Model Deteksi Autis Secara Dini Berdasarkan Pendekatan Logika Fuzzy Inference System Metode Mamdani

Model Deteksi Autis Secara Dini Berdasarkan Pendekatan Logika Fuzzy Inference System Metode Mamdani

• By Kaafi, Ahmad Al;
• Jurnal Nasional Terakreditasi
• 110
• 12 – 21

Autism is a disorder in children who have speech and a different way of communicating with other children his age were caused by developmental abnormalities of the nervous system. The term autism was first introduced by Leo Kanner in 1943. It used to autism is considered to be a lifelong disorder that can not be handled, but today many are aware that the handling of the symptoms of autism as early as possible can bring remarkable changes impact on children's development who have it. To check whether a child has autism or not, to use international standards on autism. ICD-10 (International Classification of Diseases) in 1993 and DSM-IV (Diagnostic and Statistical Manual) in 1994 to formulate criteria for the diagnosis of Autism Infantil with the same content, which is currently used throughout the world. Fuzzy logic can be used in diagnosing autis early childhood. Fuzzy Inference System (FIS) is a model Mamdani Mamdani fuzzy reasoning system that can be applied in the process of diagnosing autis in children of various criteria for patient characteristics. Using a data processing application logic while Mamdani FIS decision support systems using MATLAB toolbox R2011b. The result of this study is to diagnose autis decision support early childhood Mamdani FIS approach is more precise and efficient.

• Katakunci Diagnoses Of Autism, Fuzzy Inference System Method Mamdani
• URL http://ejournal.bsi.ac.id/ejurnal/index.php/Bianglala/issue/view/207
• Penerbit LPPM BSI Yogyakarta, Yogyakarta DI Yogyakarta

REFERENSI

[1]. Adeli, Ali dan Mehdi Neshat. 2010. A Fuzzy Expert System for eart Disease.IMECS 2010 Vol I.

[2]. Ayuningtiyas, Ika Kurnianti, dkk. 2007.Sistem Pendukung Keputusan Penanganan Kesehatan Balita Menggunakan Penalaran Fuzzy Mamdani. Seminar Nasional Aplikasi Teknologi Informasi 2007 (SNATI 2007).Yogyakarta.

[3]. Budiharto, Widodo. 2008. Membuat Sendiri Robot Cerdas-Edisi Revisi. Jakarta: PT.Alex Media Komputindo.

[4]. Basyaib, Fachmi. 2006. Teori Pembuatan Keputusan. Jakarta : PT.Grasindo.

[5]. Cannon, Joseph P., Perreault, Jr, William D,. McCarthy, E Jerome. Pemasaran Dasar, Jakarta: Salemba Empat, 2009.

[6]. Churchill, Jr Gilbert A. Dasar-dasar Riset Pemasaran, Jakarta: Erlangga, 2005.

[7]. Djohan. 2009. Psikologi Musik. Yogyakarta : Best Publisher.

[8]. Hapsari, Dian Puspita, dkk. 2012. Sistem Pendukung Keputusan Peramalan Cuaca Dengan Menggunakan Logika Fuzzy Mamdani. Jurnal IPTEK Vol 16 No.1. ITS

[9]. Kusrini. 2008. Aplikasi Sistem Pakar Menentukan Faktor Kepastian Pengguna dengan Metode Kuantifikasi Pertanyaan.Yogyakarta : PT.Andi Offset.

[10]. Kusumadewi, Sri. 2002. Analisa Desain Sistem Fuzzy menggunakan ToolBox Matlab. Edisi Pertama. Cetakan pertama.Yogyakarta : Graha Ilmu.

[11]. Laudon, Kenneth C and Laudon, Jane P.Sistem Informasi Manajemen, Jakarta:Salemba Empat, 2008.

[12]. Naba, Agus 2009. Belajar Cepat Fuzzy Logic Menggunakan Matlab. Yogyakarta:  PT.Andi Offset. 

[13]. Priyatna, Andri. 2010. Amazing Autism!.Jakarta : PT Elex Media Komputindo.

[14]. Ramza, Haryy. Dewanto, Yohanes. 2010. Teknik Pemrograman Manggunakan Matlab. Jakarta : PT.Grasindo

[15]. Sharma, Priynka, dkk. 2013. International Journal of Information and Computer Technology. ITM University, Gwalior. 

[16]. Sunu, Christopher. 2012. Panduan Mencegah Masalah Autisme: Unlocking Autisme. Yogyakarta: Lintangterbit

[17]. Turban,E., Aronson,J.E., dan LiangTing,P., 2005. Decision Support Sistems and Intelligent Sistems. Edisi 7,

Jilid 1, Versi Bahasa Inonesia, Andi Offset, Jogya

[18]. Tutik, Gusti Ayu Kadek, Rosa Delima dan Umi Proboyekti. 2009. Penerapan Forward Chaining Pada Program Diagnosa Anak Penderita Autisme. Jurnal Informatika, Volume 5 Nomor 2, November 2009 : 46 – 59. Diambil dari:http://ti.ukdw.ac.id/ojs/index.php/informatika/article/view/73/35.(10 September 2012)

[19]. Triyuniarta, Afiat,dkk. 2009. Aplikasi Logika Fuzzy Untuk Pendukung Keputusan Penentuan Keluarga Miskin Di Kota Yogyakarta. Seminar Nasional Informatika 2009 semnasIF2009).ISSN:1979-2328.Yogyakarta

[20]. Veskarisyanti, Galih A. 2008. 12 Terapi Autis Paling Efektif & Hemat Untuk Autisme, Hiperaktif dan Retardasi Mental. Yogyakarta: Percetakan Galangpress.

[21]. Widodo, Prabowo Pudjo. Handayanto, Rahmadya Trias. 2012. Penerapan Soft Computing Dengan Matlab. Edisi Revisi.Bandung : Rekayasa Sains.

[22]. Yatim, Faisal. 2007. Autisme: Suatu Gangguan Jiwa Pada Anak-anak. Jakarta: Pustaka Populer Obor.

[23]. Zadeh, L. A. (1994, Maret). Fuzzy Logic, Neural Networks and Soft Computing. Communication of The ACM , pp. 77-84.