EMAIL: PASSWORD:
Front Office
UPT. PERPUSTAKAAN
Institut Teknologi Sepuluh Nopember Surabaya


Kampus ITS Sukolilo - Surabaya 60111

Phone : 031-5921733 , 5923623
Fax : 031-5937774
E-mail : libits@its.ac.id
Website : http://library.its.ac.id

Support (Customer Service) :
timit_perpus@its.ac.id




Welcome..guys!

Have a problem with your access?
Please, contact our technical support below:
LIVE SUPPORT


Moh. Fandika Aqsa


Davi Wahyuni


Tondo Indra Nyata


Anis Wulandari


Ansi Aflacha




ITS » Paper and Presentation » Teknik Elektro - Telematika S2
Posted by aprill@is.its.ac.id at 23/12/2014 22:40:53  •  1278 Views


KLASIFIKASI BERBASIS LVQ MENGGUNAKAN OPTIMASI LEARNING RATE UNTUK MEMILIH SISWA PESERTA OSN

THE CLASSIFICATION BASED ON LVQ USING OPTIMATION OF LEARNING RATE TO CHOOSE STUDENTS FOR THE OSN

Author :
PUJIANTO, WAHYU HADI ( 2211206705 )




ABSTRAK

Olimpiade Sains Nasional OSN pada tingkat SMA dibagi menjadi 8 bidang yaitu matematika fisika biologi kimia ekonomi kebumian astronomi dan komputer. Setiap sekolah harus mengirimkan minimal 3 siswa tiap bidang olimpiade untuk mengikuti seleksi OSN tingkat kabupatenkota sehingga total dipilih 24 siswa berkualitas. Data terdiri dari nilai rapor dan nilai tes potensi akademik TPA dengan jumlah variabel adalah 14 butir. Data ini dibagi menjadi dua yaitu data training dan data testing dipilih secara sistematik sampling Data diklasifikasikan berbasiskan learning vector quantization LVQ menggunakan perubahan nilai learning rate. Hasil penelitian menunjukkan Data semi-Ideal merupakan data yang cocok untuk pelatihan data dengan acuan jumlah neuron 25 x jumlah data training learning rate 001 diperoleh hasil klasifikasi terbaik dengan akurasi 8130 untuk data training dan 7920 untuk data testing.


ABSTRACT

OSN on the senior high school devided into 8 fields mathematic phisics biology chemistry economics geography astronomy and computer. Each school has to sent at least 3 studentsfield to participate this selection on each city so that it will be 24 qualified students. The data will be derived from score of raporand test of academic potensial TPA with 14 object variable. These data are devided into two test training data and testing data choosen random systematically. The data classified based on learning vector quantization LVQ using adaptive learning rate. The result shows the Data semi-Ideal was the accurate data for training data with the criterion total neuron 2.5 x total training data learning rate 0.01 so the classification result has accurancy 81.30 for training data and 79.20 for the testing data.



KeywordsPemilihan; OSN; optimasi learning rate; LVQ
 
Subject:  Matematika dan logika simbolik
Contributor
  1. Mochamad Hariadi, S.T., M.Sc., Ph.D
  2. DR. Surya Sumpeno, S.T., M.Sc.
Date Create: 23/12/2014
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-paper-22121140006730
Collection ID: 22121140006730
Call Number: RTE 511.3 Puj k


Source
Paper and Presentations, Electrical Engineering, RTE 511.3 Puj k, 2014

Coverage
ITS Community

Rights
Copyright @2014 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Summary ]

ITS-paper-22121140006730-35050.pdf




 Similar Document...




! ATTENTION !

To facilitate the activation process, please fill out the member application form correctly and completely

Registration activation of our members will process up to max 24 hours (confirm by email). Please wait patiently

POLLING

Bagaimana pendapat Anda tentang layanan repository kami ?

Bagus Sekali
Baik
Biasa
Jelek
Mengecewakan





You are connected from 35.175.248.25
using CCBot/2.0 (https://commoncrawl.org/faq/)



Copyright © ITS Library 2006 - 2019 - All rights reserved.
Dublin Core Metadata Initiative and OpenArchives Compatible
Developed by Hassan