Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)

Prediction of Acidity Level of Avomango (Gadung Klonal 21) Using Local Polynomial Estimator

Authors
M Ulya, N Chamidah
Corresponding Author
N Chamidah
Available Online 11 October 2020.
DOI
https://doi.org/10.2991/assehr.k.201010.015How to use a DOI?
Keywords
Titratable acidity, acidity level, avomango, local polynomial estimator
Abstract

The acidity level is one of the parameters that determine fruit maturity. Mature avomango has a low acidity level, indicated by its titratable acidity value. Non-destructive analysis using a near infrared (NIR) spectroscopy tool produces wavelength data that is used as a predictor variable with a titratable acidity value as a response variable. This study aims to predict the acidity level (titratable acidity) of avomangoes using nonparametric regression based on local linear estimators and compare them with the prediction using the parametric regression approach. This study uses 100 mango data as samples, which are divided into 80 into sample data for the training process and 20 out sample data for the prediction process. The results showed that the second degree local polynomial estimator gives the best results. From the 5 iterations, the 4th iteration data gives the mean square error value of prediction using local polynomial estimator and global polynomial regression method is 0.0651and 0.0733, respectively. The mean absolute percentage error of prediction using local polynomial estimators and global polynomial regression is 39.6411 and 43.3676, respectively. It means that the nonparametric regression based on local polynomial estimator provides better predictive results compared to the parametric regression approach.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
11 October 2020
ISBN
978-94-6239-168-0
ISSN
2352-5398
DOI
https://doi.org/10.2991/assehr.k.201010.015How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - M Ulya
AU  - N Chamidah
PY  - 2020
DA  - 2020/10/11
TI  - Prediction of Acidity Level of Avomango (Gadung Klonal 21) Using Local Polynomial Estimator
BT  - Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
PB  - Atlantis Press
SP  - 92
EP  - 100
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201010.015
DO  - https://doi.org/10.2991/assehr.k.201010.015
ID  - Ulya2020
ER  -