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IMPLEMENTASI METODE MULTIPLE KERNEL SUPPORT VECTOR MACHINE UNTUK SELEKSI FITUR DARI DATA EKSPRESI GEN DENGAN STUDI KASUS LEUKIMIA DAN TUMOR USUS BESAR Yunita, Ariana; Fatichah, Chastine; Yuhana, Umi Laily
MATICS MATICS (Vol. 4 No. 2
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v0i0.1563

Abstract

Pada penelitian ini mengimplementasikan metode multiple kernel support vector machine untuk seleksi fitur. Multiple kernel merupakan metode modifikasi fungsi kernel yang mengalikan tiap elemen dari data. Metode ini melakukan seleksi fitur terhadap fitur yang kurang penting dengan tingkat akurasi lebih baik daripada metode dasar support vector machine. Uji coba dilakukan dengan menggunakan dataset ekspresi gen leukimia dan tumor usus besar. Hasil uji coba dibandingkan dengan tingkat akurasi metode support vector machine tanpa seleksi fitur. Tingkat akurasi metode multiple kernel support vector machine yang dihasilkan untuk data ekspresi gen leukimia yaitu 85% dan untuk data tumor usus besar sebesar 69%. Sedangkan tingkat akurasi dengan metode dasar support vector machine yaiu sebesar 82% untuk data leukimia dan 59% untuk data tumor usus besar. Seleksi fitur dapat mempersingkat waktu komputasi sehingga dapat dikembangkan untuk banyak aplikasi pengenalan pola. Kata Kunci: Multiple kernel, support vector  machine, seleksi fitur, data ekspresi gen
ANALISIS KEBUTUHAN UNTUK MEMBANGUN MEDIA PEMBELAJARAN MAYA YANG MENDUKUNG PROYEK ENERGI BARU DAN TERBARUKAN: ANALISIS KEBUTUHAN PENGGUNA Yunita, Ariana; Susanty, Meredita; Pamungkas, Galang Amanda Dwi; Nugroho, Herminarto
TEKNOLOGIA Vol 1 No 2 (2019): Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (478.063 KB)

Abstract

Energy security has become the main issue for Indonesia Government because Indonesia is targeted to be independent in energy field.To reach the goals NRE usage, there should be cooperations amongst all party : government, society, academicians as well as corporates. Virtual Learning Environment (VLE) is a powerful application to deliver knowledge in the digital age while contributes to educate society about New and Renewable Energy (NRE). However, user requirements are needed before developing VLE to reveal existing conditions and understand the users’ behaviour. This paper purposes to understand the user requirements, who are university students, to contribute to NRE project. Research methods used are interview, observation and questionnaire. Interview was conducted with Lentera Bumi Nusantara who develops NRE technology especially wind turbine in Indonesia. Observation was done in Lentera Bumi Nusantara’s office and questionnaire was distributed amongst 92 students in Universitas Pertamina, Jakarta, Indonesia. The results show that university students are human resources needed in NRE project. Then, learning materials regarding how to build blade and wind turbine have not distributed to others. Furthermore, results show that 84% of university students are ready to contribute in NRE project. However, only 37% of university students own original idea for NRE project related to their academic background. To build the VLE to support NRE projects, there should be menu for university students to discuss online so they can share ideas regarding NRE and menu for contributing to NRE project in Indonesia.