Research on Asset Recognition Algorithm of Information Security Product Based on Decision Tree Algorithm

2013 ◽  
Vol 397-400 ◽  
pp. 2296-2300 ◽  
Author(s):  
Fei Shuai ◽  
Jun Quan Li
Keyword(s):  
Computational Complexity ◽  
Information Security ◽  
Decision Tree ◽  
Recognition Algorithm ◽  
Space Complexity ◽  
Complex Relationship ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C4.5 Algorithm ◽  
C4.5 Decision Tree

In current, there are complex relationship between the assets of information security product. According to this characteristic, we propose a new asset recognition algorithm (ART) on the improvement of the C4.5 decision tree algorithm, and analyze the computational complexity and space complexity of the proposed algorithm. Finally, we demonstrate that our algorithm is more precise than C4.5 algorithm in asset recognition by an application example whose result verifies the availability of our algorithm.Keywordsdecision tree, information security product, asset recognition, C4.5

The Analysis and Application of the C4.5 Algorithm in Decision Tree Technology

2012 ◽  
Vol 457-458 ◽  
pp. 754-757
Author(s):  
Hong Yan Zhao
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Teaching Quality ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C4.5 Algorithm ◽  
C4.5 Decision Tree ◽  
Result Analysis

The Decision Tree technology, which is the main technology of the Data Mining classification and forecast, is the classifying rule that infers the Decision Tree manifestation through group of out-of-orders, the non-rule examples. Based on the research background of The Decision Tree’s concept, the C4.5 Algorithm and the construction of The Decision Tree, the using of C4.5 Decision Tree Algorithm was applied to result analysis of students’ score for the purpose of improving the teaching quality.

scholarly journals METODE ALGORITMA DECISION TREE C4.5 UNTUK ANALISIS KELAYAKAN KREDIT NASABAH PADA BSM KCP KEMANG PRATAMA

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Dyah Wulandari ◽  
Nur Lutfiyana ◽  
Heny Sumarno
Keyword(s):  
Decision Tree ◽  
Profit Sharing ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
Customer Data ◽  
A Value ◽  
C4.5 Algorithm ◽  
C4.5 Decision Tree ◽  
Credit Worthiness

Abstract - Credit is the provision of money or equivalent claims, based on agreements or agreements on loans between banks and other parties which require the borrowing party to repay the debt after a certain period of time with the amount of interest, compensation or profit sharing. From the credit customer data available at BSM KCP Kemang Pratama still has Non Performing Financing (NPF) or Bad Credit.In analyzing a credit sometimes an analyst does an inaccurate analysis, so there are some customers who are less able to make credit payments, resulting in bad credit. So the researchers conducted an analysis using the C4.5 decision tree algorithm and Rapid Miner application for determining credit worthiness. From the analysis of credit customer data using the C4.5 decision tree algorithm method, the feasibility of credit recipient customers is very effective and produces a value of accuracy on Rapid Miner 5.3 of 80%, Precision of 100% and Recall of 0% so as to minimize the risk.Keywords— Credit, C4.5 Algorithm, Rapid Miner, Value AccuracyAbstrak - Kredit merupakan penyediaan uang atau tagihan yang dapat disamakan dengan hal itu, berdasarkan persetujuan atau kesepakatan pinjaman-pinjaman antara bank dengan pihak lain yang mewajibkan pihak peminjam untuk melunasi utangnya setelah jangka waktu tertentu dengan jumlah bunga, imbalan atau pembagian hasil keuntungan. Dari data nasabah kredit yang ada pada BSM KCP Kemang Pratama masih memiliki Non Performing Financing (NPF) atau Kredit Macet. Dalam menganalisa sebuah kredit terkadang seorang analis melakukan analisa tidak akurat, sehingga ada beberapa nasabah yang kurang mampu dalam melakukan pembayaran kredit, dan pada akhirnya mengakibatkan kredit macet. Peneliti melakukan analisis menggunakan algoritma decision tree C4.5 dan aplikasi Rapid Miner untuk penentuan kelayakan pemberian kredit. Dari analisis data nasabah kredit menggunakan metode Algoritma decision tree C4.5 menghasilkan kelayakan nasabah penerima kredit sangat efektif dan menghasilkan nilai akurasi pada Rapid Miner 5.3 sebesar 80%, Precision sebesar 100% dan Recall sebesar 0% sehingga dapat meminimalisir resiko yang terjadi.Kata kunci— Kredit, Algoritma C4.5, Rapid Miner, Nilai Akurasi

scholarly journals Optimization of Management Mode of Small- and Medium-Sized Enterprises Based on Decision Tree Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yuzhu Diao ◽  
Qing Zhang
Keyword(s):  
Project Management ◽  
Decision Tree ◽  
Performance Appraisal ◽  
Information Gain ◽  
Decision Tree Algorithm ◽  
Management Information ◽  
Report Generation ◽  
Tree Algorithm ◽  
Gain Rate ◽  
C4.5 Algorithm

Decision tree algorithm is a common classification algorithm in data mining technology, and its results are usually expressed in the form of if-then rules. The C4.5 algorithm is one of the decision tree algorithms, which has the advantages of easy to understand and high accuracy, and the concept of information gain rate is added compared with its predecessor ID3 algorithm. After theoretical analysis, C4.5 algorithm is chosen to analyze the performance appraisal results, and the decision tree for performance appraisal is generated by collecting data, data preprocessing, calculating information gain rate, determining splitting attributes, and postpruning. The system is developed in B/S architecture, and an R&D project management system and platform that can realize performance assessment analysis are built by means of visualization tools, decision tree algorithm, and dynamic web pages. The system includes information storage, task management, report generation, role authority control, information visualization, and other management information system functional modules. They can realize the project management functions such as project establishment and management, task flow, employee information filling and management, performance assessment system establishment, report generation of various dimensions, management cockpit construction. With decision tree algorithm as the core technology, the system obtains scientific and reliable project management information with high accuracy and realizes data visualization, which can assist enterprises to establish a good management system in the era of big data.

scholarly journals C4.5 DECISION TREE IMPLEMENTATION IN SISTEM INFORMASI ZAKAT (SIZAKAT) TO AUTOMATICALLY DETERMINING THE AMOUNT OF ZAKAT RECEIVED BY MUSTAHIK

2014 ◽  
Vol 10 (1) ◽  
pp. 28 ◽  
Author(s):  
David Bayu Ananda ◽  
Ari Wibisono
Keyword(s):  
Information Systems ◽  
Decision Tree ◽  
Decision Tree Algorithm ◽  
Accuracy Rate ◽  
Tree Algorithm ◽  
C4.5 Decision Tree

Abstract In general, Zakat Information Systems is established to manage the zakat services, so that the data can be well documented. This study proposes the existence of a feature that will determine the amount of zakat received by Mustahik automatically using C4.5 Decision Tree algorithm. This feature is expected to make the process of determining the amount of zakat be done easy and optimal. The data used in this study are the data taken from Masjid An-Nur, Pancoran, South Jakarta. The experiment results show that the proposed feature produces an accuracy rate over 85%.

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