K-Value Effect for Detecting Stairs Descent using Combination GLCM and KNN
| Main Authors: | Satria Bahari Johan, Ahmad Wali, Utaminingrum, Fitri, Budi, Agung Setia |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
Faculty of Computer Science (FILKOM) Brawijaya University
, 2020
|
| Online Access: |
http://jitecs.ub.ac.id/index.php/jitecs/article/view/144 http://jitecs.ub.ac.id/index.php/jitecs/article/view/144/104 http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/45 http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/46 |
| ctrlnum |
article-144 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><title lang="en-US">K-Value Effect for Detecting Stairs Descent using Combination GLCM and KNN</title><creator>Satria Bahari Johan, Ahmad Wali</creator><creator>Utaminingrum, Fitri</creator><creator>Budi, Agung Setia</creator><description lang="en-US">This study aims to analyze the k-value on K nearest neighbor classification. k-value is the distance used to find the closest data to label the class from the testing data. Each k-value can produce a different class label against the same testing data. The variants of k-value that we use are k=3, k=5 and k=7 to find the best k-value. There are 2 classes that are used in this research. Both classes are stairs descent and floor classes. The gray level co-occurrence matrix method is used to extract features. The data we use comes from videos obtained from the camera on the smart wheelchair taken by the frame. Refer to the results of our tests, the best k-value is obtained when using k=7 and angle 0° with accuracy is 92.5%. The stairs descent detection system will be implemented in a smart wheelchair</description><publisher lang="en-US">Faculty of Computer Science (FILKOM) Brawijaya University</publisher><contributor lang="en-US"/><date>2020-02-28</date><type>Journal:Article</type><type>Other:info:eu-repo/semantics/publishedVersion</type><type>Journal:Article</type><type>File:application/pdf</type><identifier>http://jitecs.ub.ac.id/index.php/jitecs/article/view/144</identifier><identifier>10.25126/jitecs.202051144</identifier><source lang="en-US">Journal of Information Technology and Computer Science; Vol 5, No 1: April 2020; 23-31</source><source>2540-9824</source><source>2540-9433</source><source>10.25126/jitecs.202051</source><language>eng</language><relation>http://jitecs.ub.ac.id/index.php/jitecs/article/view/144/104</relation><relation>http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/45</relation><relation>http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/46</relation><rights lang="en-US">Copyright (c) 2020 Journal of Information Technology and Computer Science</rights><recordID>article-144</recordID></dc>
|
| language |
eng |
| format |
Journal:Article Journal Other:info:eu-repo/semantics/publishedVersion Other File:application/pdf File Journal:Journal |
| author |
Satria Bahari Johan, Ahmad Wali Utaminingrum, Fitri Budi, Agung Setia |
| title |
K-Value Effect for Detecting Stairs Descent using Combination GLCM and KNN |
| publisher |
Faculty of Computer Science (FILKOM) Brawijaya University |
| publishDate |
2020 |
| url |
http://jitecs.ub.ac.id/index.php/jitecs/article/view/144 http://jitecs.ub.ac.id/index.php/jitecs/article/view/144/104 http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/45 http://jitecs.ub.ac.id/index.php/jitecs/article/downloadSuppFile/144/46 |
| contents |
This study aims to analyze the k-value on K nearest neighbor classification. k-value is the distance used to find the closest data to label the class from the testing data. Each k-value can produce a different class label against the same testing data. The variants of k-value that we use are k=3, k=5 and k=7 to find the best k-value. There are 2 classes that are used in this research. Both classes are stairs descent and floor classes. The gray level co-occurrence matrix method is used to extract features. The data we use comes from videos obtained from the camera on the smart wheelchair taken by the frame. Refer to the results of our tests, the best k-value is obtained when using k=7 and angle 0° with accuracy is 92.5%. The stairs descent detection system will be implemented in a smart wheelchair |
| id |
IOS5163.article-144 |
| institution |
Universitas Brawijaya |
| affiliation |
mill.onesearch.id |
| institution_id |
30 |
| institution_type |
library:university library |
| library |
Fakultas Ilmu Komputer |
| library_id |
1383 |
| collection |
Journal of Information Technology and Computer Science (JITeCS) |
| repository_id |
5163 |
| subject_area |
Computer Science Information System Computer Engiineering Information Technology |
| city |
KOTA MALANG |
| province |
JAWA TIMUR |
| repoId |
IOS5163 |
| first_indexed |
2020-03-02T09:04:05Z |
| last_indexed |
2020-08-07T11:14:17Z |
| recordtype |
dc |
| _version_ |
1686314747953152000 |
| score |
17.610468 |