PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER

Muhammad Rosyid Abdurrahman; Dwi Ispriyanti; Alan Prahutama

doi:10.14710/j.gauss.3.4.731-739

DOI: https://doi.org/10.14710/j.gauss.3.4.731-739

PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER

*Muhammad Rosyid Abdurrahman -

Dwi Ispriyanti -

Alan Prahutama -

How to cite (IEEE): M. R. Abdurrahman, D. Ispriyanti, and A. Prahutama, "PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER," Jurnal Gaussian, vol. 3, no. 4, pp. 731-739, Oct. 2014. https://doi.org/10.14710/j.gauss.3.4.731-739

How to cite (APA): Abdurrahman, M. R., Ispriyanti, D., & Prahutama, A. (2014). PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER. Jurnal Gaussian, 3(4), 731-739. https://doi.org/10.14710/j.gauss.3.4.731-739

How to cite (BCREC): Abdurrahman, M. R., Ispriyanti, D., Prahutama, A. (2014). PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER. Jurnal Gaussian, 3 (4), 731-739 (doi:10.14710/j.gauss.3.4.731-739)

How to cite (Chicago): Abdurrahman, Muhammad R., Dwi Ispriyanti, and Alan Prahutama. "PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER." Jurnal Gaussian 3, no. 4 (2014): 731-739. Accessed : March 15, 2025. https://doi.org/10.14710/j.gauss.3.4.731-739

How to cite (Vancouver): Abdurrahman MR, Ispriyanti D, Prahutama A. PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER. Jurnal Gaussian [Online]. 2014 Oct;3(4):731-739. https://doi.org/10.14710/j.gauss.3.4.731-739.

How to cite (Harvard): Abdurrahman, M. R., Ispriyanti, D., and Prahutama, A., 2014. PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER. Jurnal Gaussian, [Online] Volume 3(4), pp. 731-739. https://doi.org/10.14710/j.gauss.3.4.731-739 [Accessed : 15 Mar. 2025].

How to cite (MLA8): Abdurrahman, Muhammad, Dwi Ispriyanti, and Alan Prahutama. "PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER." Jurnal Gaussian, vol. 3, no. 4, 30 Oct. 2014, pp. 731-739 , https://doi.org/10.14710/j.gauss.3.4.731-739. Retrieved : 15 Mar. 2025.

BibTex Citation Data :

@article{J.Gauss8084,
    author = {Muhammad Abdurrahman and Dwi Ispriyanti and Alan Prahutama},
    title = {PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER},
    journal = {Jurnal  Gaussian},
  volume = {3},
    number = {4},
    year = {2014},
    keywords = {},
    abstract = { In this modern era of fast food commonly found that sometimes have chemical substances and the increasing number of motor vehicles that cause the uncontrolled circulation of air pollution that can affect the health of the human liver. To assist in analyzing the presence of liver disorders in humans can be used QUEST (Quick, Unbiased, and Efficient Statistical Tree) algorithm to classify the characteristics of the patient's liver by liver function tests performed in clinical laboratories. QUEST construct rules to predict the class of an object from the values of predictor variables. The tree is constructed by partitioning the data by recuresively, where class and the values of the predictor variables of each observation in the data sample is known. Each partition is represented by a node in the tree. QUEST is one of the binary classification tree method. The results of the classification tree is formed, an important variable in classifying a person affected by liver disease or not, that is the variable Direct Bilirubin, Alkaline Phosphatase, Serum Glutamic Oxaloacetic Transaminase (SGOT), and age of the patient. Accuracy of the QUEST algorithm classifying liver patient data by 73,4 %.      Keywords : binary classification trees, QUEST algorithm, liver patient data. },
   issn = {2339-2541},   pages = {731--739}  doi = {10.14710/j.gauss.3.4.731-739},
    url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/8084}
}

Refworks Citation Data :

@article{{J.Gauss}{8084}, author = {Abdurrahman, M., Ispriyanti, D., Prahutama, A.}, title = {PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER}, journal = {Jurnal Gaussian}, volume = {3}, number = {4}, year = {2014}, doi = {10.14710/j.gauss.3.4.731-739}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/8084} }

Citation Format:

Abstract

In this modern era of fast food commonly found that sometimes have chemical substances and the increasing number of motor vehicles that cause the uncontrolled circulation of air pollution that can affect the health of the human liver. To assist in analyzing the presence of liver disorders in humans can be used QUEST (Quick, Unbiased, and Efficient Statistical Tree) algorithm to classify the characteristics of the patient's liver by liver function tests performed in clinical laboratories. QUEST construct rules to predict the class of an object from the values of predictor variables. The tree is constructed by partitioning the data by recuresively, where class and the values of the predictor variables of each observation in the data sample is known. Each partition is represented by a node in the tree. QUEST is one of the binary classification tree method. The results of the classification tree is formed, an important variable in classifying a person affected by liver disease or not, that is the variable Direct Bilirubin, Alkaline Phosphatase, Serum Glutamic Oxaloacetic Transaminase (SGOT), and age of the patient. Accuracy of the QUEST algorithm classifying liver patient data by 73,4 %.

Keywords: binary classification trees, QUEST algorithm, liver patient data.

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In Vol 3, No 4 (2014): Jurnal Gaussian