TY - GEN
T1 - Geometric time variant particle swarm optimization with fuzzy - AHP for pomology plant recommendation
AU - Cholissodin, Imam
AU - Pambudi, Maulana Putra
AU - Dewi, Candra
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - In Indonesia, one of the most popular commodities is pomology (fruit). But, in Indonesia, fruit production rate is not bigger than fruit consumption rate. Lack of fruit production in Indonesia can be caused by a various factor. One of the factors is production failure that caused by wrong fruit choice. That factor can happen because of the lack of farmer knowledge about compatibility between land and fruit Therefore it takes a program that can use to help farmer check if their land is compatible with one kind of fruit or not. FAHP-GTVPSO is one of the methods that can solve a problem with many determining factors inside iL This method is a combination of 2 previous methods. That 2 previous method is Fuzzy-AHP and Geometric Time Variant Particle Swarm Optimization (PSO). Particle Swarm Optimization method will be working to optimize criteria weight ratio that should be generated from AHP. From the test result, Spearman coefficient for comparing rank result in 3 lands and 10 fruit is 0.8598. Besides that from the classification result, we can obtain Spearman coefficient is 0.9659.
AB - In Indonesia, one of the most popular commodities is pomology (fruit). But, in Indonesia, fruit production rate is not bigger than fruit consumption rate. Lack of fruit production in Indonesia can be caused by a various factor. One of the factors is production failure that caused by wrong fruit choice. That factor can happen because of the lack of farmer knowledge about compatibility between land and fruit Therefore it takes a program that can use to help farmer check if their land is compatible with one kind of fruit or not. FAHP-GTVPSO is one of the methods that can solve a problem with many determining factors inside iL This method is a combination of 2 previous methods. That 2 previous method is Fuzzy-AHP and Geometric Time Variant Particle Swarm Optimization (PSO). Particle Swarm Optimization method will be working to optimize criteria weight ratio that should be generated from AHP. From the test result, Spearman coefficient for comparing rank result in 3 lands and 10 fruit is 0.8598. Besides that from the classification result, we can obtain Spearman coefficient is 0.9659.
KW - farmer
KW - Fuzzy-AHP
KW - Geometric Time Variant Particle Swarm Optimization (GTVPSO)
KW - land suitability
KW - pomology
KW - Spearman coefficient
KW - wight of criteria
UR - https://www.scopus.com/pages/publications/85050907601
U2 - 10.1109/ICACSIS.2017.8355021
DO - 10.1109/ICACSIS.2017.8355021
M3 - Conference contribution
AN - SCOPUS:85050907601
T3 - 2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
SP - 121
EP - 126
BT - 2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
Y2 - 28 October 2017 through 29 October 2017
ER -