TY - GEN
T1 - Classifying beneficiaries of islamic boarding school rehabilitation aid based on neural network approaches
T2 - 1st International Conference on Information and Communications Technology, ICOIACT 2018
AU - Almafaluti, Ahmad Andi Akmal
AU - Nugroho, Supeno Mardi Susiki
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/26
Y1 - 2018/4/26
N2 - Islamic Boarding Schools (pesantren in Indonesian language) often need government funding grants for improving education services, i.e. rehabilitation aid. Many affecting variables such as the number of student, pesantren activity type, and infrastructure condition need further examination, in addition to the large number of institutions. Because of those complex variables and the absence of definite variables pattern about correlation with the target classes, this research proposed two neural network based model for classifying beneficiaries to determine rehabilitation aid for the pesantren institutions and compared which is the best. 15 input variables were used as the features in learning model are accordance with 4 target classes. Neural Network formed from the learning process can generate new data classification as much as 100% for Backpropagation with accuration value 0.5, and 94.45489% for Radial Basis Function with accuration value 0.428571429.
AB - Islamic Boarding Schools (pesantren in Indonesian language) often need government funding grants for improving education services, i.e. rehabilitation aid. Many affecting variables such as the number of student, pesantren activity type, and infrastructure condition need further examination, in addition to the large number of institutions. Because of those complex variables and the absence of definite variables pattern about correlation with the target classes, this research proposed two neural network based model for classifying beneficiaries to determine rehabilitation aid for the pesantren institutions and compared which is the best. 15 input variables were used as the features in learning model are accordance with 4 target classes. Neural Network formed from the learning process can generate new data classification as much as 100% for Backpropagation with accuration value 0.5, and 94.45489% for Radial Basis Function with accuration value 0.428571429.
KW - Backpropagation NN
KW - Beneficiaries of Islamic Boarding School Rehabilitation Aid
KW - Radial Basis Function NN
KW - classification
UR - http://www.scopus.com/inward/record.url?scp=85050462198&partnerID=8YFLogxK
U2 - 10.1109/ICOIACT.2018.8350784
DO - 10.1109/ICOIACT.2018.8350784
M3 - Conference contribution
AN - SCOPUS:85050462198
T3 - 2018 International Conference on Information and Communications Technology, ICOIACT 2018
SP - 454
EP - 459
BT - 2018 International Conference on Information and Communications Technology, ICOIACT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 March 2018 through 7 March 2018
ER -