Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil

Supriyatna, Adi; Mustika, Wida Prima

doi:10.30645/j-sakti.v2i2.78

Cited by 21 publications

(24 citation statements)

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“…Metode ini digunakan untuk menyelesaikan masalah diagnosa dan prediksi (Supriyatna & Mustika, 2018). Definisi lain mengatakan Naive Bayes merupakan pengklasifikasian dengan metode probabilitas dan statistik yang dikemukakan oleh ilmuan Inggris Thomas Bayes, yaitu memprediksi peluang di masa depan berdasarkan pengalaman di masa sebelumnya.…”

Section: Metode Naive Bayesunclassified

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Komparasi Algoritma Neural Network Dan Naïve Bayes Untuk Memprediksi Penyakit Jantung

Nawawi

Purnama²,

Hikmah

2019

pilar

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Heart disease is one of the types of deadly diseases whose treatment must be dealt with as soon as possible because it can occur suddenly to the sufferer. Factors of heart disease that are recognized based on the condition of the body of a sufferer need to be known from an early age so that the risk of possible instant attacks can be minimized or can be overcome in various ways such as a healthy lifestyle and regular exercise that can regulate heart health in the body. By looking at the condition of a person's body based on sex, blood pressure, age, whether or not a smoker and some indicators that cause a person's affected by heart disease are described in a study using the Neural Network and Naïve Bayes algorithm with the aim of comparing the level of accuracy to attributes influential to predict heart disease, so the results of this study can be used as a reference to predict whether a person has heart disease or not based on health data used as research benchmarks.

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Section: Metode Naive Bayesunclassified

“…( 1 = 1| = 1)) = 1 √2 exp( 1 − )2 .. ..(8) Dimana : P : Peluang Xi : Atribut ke i xi : Nilai atribut ke i Y : Kelas yang dicari Yi : sub kelas Y yang dicari µ : Mean, menyatakan varian dari seluruh atribut σ : deviasi standar, menyatakan varian dari seluruh atribut (Supriyatna & Mustika, 2018).…”

Section: Metode Naive Bayesunclassified

Komparasi Algoritma Neural Network Dan Naïve Bayes Untuk Memprediksi Penyakit Jantung

Nawawi

Purnama²,

Hikmah

2019

pilar

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“…Imunoterapi intralesi adalah pengobatan efektif untuk kutil. Metode ini memiliki respons terapeutik yang lebih baik, membutuhkan lebih sedikit sesi, dan mampu mengobati kutil yang sudah lama (Supriyatna, 2018). Ada tren baru terhadap penggunaan imunoterapi dalam pengobatan kutil, karena sistem kekebalan tubuh tampaknya memainkan peran penting dalam pengendalian infeksi kutil (Shah, 2016).…”

Section: Pendahuluanunclassified

Analisis Algoritma Klasifikasi C 4.5 Untuk Memprediksi Keberhasilan Immunotherapy Pada Penyakit Kutil

Hermawan¹,

Sukma²,

Halfis³

2019

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Maintaining skin health is one thing that is also needed. Not only health from inside, health from the outside must also be considered. There are so many skin problems that arise in the human body. Wart disease is characterized by small bumps on the surface of the skin which are generally caused by the Human Papiloma Virus (HPV) virus. One technique for treating wart disease is immunotherapy, this method is a treatment by increasing the immune system to deal with wart disease. Clinical predictions are growing very rapidly by adopting computer science and information technology in managing health and drug data, this clinical prediction can be produced from processing using data mining methods. Data mining is a popular method used to explore patterns or knowledge from large data stacks. C 4.5 algorithm which is one of the decision tree induction algorithms is also a method of data mining algorithms used to classify. This study aims to predict the success rate of immunotherapy treatment methods on wart disease with algorithm C 4.5 using RapidMiner. From the study it was known that the accuracy rate for processing immunotherapy data on wart disease to predict its success using the C 4.5 algorithm of 74.07%.

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“…Predictions about health develop very rapidly by using computer science and information technology in processing health data. (Supriyatna & Mustika, 2018)…”

Section: Introductionmentioning

confidence: 99%

Analysis of Neural Network Classification Algorithm to Know the Success Level of Immunotherapy

Fazriansyah

Azis²,

Yudhistira

2020

techno

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Cancer is a disease that is feared by humans at this stage, the genetic term of most diseases that have the characteristics of abnormal cell growth and beyond the normal cell limits so that they can attack cells that cover and are able to spread to other organs. For cancer recovery therapy is immunization therapy. Of course in this alternative treatment still needs to be done research to determine the level of success with existing conditions and parameters. Increasingly sophisticated, developing technology that helps human work. The neural network algorithm is used to analyze large datasets, the purpose of this study is to find the accuracy and immunotherapy methods of the dataset using a neural network learning machine with 200 data training cycles, 0.9 momentum and 0.01 learning levels that produce quite high accuracy 80 % and AUC value of 0.738

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Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil

Cited by 21 publications

References 0 publications

Komparasi Algoritma Neural Network Dan Naïve Bayes Untuk Memprediksi Penyakit Jantung

Komparasi Algoritma Neural Network Dan Naïve Bayes Untuk Memprediksi Penyakit Jantung

Analisis Algoritma Klasifikasi C 4.5 Untuk Memprediksi Keberhasilan Immunotherapy Pada Penyakit Kutil

Analysis of Neural Network Classification Algorithm to Know the Success Level of Immunotherapy

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