Aplikasi Diagnosis Tingkatan Pneumonia dan Saran Pengobatan dengan Fuzzy Tsukamoto

Elyza Gustri Wahyuni, Ahmad Syahriza Ramadhan

Abstract


Pneumonia is a disease that attacks almost every human being, ranging from young people to adults. Doctors often find it difficult to identify someone who has pneumonia, because pneumonia has several levels of classification, making it possible to experience symptoms that are also different. Pulmonary specialist experts classify pneumonia classification to be "mild" and "severe", making it easier for doctors to diagnose pneumonia. One of the right methods is to use fuzzy logic because it tends to have symptoms and diagnoses that are biased/fuzzy. The conclusion of testing several primary data obtained from interviews and system testing is that the implementation of the pneumonia diagnosis system with Tsukamoto fuzzy logic can help experts determine the level of pneumonia according to the symptoms experienced by the patient, with the value of user acceptance testing at 95%.

Keywords


Pneumonia; Logika Fuzzy; Tsukamoto; diagnosis

Full Text:

PDF

References


“Modul dan Materi Promosi Kesehatan untuk Politeknik/D3,” Pusat Promosi Kesehatan Depkes RI, 2006.

Z. Hoare Z, W.S. Lim, “Pneumonia: Update on Diagnosis and Management,” BMJ, Vol. 332, No. 7549, hal. 1077-1079, 2006.

(2014) “Pneumonia Balita” [Online], http://www.depkes.go.id/ downloads/publikasi/buletin/BULETIN%20PNEUMONIA.pdf, tanggal akses: 6-Sep-2017.

A. Pratiwi, E.G. Wahyuni, “Sistem Pakar Diagnosis Ispa pada Balita dengan Metode Certainty Factor,” Seminar Nasional Informatika Medis (SNIMED VII), 2016, hal. 42-53.

E.P. Wiweka, “Sistem Pakar Diagnosa Infeksi Saluran Pernafasan Akut (ISPA),” Jurnal Sistem dan Teknologi Informasi, Vol. 1, No. 1, hal. 1-5, 2013.

Y. Farida, A. Trisna, dan D. Nur W., “Studi Penggunaan Antibiotik pada Pasien Pneumonia di Rumah Sakit Rujukan Daerah Surakarta,” Journal of Pharmaceutical Science and Clinical Research, Vol. 2, hal. 44-52, 2017.

F. Thamrin, E. Sediyono, dan Suhartono, “Studi Inferensi Fuzzy Tsukamoto untuk Penentuan Faktor Pembebanan Trafo PLN,” Teknologi Informasi, Vol. 2, No. 1, hal.1-5, 2012.

E.G. Wahyuni, dan B.R. Rahman, “Sistem Pendukung Keputusan KPR Menggunakan Fuzzy Inference System (FIS) Metode Tsukamoto,” Seminar Nasional Teknologi dan Rekayasa Informasi (SENTRIN), 2016, hal. 36-44.

A. Saelan, “Logika Fuzzy,” Institut Teknologi Bandung, Bandung, Indonesia, Lecture report, hal. 1-5, 2009.

S. Kusumadewi dan H. Purnomo, Aplikasi Logika Fuzzy untuk Mendukung Keputusan, Yogyakarta, Indonesia: Graha ilmu. 2004.

W. Budiharto dan D. Suhartono, Artificial Intelligence: Konsep dan Penerapannya,Yogyakarta, Indonesia: Andi Publisher, 2014.

D. Kho (2017) “Pengertian Skala Likert dan Menggunakannya,” [Online] http://teknikelektronika.com/pengertian-skala-likert-likert-scale-menggunakan-skala-likert/, tanggal akses: 6-Nov-2017.




DOI: http://dx.doi.org/10.22146/jnteti.v8i2.500

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Jurnal Nasional Teknik Elektro dan Teknologi Informasi

Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik Universitas Gadjah Mada
Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
+62 274 552305
jnteti@ugm.ac.id