ◽  
Author(s):  
Blaine Ditto ◽  
Bianca D'Antono ◽  
Gilles Dupuis ◽  
Denis Burelle
Keyword(s):  
Blood Pressure ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chest Pain

scholarly journals Fuzzy Decision Tree to Predict Student Success in Their Studies

2020 ◽  
Vol 1 (3) ◽  
pp. 135-144
Author(s):  
Heri Bambang Santoso
Keyword(s):  
Decision Tree ◽  
Fuzzy Inference ◽  
Drop Out ◽  
Classification Rules ◽  
University Management ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Inference System ◽  
Target Time ◽  
Id3 Algorithm

The number of students graduating on time is one of the important aspects in the assessment of accreditation of a university. But the problem is still a lot of students who exceed the target time of graduation. Therefore, the prediction of graduation on time can serve as an early warning for the university management to prepare strategies related to the prevention of cases of drop out. The purpose of this research is to build a model using fuzzy decision tree to form the classification rules are used to predict the success of a student's study using fuzzy inference system. Results of this study was generated model of the number of classification rules are 28 rules when the value θr is 98% and θn is 3%, with the level of accuracy is 95.85%. Accuracy of Fuzzy ID3 algorithm is higher than ID3 algorithms in predicting the timely graduation of students.

scholarly journals Application of Fuzzy Decision Tree Algorithm Based on Mobile Computing in Sports Fitness Member Management

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhu Gu ◽  
Chaohu He
Keyword(s):  
Decision Tree ◽  
Mobile Computing ◽  
Classification Accuracy ◽  
Decision Tree Algorithm ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Data Set ◽  
Tree Algorithm ◽  
Id3 Algorithm ◽  
Fitness Industry

After the reform and the opening, the economy of our country has developed rapidly, and the living conditions of the people have become better and better. As a result, they have a lot of time to pay attention to their health, which has promoted the rapid development of the sports and fitness industry in my country. In response to the increasing development of the sports and fitness sector of my country, the current state of the administration of members of the sports fitness industry does not keep pace with the development of the sports and fitness industry of my country. Based on this, this article uses a fuzzy decision tree algorithm to establish a decision tree based on the characteristics of customer data and loses existing customers. Analyzing the situation is of strategic significance for improving the competitiveness of the club. This article selects the 7 most commonly used data sets from the UCI data set as the initial experimental data for model training in three different formats and then uses the data of a specific club member to conduct experiments, using these data files as training samples to construct a vague analysis of the decision tree to overturn the customer to analyze the main factors of customer change. Experiments show that the fuzzy decision tree ID3 algorithm based on mobile computing has the highest accuracy in the Iris data set, reaching 97.8%, and the accuracy rate in the Wine data set is the smallest, only 65.2%. The mobile computing-based fuzzy decision tree ID3 algorithm proposed in this paper obtained the highest correct rate (86.32%). This shows that, compared to traditional analysis methods, the blurred decision tree obtained for churn client analysis has the advantages of high classification accuracy and is understandable so that ideal classification accuracy can be achieved when the tree is small.

A C4.5 Fuzzy Decision Tree Method for Multivariate Time Series Forecasting

2021 ◽  
Author(s):  
Rafael R. C. Silva ◽  
Walmir Matos Caminhas ◽  
Petronio Candido de Lima e Silva ◽  
Frederico Gadelha Guimaraes
Keyword(s):  
Time Series ◽  
Decision Tree ◽  
Multivariate Time Series ◽  
Time Series Forecasting ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Decision Tree Method ◽  
Tree Method

Chi-MFlexDT: Chi-square-based multi flexible fuzzy decision tree for data stream classification

2021 ◽  
pp. 107301
Author(s):  
Farnaz Mahan ◽  
Maryam Mohammadzad ◽  
Seyyed Meysam Rozekhani ◽  
Witold Pedrycz
Keyword(s):  
Decision Tree ◽  
Data Stream ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Chi Square ◽  
Stream Classification ◽  
Data Stream Classification

Weighted Fuzzy Decision Tree for Multi-Label Classification

2020 ◽  
Author(s):  
Sara Sardari ◽  
Ehsan Ahmadi ◽  
Mohammad Taheri ◽  
Mansoor Zolghadri Jahromi
Keyword(s):  
Decision Tree ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree

Optimization of integrated fuzzy decision tree and regression models for selection of oil spill response method in the Arctic

2021 ◽  
Vol 213 ◽  
pp. 106676
Author(s):  
Saeed Mohammadiun ◽  
Guangji Hu ◽  
Abdorreza Alavi Gharahbagh ◽  
Reza Mirshahi ◽  
Jianbing Li ◽  
...  
Keyword(s):  
Decision Tree ◽  
Oil Spill ◽  
Regression Models ◽  
The Arctic ◽  
Fuzzy Decision ◽  
Fuzzy Decision Tree ◽  
Oil Spill Response ◽  
Response Method ◽  
Selection Of
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