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Comparison of two classification models for sex estimation based on bone length of hispanic population

One of the essential factors of conducting a forensic investigation is to determine sex. Although multiple studies have been conducted using hand bone, the studies using the Hispanic population are minimal. The purpose of this study is to develop the Discriminant Function Analysis (DFA) and Artifici...

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Main Authors: Mohd. Faaizie, Darmawan, Fajar Agung, Nugroho, Ernawan, Ferda, Ahmad Firdaus, Zainal Abidin, Mohd Zamri, Osman
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2021
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/33130/1/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation_FULL.pdf
http://umpir.ump.edu.my/id/eprint/33130/2/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation.pdf
http://umpir.ump.edu.my/id/eprint/33130/
https://doi.org/10.1109/ICICoS53627.2021.9651777
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spelling my.ump.umpir.331302022-09-02T07:34:25Z http://umpir.ump.edu.my/id/eprint/33130/ Comparison of two classification models for sex estimation based on bone length of hispanic population Mohd. Faaizie, Darmawan Fajar Agung, Nugroho Ernawan, Ferda Ahmad Firdaus, Zainal Abidin Mohd Zamri, Osman QA76 Computer software One of the essential factors of conducting a forensic investigation is to determine sex. Although multiple studies have been conducted using hand bone, the studies using the Hispanic population are minimal. The purpose of this study is to develop the Discriminant Function Analysis (DFA) and Artificial Neural Network (ANN) model for sex estimation based on the Hispanic population using left-hand bone. The samples used are subjects ranged between age groups of infants and 18 years old which comprised of 91 females and 92 males. For the input, the length of nineteen bones from the subjects’ left hand is measured in centimeters and then normalized to become input for both models. The DFA model is chosen as a benchmark in this study to be compared with the ANN model based on accuracy percentage. The chosen DFA model is due to the widely used in estimating sex based on quantitative input. For the results, the DFA model produces a 72.7% accuracy percentage while the ANN produces 83.8%. Thus, the ANN model is selected to be the most ideal model in estimating sex compared to the DFA model. IEEE 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33130/1/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation_FULL.pdf pdf en http://umpir.ump.edu.my/id/eprint/33130/2/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation.pdf Mohd. Faaizie, Darmawan and Fajar Agung, Nugroho and Ernawan, Ferda and Ahmad Firdaus, Zainal Abidin and Mohd Zamri, Osman (2021) Comparison of two classification models for sex estimation based on bone length of hispanic population. In: 2021 5th International Conference on Informatics and Computational Sciences (ICICoS), 24-25 Nov. 2021 , Virtual Conference. pp. 1-5.. ISSN 2767-7087 ISBN 978-1-6654-3807-0 https://doi.org/10.1109/ICICoS53627.2021.9651777
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA76 Computer software
spellingShingle QA76 Computer software
Mohd. Faaizie, Darmawan
Fajar Agung, Nugroho
Ernawan, Ferda
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
Comparison of two classification models for sex estimation based on bone length of hispanic population
description One of the essential factors of conducting a forensic investigation is to determine sex. Although multiple studies have been conducted using hand bone, the studies using the Hispanic population are minimal. The purpose of this study is to develop the Discriminant Function Analysis (DFA) and Artificial Neural Network (ANN) model for sex estimation based on the Hispanic population using left-hand bone. The samples used are subjects ranged between age groups of infants and 18 years old which comprised of 91 females and 92 males. For the input, the length of nineteen bones from the subjects’ left hand is measured in centimeters and then normalized to become input for both models. The DFA model is chosen as a benchmark in this study to be compared with the ANN model based on accuracy percentage. The chosen DFA model is due to the widely used in estimating sex based on quantitative input. For the results, the DFA model produces a 72.7% accuracy percentage while the ANN produces 83.8%. Thus, the ANN model is selected to be the most ideal model in estimating sex compared to the DFA model.
format Conference or Workshop Item
author Mohd. Faaizie, Darmawan
Fajar Agung, Nugroho
Ernawan, Ferda
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
author_facet Mohd. Faaizie, Darmawan
Fajar Agung, Nugroho
Ernawan, Ferda
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
author_sort Mohd. Faaizie, Darmawan
title Comparison of two classification models for sex estimation based on bone length of hispanic population
title_short Comparison of two classification models for sex estimation based on bone length of hispanic population
title_full Comparison of two classification models for sex estimation based on bone length of hispanic population
title_fullStr Comparison of two classification models for sex estimation based on bone length of hispanic population
title_full_unstemmed Comparison of two classification models for sex estimation based on bone length of hispanic population
title_sort comparison of two classification models for sex estimation based on bone length of hispanic population
publisher IEEE
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/33130/1/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation_FULL.pdf
http://umpir.ump.edu.my/id/eprint/33130/2/Comparison%20of%20two%20classification%20models%20for%20sex%20estimation.pdf
http://umpir.ump.edu.my/id/eprint/33130/
https://doi.org/10.1109/ICICoS53627.2021.9651777
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score 13.211869

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