PROTOTIPE SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SISWA AKSELERASI DENGAN MENERAPKAN LOGIKA FUZZY: STUDI KASUS SMA NEGERI 11 KAB. TANGERANG
Abstract
Salah satu program pemerintah dalam meningkatkan kualitas sumber daya manusia pada peserta didik yang memiliki potensi belajar gifted (nilai IQ minimal 130) yaitu dengan menyelenggarakan kelas akselerasi yang bertujuan untuk meningkatkan wawasan pengetahuan, kemampuan kreatifitas, menanamkan sikap disiplin serta untuk menguasai ilmu pengetahuan dan teknologi dalam waktu yang lebih cepat dari kelas umumnya. Beberapa permasalahan dalam memilih siswa akselerasi yang dilakukan oleh panitia seleksi pada tahun pertama diantaranya yaitu hanya berdasarkan nilai dari intelegensi (IQ) melalui psikotest. Pemilihan siswa akselerasi pada tahun kedua (tahun akademik 2013/2014) diperlukan beberapa faktor diantaranya yaitu tingkat intelegensi (IQ), nilai raport tingkat menengah pertama semester 3, 4, dan 5 (NR), nilai potensi akademik, nilai kreatifitas, nilai produktifitas, dan nilai pengamatan kelas yang dilakukan oleh tenaga pendidik. Oleh karena kompleksitas kriteria tersebut, maka perlu dirancang suatu sistem pendukung keputusan yang akan digunakan oleh pihak panitia penerimaan siswa baru akselerasi dengan menerapkan logika fuzzy sugeno. Implementasi aplikasi menggunakan software Matlab R2008b. Hasil dengan pendekatan logika fuzzy Sugeno adalah dapat membantu panitia dalam membuat keputusan pemilihan siswa akselerasi melalui sistem aplikasi yang akan diajukan pada kepala Sekolah Menengah Atas.
References
Marimin. 2009. Teori dan Aplikasi Sistem Pakar dalam Teknologi Manajerial. Bogor: IPB Press.
Marimin, dkk. 2013. Teknik dan Analisis Pengambilan Keputusan
Fuzzy dalam Manajemen Rantai Pasok. Bogor: IPB Press.
Mathwork 2008. Creating Graphical User Interface Matlab R2008b. MathWorks, Inc.
Panitia P3CI. 2013. Panduan Pelaksanaan Peningkatan
Pembelajaran Program Cerdas Istimewa. Jakarta: Direktorat Jenderal Pendidikan Menengah Kemdikbud.
Kusumadewi, Sri. 2003. Artificial Intelegence (Teknik dan Aplikasinya). Yogyakarta : Graha
Ilmu.
Arikunto, Suharsimi. 2002. Prosedur Penelitian. Jakarta: Rineka Cipta.
Sri Herawati dan Wahyudi Agustiono. 2009. Interaksi Manusia dan Komputer. Bangkalan: ITS.
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