TY - JOUR
T1 - Predicting the sweetness level of avomango (Gadung Klonal 21) using multi-predictor local polynomial regression
AU - Ulya, M.
AU - Chamidah, N.
AU - Saifudin, T.
N1 - Funding Information:
The first author would like to thank the Directorate of Higher Education (DIKTI), Ministry of Education and Culture, Indonesia, for providing financial support through the BPPDN scholarship 2019.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/5/4
Y1 - 2021/5/4
N2 - One of the mango's maturity aspects is the sweetness of the fruits. Mature Avomango has a high degree of sweetness, characterized by a high total soluble solids (TSS) content. Currently, many non-destructive tests are using Near Infra-Red (NIR) spectroscopy to find out the TSS content. NIR spectroscopy generates spectra data, which can be used as predictors to predict Avomangos sweetness level. This study aims to predict the level of Avomangos sweetness by using a multi-predictor local polynomial regression approach and compare it with multiple polynomial regression. In this study, we use 120 samples of Avomango divided into two parts, 100 as training data and 20 as testing data. The multi-predictor local polynomial regression has better performance with the value mean absolute percentage error (MAPE) is 8.554% that categorized as a highly accurate prediction for predicting Avomangos sweetness level.
AB - One of the mango's maturity aspects is the sweetness of the fruits. Mature Avomango has a high degree of sweetness, characterized by a high total soluble solids (TSS) content. Currently, many non-destructive tests are using Near Infra-Red (NIR) spectroscopy to find out the TSS content. NIR spectroscopy generates spectra data, which can be used as predictors to predict Avomangos sweetness level. This study aims to predict the level of Avomangos sweetness by using a multi-predictor local polynomial regression approach and compare it with multiple polynomial regression. In this study, we use 120 samples of Avomango divided into two parts, 100 as training data and 20 as testing data. The multi-predictor local polynomial regression has better performance with the value mean absolute percentage error (MAPE) is 8.554% that categorized as a highly accurate prediction for predicting Avomangos sweetness level.
UR - http://www.scopus.com/inward/record.url?scp=85106661343&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/733/1/012009
DO - 10.1088/1755-1315/733/1/012009
M3 - Conference article
AN - SCOPUS:85106661343
SN - 1755-1307
VL - 733
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012009
T2 - 4th International Conference on Green Agro-industry and Bioeconomy, ICGAB 2020
Y2 - 25 August 2020
ER -