Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Ester Nadya Fiorentina Lumban Gaol
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Deteksi Tangga Turun, Tangga Naik, dan Lantai menggunakan Gray Level Co-Occurrence Matrix dan K-Nearest Neighbors berbasis Raspberry Pi Ester Nadya Fiorentina Lumban Gaol; Fitri Utaminingrum; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A smart wheelchair is a mobility aid that is easy to operate and aids in its users' independence. In its development, the smart wheelchair design not only pays attention to the aspect of convenience but also in terms of safety. Any obstacles that include accessibility obstacles in the environment must be detectable by a smart wheelchair to increase safety. One of these accessibility obstacles is the sudden change in the level of surfaces such as stairs. This research aims to create a system capable of detecting stairs descent, stairs ascent, and floors using the Gray Level Co-occurrence Matrix (GLCM) method to obtain the extraction of characteristic features from stairs descent, stairs ascent, and floors. Then applies the K-Nearest Neighbors (K-NN) classification method to predict what states are detected. Using the GLCM methods with 4 feature (contrast, dissimilarity energy, and homogeneity), distance (d) = 4, q=90° and K-NN with k=4, the system obtained an average accuracy of 93.33% and an average computation time of 1551ms.
Co-Authors Agung Setia Budi Utaminingrum, Fitri