Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

被引:1
|
作者
Wahyuni, Sri [1 ]
机构
[1] Univ Pembangunan Panca Budi, Comp Engn, Medan, Indonesia
关键词
D O I
10.1088/1742-6596/970/1/012030
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] Color Recognition Based on C4.5 Decision Tree Algorithm
    Chen, Chao
    Xu, He-Gen
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND INFORMATION SYSTEMS, 2016, 52 : 158 - 163
  • [22] AUC4.5: AUC-Based C4.5 Decision Tree Algorithm for Imbalanced Data Classification
    Lee, Jong-Seok
    IEEE ACCESS, 2019, 7 : 106034 - 106042
  • [23] C4.5 decision forests
    Ho, TK
    FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2, 1998, : 545 - 549
  • [24] CHARACTERISATION OF BUILDING ALIGNMENTS WITH NEW MEASURES USING C4.5 DECISION TREE ALGORITHM
    Cetinkaya, Sinan
    Basaraner, Melih
    GEODETSKI VESTNIK, 2014, 58 (03) : 552 - 567
  • [25] Path Determination With Classification From Data Mining Using C4.5 Algorithm
    Yonesa, Suci
    Nasution, Surya Michrandi
    Nugrahaeni, Ratna Astuti
    2018 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY SYSTEMS AND INNOVATION (ICITSI), 2018, : 22 - 25
  • [26] Prediction of the Student Graduation's Level using C4.5 Decision Tree Algorithm
    Purnamasari, Evi
    Rini, Dian Palupi
    Sukemi
    2019 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (ICECOS 2019), 2019, : 192 - 195
  • [27] Performance Improvement of C4.5 Algorithm using Difference Values Nodes in Decision Tree
    Nugroho, Handoyo Widi
    Adji, Teguh Bharata
    Setiawan, Noor Akhmad
    2018 6TH INTERNATIONAL CONFERENCE ON CYBER AND IT SERVICE MANAGEMENT (CITSM), 2018, : 334 - 339
  • [28] An Online Software for Decision Tree Classification and Visualization using C4.5 Algorithm (ODTC)
    Das, Suvajit
    Dahiya, Shashi
    Bharadwaj, Anshu
    2014 INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2014, : 962 - 965
  • [29] Text document categorisation using random forest and C4.5 decision tree classifier
    Pawar, Sumathi
    Rao, Manjula Gururaj
    Pandith, Karuna
    International Journal of Computational Systems Engineering, 2023, 7 (2-4) : 211 - 220
  • [30] Improved C4.5 algorithm in the application of data mining match assessment and decision-making
    School of Physical Education, Langfang Teachers’ College, Langfang
    Hebei, China
    不详
    Hebei, China
    Intl. J. Earth Sci. Eng., 1 (210-216):