Expert System for Diagnosing Early Symptoms of Stroke Using the Fuzzy Mamdani Method
Sistem Pakar Diagnosa Gejala Dini Penyakit Stroke Menggunakan Metode Fuzzy Mamdani
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(1) * Sylfanie Sekar Mayang
Universitas Muhammadiyah Sidoarjo, Indonesia
Indonesia
(2) Ade Eviyanti Universitas Muhammadiyah Sidoarjo, Indonesia
Indonesia
(*) Corresponding Author
Abstract
One of the dangerous diseases is stroke because it can disrupt the nervous system system in humans so that sufferers of this disease often experience paralysis in their body parts. Therefore, an application is needed to assist medical personnel when doctors are not available or are not on duty. Expert system applications are needed in early diagnosing the characteristics of the disease suffered by a patient. Expert systems are computer-based systems that use knowledge, facts and reasoning techniques to solve problems. The purpose of this study is to make it easier for researchers to identify problems with stroke based on the symptoms experienced by the patient or a person. The research method used is the fuzzy mamdani method. Data collection techniques are quantitative data techniques. The results that have been achieved from this study are that it can prevent and reduce the risk of stroke that can occur as early as possible in sufferers or the community and reduce the death rate in stroke patients.
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References
A. F. Poni Wijayanti, “Jurnal Sarjana Teknik Informatika,” SISTEM PAKAR MENDIAGNOSA JENIS PENYAKIT STROKE MENGGUNAKAN METODE CERTAINTY FACTOR, vol. II, no. 1, p. 13, 2014.
R. P. S. M. I. Z. Jansen Kanggeraldo, “JURNAL RESTI (Rekayasa Sistem danTeknologi Informasi),” Sistem Pakar Untuk Mendiagnosis Penyakit Stroke Hemoragik dan Iskemik Menggunakan Metode Dempster Shafer, vol. II, no. 2, p. 498, 2018.
E. P. S. Ira Lina Kendayto Panjaitan, “Journal Of Informatic Pelita Nusantara,” ANALISIS PERBANDINGAN METODE DEMPSTER SHAFER DENGAN METODE CERTAINTY FACTOR UNTUK MENDIAGNOSA PENYAKIT STROKE, vol. III, no. 1, p. 69, 2018.
G. S. M. A. M. S. M. Romy Ramanda, PERANCANGAN APLIKASI SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT STROKE ISKEMIK DENGAN MENGGUNAKAN BAHASA PEMOGRAMAN PHP DAN MYSQL.
A. A. S. ,. E. A. M. Deby Putri Indraswari, “Journal of Environmental Engineering & Sustainable Technology,” SISTEM PENDUKUNG KEPUTUSAN DETEKSI DINI PENYAKIT STROKE MENGGUNAKAN METODE DEMPSTER-SHAFER, vol. II, no. 2, p. 97, 2015.
K. H. I. W. T. Moh. Zainuddin, PENERAPAN CASE BASED REASONING (CBR) UNTUK MENDIAGNOSIS PENYAKIT STROKE MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR, 2016.
R. Dwi, “Jurnal Sistem Informasi & Telematika (Telekomunikasi, Multimedia & Informatika),” PEMANFAATAN CERTAINTY FACTOR DALAM MENENTUKAN JENIS PENYAKIT PENYEBAB STROKE, vol. VIII, no. 2, p. 122, 2017.
T. A. S. S. Annisa Natassya, “Jurnal Sistem dan Teknologi Informasi,” Case Based Reasoning Diagnosis Risiko Penyakit Stroke Menggunakan Metode Hamming Distance, vol. VII, no. 2, p. 123, 2019.
G. P. Agus Ramdhani Nugraha, “JURNAL MANAJEMEN INFORMATIKA,” SISTEM INFORMASI AKADEMIK SEKOLAH BERBASIS WEB DI SEKOLAH MENENGAH PERTAMA NEGERI 11 TASIKMALAYA, vol. IV, no. 2, p. 7, 2017.
H. R. H. Nataniel Dengen, “Jurnal Informatika Mulawarman,” Perancangan Sistem Informasi Terpadu Pemerintah Daerah Kabupaten Paser, vol. 4, no. 1, 2009.
