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Jurnal
SINTA 2
Classification of Human Weight Based on Image
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 13 No. 2 (2019) · pp. 105–116
ISSN 2460-7258, 1978-1520
Published 2019-04-30
Publisher IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language eng
Abstract
Classification of human weight can be determined by body mass index. The body mass index can be calculated by dividing the height by the square of the body weight. According to researchers, this is less practical, so it needs to make a tool that can be used to determine ideal body weight more practically. One way is to use an Android smartphone camera. The camera is used to capture the image of the human body. Then the image is processed by using digital image processing and by using certain algorithms, so it may conclude the person's ideal weight category. The data used in this study are human photos, body weight and height. There are four stages to determine the weight and height based on the image. First, performing an analysis of the calculation of the derived formulas. Second, analyzing the edge detection algorithm. Third, conducting unit convertion, and fourth, proposing several algorithms to calculate the height and weight used to determine the ideal body weight. The results of the evaluation show that Algorithm C (measuring the width of an object starting with the height of the image adjusting half of the height of the object in the image) is the best algorithm with deviation value of 1.85% of the height and 8.87% of the weight, while the system accuracy rate in determining the ideal body weight has reached 78.7%.
Collaboration network of the authors
11 authors ·
11 co-authorship links
· 2 across different organisations
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Sunan Kalijaga State Islamic University Yogyakarta Universitas Gadjah Mada Affiliation unknown
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Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai,
first harvested 26 Okt 2026,
last seen 26 Okt 2026.
Original metadata (oai_dc)
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<dc:title xml:lang="en-US">Classification of Human Weight Based on Image</dc:title>
<dc:creator>'Uyun, Shofwatul</dc:creator>
<dc:creator>Efendi, Toni</dc:creator>
<dc:subject xml:lang="en-US">informatics</dc:subject>
<dc:subject xml:lang="en-US">human weight; Image; edge detection; body mass index</dc:subject>
<dc:description xml:lang="en-US">Classification of human weight can be determined by body mass index. The body mass index can be calculated by dividing the height by the square of the body weight. According to researchers, this is less practical, so it needs to make a tool that can be used to determine ideal body weight more practically. One way is to use an Android smartphone camera. The camera is used to capture the image of the human body. Then the image is processed by using digital image processing and by using certain algorithms, so it may conclude the person's ideal weight category. The data used in this study are human photos, body weight and height. There are four stages to determine the weight and height based on the image. First, performing an analysis of the calculation of the derived formulas. Second, analyzing the edge detection algorithm. Third, conducting unit convertion, and fourth, proposing several algorithms to calculate the height and weight used to determine the ideal body weight. The results of the evaluation show that Algorithm C (measuring the width of an object starting with the height of the image adjusting half of the height of the object in the image) is the best algorithm with deviation value of 1.85% of the height and 8.87% of the weight, while the system accuracy rate in determining the ideal body weight has reached 78.7%. </dc:description>
<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
<dc:contributor xml:lang="en-US"></dc:contributor>
<dc:date>2019-04-30</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US"></dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/35794</dc:identifier>
<dc:identifier>10.22146/ijccs.35794</dc:identifier>
<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 105-116</dc:source>
<dc:source>2460-7258</dc:source>
<dc:source>1978-1520</dc:source>
<dc:language>eng</dc:language>
<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/35794/24366</dc:relation>
<dc:rights xml:lang="en-US">Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>
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Cite this article
APA 7
'Uyun, S., & Efendi, T. (2019). Classification of Human Weight Based on Image. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 13(2), 105–116. https://doi.org/10.22146/ijccs.35794
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IEEE
S. 'Uyun and T. Efendi, “Classification of Human Weight Based on Image,” IJCCS (Indonesian Journal of Computing and Cybernetics Systems), vol. 13, no. 2, pp. 105–116, 2019, doi: 10.22146/ijccs.35794.
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