Mamdani Fuzzy Inference System (FIS) for Early Diagnosis of Diabetes Mellitus (DM) and Calorie Needs

DOI

10.2991/aer.k.201124.070How to use a DOI?

Keywords

FIS, Mamdani, Diabetes Mellitus, Calorie

Abstract

Diabetes Mellitus (DM) is a frightening type of disease because DM causes complications for the patients if it is not treated quickly. From year to year DM in Indonesia undergone a significant increase and was ranked 6th in the world. In this study, a fuzzy logic system was created for the early diagnosis of DM and calorie needs using the Mamdani method. The trial was conducted in collaboration with Jombang Regional Hospital by comparing the results of the doctor’s diagnosis with the fuzzy system created by taking 50 samples of inpatient’s medical record data. The first result of this research was a DM diagnosis system with 6 input variables, 3 output variables and 155 rules with MAPE achieved 29.48%. The second was a system of calorie requirement with 2 input variables, 2 output variables and 9 rules with the results achieved BMI with MAPE of 10.57% and BMR of MAPE of 9.7%.

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/).

Download article (PDF)

TY  - CONF
AU  - Humaidillah Kurniadi Wardana
AU  - Imamatul Ummah
AU  - Lina Arifah Fitriyah
PY  - 2020
DA  - 2020/11/24
TI  - Mamdani Fuzzy Inference System (FIS) for Early Diagnosis of Diabetes Mellitus (DM) and Calorie Needs
BT  - Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020)
PB  - Atlantis Press
SP  - 387
EP  - 394
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201124.070
DO  - 10.2991/aer.k.201124.070
ID  - Wardana2020
ER  -