Identifikasi Diagnosis Gangguan Autisme Pada Anak Menggunakan Metode Modified K-Nearest Neighbor (Mknn)

Sianipar., Jojor Jennifer (2017) Identifikasi Diagnosis Gangguan Autisme Pada Anak Menggunakan Metode Modified K-Nearest Neighbor (Mknn). Sarjana thesis, Universitas Brawijaya.

Abstract

Autisme adalah suatu gangguan neurologis yang secara signifikan mengakibatkan kurangnya kemampuan membentuk hubungan sosial, komunikasi yang normal, dan juga perilaku pada anak. Gejala autisme ini pada umumnya timbul sebelum anak mencapai usia 3 tahun. Autisme bukan penyakit kejiwaan karena autisme adalah suatu gangguan yang terjadi pada otak sehingga menyebabkan otak anak tersebut tidak dapat berfungsi normal dan hal tersebut termanifestasi pada perilaku anak autisme. Ada beberapa penelitian yang mengatakan bahwa penyebab autisme yaitu gangguan saraf pusat yang menyebabkan pada kelainan struktur otak anak. Ahli yang berbeda menyebutkan bahwa autisme salah satu penyebabnya adalah jenis makanan yang dikonsumsi salah atau dikarenakan berada dalam lingkungan yang banyak zat-zat berbahaya yang menyebabkan masalah dalam sikap ataupun tingkah laku anak. Untuk menangani gangguan autisme maka dibuat sistem untuk identifikasi gangguan autisme pada anak menggunakan metode Modified K-Nearest Neighbor (MKNN). Metode ini adalah salah satu metode klasifikasi berdasarkan kemunculan kelas terbanyak pada nilai data latih. Terdapat 14 gejala dari 4 aspek yang digunakan sebagai parameter dalam pengembangan sistem. Keluaran yang dihasilkan sistem merupakan status gangguan autisme atau tidak pada anak. Berdasarkan pengujian yang telah dilakukan sistem yang menggunakan metode Modified K-Nearest Neighbor (MKNN) memperoleh hasil akurasi maksimum 100% serta akurasi minimum 92%. Berdasarkan hasil tersebut, sistem yang menggunakan metode Modified K-Nearest Neighbor (MKNN) dapat diimplementasikan dalam kehidupan sehari-hari.

English Abstract

Autism is a neurological disorder that shows significant result as a lack of ability to form social relationships, normal communication, and behavior in children. This symptoms generally appear before children reach the age of 3 years. It is not classified as a psychiatric disease because autism is a disorder that occurs malfunction of children’s brain and it is manifested on children’s behaviour. Some research states that autism causes as the neurodevelopmental disorder that causes abnormalities in children’s brain structure. Different experts mentioned that autism in children caused by the kind of food they consumed or they living environment that contain many harmful substances that shows in children’s behaviour. Therefore, the system for the identification of autism disorders in children will be create to help identifies autism disorder by using the method of Modified K-Nearest Neighbor (MKNN). It is one of classification method based on the appearance of largest classes in data training. There are 14 symptoms from 4 aspects that are used as parameters in the development of the system. The output of the system is status whether a child is autistic individuals or not. Based on the testing that has been done on the system that using Modified K-Nearest Neighbor (MKNN), maximum accuracy shows 100% accuracy while minimum accuracy is 92%. Based on those results, the uses of Modified K-Nearest Neighbor (MKNN) method can be implemented in our daily life.

Item Type: Thesis (Sarjana)
Identification Number: SKR/FTIK/2017/236/051704795
Uncontrolled Keywords: Autisme, Klasifikasi, Modified K-Nearest Neighbor (MKNN)
Subjects: 000 Computer science, information and general works > 004 Computer science > 004.015 1 Finite mathematic
Divisions: Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Sugiantoro
Date Deposited: 17 Jul 2017 02:04
Last Modified: 11 Dec 2020 05:02
URI: http://repository.ub.ac.id/id/eprint/262
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