Skripsi

PENERAPAN MACHINE LEARNING DALAM SISTEM KLASIFIKASI PENYAKIT MANUSIA DENGAN MODEL DECISION TREE DAN NEURAL NETWORK

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Penilaian

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By using machine learning, a system can classify human diseases based on the symptoms experienced by a person. The purpose of this study is to obtain the best machine learning model for classifying diseases using decision trees and neural networks and use these models to be converted into TensorFlow lite. The dataset used in this study is the Kaggle Disease Prediction Using Machine Learning dataset. After getting the dataset, data preprocessing is carried out using the decision tree model. Neural network models are used to predict human disease. The results of the final model accuracy in the training and validation process are 100%, while the accuracy of model testing is 97.6%. The model will be converted to TensorFlow lite using the TFLiteConverter method so that it can be implemented in the human disease classification system.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107003848	T60652	T606522021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T606522021

Publisher

Indralaya : Prodi Ilmu Fisika, Fakultas Matematika dan Ilmu Pengetahuan Alam., 2021

Collation

ix, 36 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

530.807

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Ilmu Fisika
Satuan Fisika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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