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Meiliyani Siringoringo
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Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
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Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Core Subject : Economy, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 12 Documents
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Search results for , issue "Vol 8 No 2 (2017)" : 12 Documents clear
Aplikasi Metode Naive Bayes dalam Prediksi Risiko Penyakit Jantung M. Sabransyah; Yuki Novia Nasution; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.691 KB)

Abstract

Classification is an activity for assessing object data which include it the data into particular class among any number of classes available. Naive Bayes is classification with probability method. This research examines the use of naive Bayes method for a heart disease risk prediction application. In this research, it will be classified a person who have the risk of heart disease by using the data of patient in RSUD AWS during November and December 2016 the sample case is 47 years old male object, has cholesterol level of 198 mg/dL, has blood pressure of 131 mmHg, parents having heart disease medical record, suffering diabetes Mellitus, has obesity, has high dyslipidemia. It is concluded that the object falls into "potential category" of having heart disease. The classification result that has been done, the exact accuracy was obtained with 25 tested data and got accuracy level in an amount of 80% and 50 tested data sample and got accuracy level in an amount of 78%.
Klasifikasi Lama Masa Studi Mahasiswa Menggunakan Perbandingan Metode Algoritma C.45 dan Algoritma Classification and Regression Tree Hadi Dwi Darmawan; Desi Yuniarti; Yuki Novia Nasution
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (802.413 KB)

Abstract

Classification is the grouping samples based on the characteristics of the similarities and differences using target variable category. In this study, the decision tree is formed using C4.5 algorithm and Classification and regression tree (CART) algorithm to classify a student’s study period class of 2016 FMIPA UNMUL. C4.5 algorithm is a non binary classification tree where the branches of trees can be more than two on C4.5 algorithm, decision tree is established based on Entropy value. The purpose of CART algorithm is to get an accurate data as group identifier of a classification. CART can be applied in three main steps, namely the establishment of a classification tree, trimming of the classification tree, and determination of optimal classification tree. The main goal of this research is to determine factors which may effect on all predicate graduation who was graduated on 2016 using C4.5 algorithm and CART algorithm and also to know comparison accuracy of classification result by C4.5 algorithm and CART algorithm. The result showed that factors which affected the duration of all graduation using C4.5 algorithm are major (X4), region school (X5) and region origin (X3) and factors affected to the duration of all graduation using CART algorithm are major (X4) and Cumulative Achievement Index (X1). Precision classification in CART algorithm is better than C4.5 algorithm. C4.5 algorithm was able to predict with 40% accuracy while the CART algorithm has a predictive accuracy of 60%.

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