TY - GEN
T1 - A Decision Tree Knowledge-based System for Reviewing Research Ethics Protocol
AU - Anggraini, Ratih Nur Esti
AU - Ariyani, Nurul Fajrin
AU - Septiyanto, Abdullah F.
AU - Sarno, Riyanarto
AU - Meilani, Zahra D.
AU - Soendoro, Triono
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Knowledge base systems have undergone many developments in providing similar results to experts. This can help increase time effectiveness in determining decisions and analysis results. Several methods have given good results in determining decisions based on knowledge, one of which is using a decision tree. In this study, the researchers applied decision tree modeling to determine the results of the review on ethical research protocols. Our target is to classify ethical protocols into one of three decisions: Exempted, Expedited, or Full Board. Three decision tree models are used in this research to evaluate the best results that can predict the ethical review protocol results according to the expert's dataset. The experiments showed that all models showed the same result, with an accuracy value of 0,91, precision of 0,93, and recall of 0,91. However, manual checking showed that the second model with Gini criteria parameters and class weight balance resulted in 10 data correctly predicted based on the dataset used.
AB - Knowledge base systems have undergone many developments in providing similar results to experts. This can help increase time effectiveness in determining decisions and analysis results. Several methods have given good results in determining decisions based on knowledge, one of which is using a decision tree. In this study, the researchers applied decision tree modeling to determine the results of the review on ethical research protocols. Our target is to classify ethical protocols into one of three decisions: Exempted, Expedited, or Full Board. Three decision tree models are used in this research to evaluate the best results that can predict the ethical review protocol results according to the expert's dataset. The experiments showed that all models showed the same result, with an accuracy value of 0,91, precision of 0,93, and recall of 0,91. However, manual checking showed that the second model with Gini criteria parameters and class weight balance resulted in 10 data correctly predicted based on the dataset used.
KW - decision tree
KW - ethics protocol
KW - knowledge-based system
UR - http://www.scopus.com/inward/record.url?scp=85146650206&partnerID=8YFLogxK
U2 - 10.1109/COMNETSAT56033.2022.9994414
DO - 10.1109/COMNETSAT56033.2022.9994414
M3 - Conference contribution
AN - SCOPUS:85146650206
T3 - Proceeding - IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022
SP - 50
EP - 55
BT - Proceeding - IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022
Y2 - 3 November 2022 through 5 November 2022
ER -