Jurnal Teknik Informatika UNIKA Santo Thomas
Vol 7 No. 1 : Tahun 2022

Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network

Mochammad Abdul Azis (Universitas Bina Sarana Informatika)
Ahmad Fauzi (Universitas Bina Sarana Informatika)
Ginabila Ginabila (Universitas Bina Sarana Informatika)
Imam Nawawi (Universitas Bina Sarana Informatika)

Article Info

Publish Date
01 Jun 2022

Abstract

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.

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Journal Info
Jurnal Teknik Informatika UNIKA Santo Thomas
Website

Abbrev

JTIUST

Publisher

Universitas Katolik Santo Thomas Sumatera Utara

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Terbit Setiap Bulan Juni dan Desember Setiap Tahunnya. Jurnal ini Media publikasi untuk bidang Ilmu Komputer seperti Teknologi dan Jaringan, Sistem Cerdas, Web, Mobile, Sistem Pendukung Keputusan, Cloud Computing, Citra, Krpitografy dan yang ...