Anggraeni, DewiRetno (2014) Sistem Pakar Tuberkulosis Pada Anak Menggunakan Metode Fuzzy K-NN. Sarjana thesis, Universitas Brawijaya.
Abstract
Penyakit tuberculosis atau TB sampai saat ini masih menjadi masalah kesehatan masyarakat diantaranya pada anak-anak. Permasalahan yang mendasar adalah gejala pada anak yang tidak khas sehingga sulit untuk didiagnosis. Permasalahan tersebut dapat diatasi dengan teknik scoring system. Penelitian ini bertujuan untuk memudahkan dokter dalam mendiagnosis, tetapi dengan syarat pasien sudah mempunyai rekam medis. Metode yang digunakan dalam penelitian ini adalah menggunakan Fuzzy K-NN. Metode Fuzzy K-NN adalah suatu varian dari algoritma K-NN yang merupakan gabungan antara teknik Fuzzy dan K-NN Classifier. Berdasarkan konsep dasar K-NN yaitu memberikan teknik klasifikasi yang sederhana tetapi mempunyai hasil kerja yang cukup bagus sehinggaa diharapkan metode ini dapat memberikan cara klasifikasi yang sederhana, mudah dan cepat. Pengujian pada penelitian ini dilakukan dengan uji akurasi dan black box. Hasil penelitian menunjukkan bahwa semakin banyaknya varian data latih yang digunakan maka akan berpengaruh terhadap nilai akurasi yang didapatkan dan pengujian black box menunjukkan nilai valid sebesar 100% yang menandakan bahwa fungsionalitas sistem dapat berjalan dengan baik sesuai dengan daftar kebutuhan. Sedangkan pada akurasi sebesar Pada pengujian data latih terhadap akurasi, akurasi tertinggi pada data latih ke 100 dan 150 dengan rata-rata 98,2 dan 97,8. Untuk pengujian data uji rata-rata nilai tertinggi pada data uji 10 yaitu 100 % untuk data latih ke 100 dan untuk data latih 150 memiliki prosentase 97,8 % untuk data uji 10 dan data uji 20.
English Abstract
Tuberculosis or TB disease is still a public health problem among children . Underlying issue is the childs symptoms are not typical so difficult to diagnose. These problems can be overcome by engineering scoring system . This study aims to facilitate the physician in diagnosing , but on condition that the patient already has a medical record . The method used in this study is the use of Fuzzy K - NN . Fuzzy K - NN method is a variant of the K - NN algorithm that is a combination of technique and Fuzzy K - NN Classifier . Based on the basic concept of providing K - NN classification techniques are simple but have a pretty good work sehinggaa expected that this method can provide classification method that is simple, easy and fast. Tests conducted in this study to test the accuracy and the black box . The results showed that the number of variants of the training data used will affect the accuracy of the values obtained and black box testing indicate a valid value of 100 %, which indicates that the functionality of the system can run well in accordance with the listing requirements. The accuracy of On testing the accuracy of training data, the highest accuracy on training data to 100 and 150 with an average of 98.2 and 97.8. The test data on average the highest score on the test data 10 that is 100% for training data to 100 and 150 for training data has a percentage of 97.8% for the test data and test data 10 and 20.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2014/84/051403264 |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Hasbi |
| Date Deposited: | 18 Jun 2014 08:54 |
| Last Modified: | 20 Oct 2021 06:47 |
| URI: | http://repository.ub.ac.id/id/eprint/146121 |
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