Mamdani Fuzzy Inference System (FIS) for Early Diagnosis of Diabetes Mellitus (DM) and Calorie Needs
Humaidillah Kurniadi Wardana, Imamatul Ummah, Lina Arifah Fitriyah
Humaidillah Kurniadi Wardana
Available Online 24 November 2020.
- https://doi.org/10.2991/aer.k.201124.070How to use a DOI?
- FIS, Mamdani, Diabetes Mellitus, Calorie
- 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%.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/aer.k.201124.070 ID - Wardana2020 ER -