Peningkatan Deep Neural Network pada Kasus Prediksi Diabetes Menggunakan PSO

Authors

  • Rusmal Firmansyah Universitas Dian Nuswantoro
  • Guruh Fajar Shidik Universitas Dian Nuswantoro

DOI:

https://doi.org/10.33633/tc.v22i4.9209

Keywords:

Diabetes, DNN, PSO, SVM

Abstract

Diabetes adalah ancaman utama bagi kesehatan penduduk dunia yang saat ini merupakan penyebab utama kematian pada penduduk dunia yang berusia kurang dari 60 tahun. Dengan menggunakan Machine Learning diharapkan mampu memprediksi diabetes. Dengan menggunakan dataset Pima Indians Diabetes (PIMA Dataset). Pada penelitian ini dilakukan pengujian dengan menggunakan 2 Algoritma dan 1 Algoritma yang dioptimasi. Pengujian Pertama Menggunakan Support Vector Machine (SVM), Pengujian Kedua menggunakan Deep Neural Network (DNN)  dan Pengujian Ketiga menggunakan DNN yang dikombinakan dengan Particle Swarm Optimize (PSO). Pemilihan data yang digunakan sebagai training dilakukan dengan menggunakan Non-Random Sampling. Dalam Penelitian ini pengujian pertama dengan menggunakan SVM dengan melakukan pengujian tanpa menggunakan kernel dan menggunakan kernel Linear, Sigmoid, Polynomial dan Radial Basis Function (RBF). Untuk Pengujian Kedua dilakukan dengan menggunakan DNN tanpa menggunakan Optimaliasi atau DNN original dengan dilakukan penggujian dengan jumlah hidden layer 2 dan jumlah neuron 8 sampai 10 pada setiap hidden layer. Pengujian Ketiga dilakukan dengan menggunakan DNN yang dioptimalisasi dengan menggunakan PSO. Pada Pengujian Ketiga dilakukan penggujian dengan jumlah hidden layer 2 dan jumlah neuron 8 sampai 10 pada setiap hidden layer. Hasil yang diperoleh menunjukkan bahwa DNN yang dioptimasi dengan PSO mampu memberikan akurasi tertinggi dengan jumlah hidden layer 1 sebanyak 9 node dan jumlah hidden layer 2 sebanyak 8 node dengan jumlah iterasi pada PSO sebanyak 166 iterasi.

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Published

2023-11-21

Issue

Vol. 22 No. 4 (2023): November 2023

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Articles

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