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Penerapan Routing EIGRP, RIPv2 Dan OSPF Pada IPv6 Menggunakan Metode Redistribution Maulana, Andry; Harafani, Hani; Setiawan, Ade
Jurnal Pendidikan Teknologi dan Kejuruan Vol 15, No 2 (2018): Edisi Juli 2018
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (447.696 KB) | DOI: 10.23887/jptk-undiksha.v15i2.14276

Abstract

The benefits of a computer network are to be able to exchange information and facilitate the work. Information sent from one network to another cannot be separated from the use of the router. Determination of network address can be done by routing method. Routing on many routers is easier and more efficient when using dynamic routing like EIGRP, OSPF, and RIP. Different route settings become a problem in data transmission. The purpose of this study is to explain the method of routing data transmission route routing. The routing redistribution method is chosen as one way to connect the routing method by combining the method using IPv6. Based on the results of the tests conducted on redistribution routing by looking at the length of time the data packet delivery with ICMP then obtained EIGRP redistribution routing to OSPF with an average value of 3.478 seconds and OSPF redistribution to RIP with an average of 3.486 seconds, and EIGRP redistribution to RIP with average 3,514 seconds. While the value of ICMP data transmission the longest by using OSPF redistribution to EIGRP with an average of 4.976 seconds, RIP redistribution to EIGRP with an average of 4.616 seconds and RIP redistribution to OSPF with an average of 4.462 seconds.
APLIKASI PERHITUNGAN RESISTOR SMD BERBASIS ANDROID Setiawan, Ade; Maulana, Andry; Faisal, Muhamad; Pernando, Frenki
Jurnal Akrab Juara Vol 4 No 2 (2019)
Publisher : Yayasan Akrab Pekanbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In this study, how to create an SMD resistor application that aims to help mobile phone technicians who experience problems in reading an SMD resistor value whose size is as large as fleas. This is because the SMD resistor has unique codes to determine the value of a component that is not easily memorized for mobile and computer repair technicians, thus influencing the effectiveness and speed of work of mobile phone technicians. For the tools used in making this application include the Indigo Eclipse, Android Windows SD, UML and Flowchart.
Penerapan Algoritma Genetika pada Support Vector Machine Sebagai Pengoptimasi Parameter untuk Memprediksi Kesuburan Harafani, Hani; Maulana, Andry
Jurnal Teknik Informatika Vol. 5 No. 1 (2019): JTI Periode Februari 2019
Publisher : LPPM STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51998/jti.v5i1.303

Abstract

Abstract— Fertility rates ini various countries have decreased. The result of the WHO study found 50% the causes of infertility were men caused by a decrease in the quality of semen. In this study, Genetic Algorithm and SVM Methods are used to predict the quality of semen in the Fertility dataset. Based on experiments with 10 iterations, the highest level of accuracy knowb is SVM+GA(dot kernel) of 89%, then SVM of 88%, followed by Decision Tree 84%, Neural Network 82%, and Naïve Bayes 82%. In Conclusion, GA is proven to increase the accuracy value of SVM  with kernel dot which shows a significant difference, although 2 kernel of SVM shows insignificant differences. Intisari— Tingkat kesuburan di berbagai Negara mengalami penurunan, Hasil riset WHO mendapatkan 50% penyebab infertilitas adalah pihak pria yang disebabkan oleh menurunnya kualitas semen. Pada penelitian ini Algoritma Genetika dan metode SVM digunakan untuk memprediksi kualitas semen pada dataset Fertility. Berdasarkan eksperimen dengan 10 iterasi, didapatkan tingkat akurasi paling tinggi adalah SVM+GA(kernel dot) sebesar 89%, kemudian SVM sebesar 88%, disusul Decision Tree 84%, Neural Network 83%, dan Naïve Bayes 82%. Kesimpulannya GA terbukti dapat meningkatkan akurasi pada SVM dengan kernel dot yang menunjukkan perbedaan yang signifikan, meskipun 2 kernel dari SVM menunjukan perbedaan yang tidak signifikan. Kata Kunci— Letakkan 4-8 kata kunci Anda di sini, kata kunci dipisahkan dengan koma.
Penerapan Algoritma Genetika pada Support Vector Machine Sebagai Pengoptimasi Parameter untuk Memprediksi Kesuburan Harafani, Hani; Maulana, Andry
Jurnal Teknik Informatika Vol 5 No 1 (2019): JTI Periode Februari 2019
Publisher : LPPM STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51998/jti.v5i1.303

Abstract

Abstract— Fertility rates ini various countries have decreased. The result of the WHO study found 50% the causes of infertility were men caused by a decrease in the quality of semen. In this study, Genetic Algorithm and SVM Methods are used to predict the quality of semen in the Fertility dataset. Based on experiments with 10 iterations, the highest level of accuracy knowb is SVM+GA(dot kernel) of 89%, then SVM of 88%, followed by Decision Tree 84%, Neural Network 82%, and Naïve Bayes 82%. In Conclusion, GA is proven to increase the accuracy value of SVM  with kernel dot which shows a significant difference, although 2 kernel of SVM shows insignificant differences. Intisari— Tingkat kesuburan di berbagai Negara mengalami penurunan, Hasil riset WHO mendapatkan 50% penyebab infertilitas adalah pihak pria yang disebabkan oleh menurunnya kualitas semen. Pada penelitian ini Algoritma Genetika dan metode SVM digunakan untuk memprediksi kualitas semen pada dataset Fertility. Berdasarkan eksperimen dengan 10 iterasi, didapatkan tingkat akurasi paling tinggi adalah SVM+GA(kernel dot) sebesar 89%, kemudian SVM sebesar 88%, disusul Decision Tree 84%, Neural Network 83%, dan Naïve Bayes 82%. Kesimpulannya GA terbukti dapat meningkatkan akurasi pada SVM dengan kernel dot yang menunjukkan perbedaan yang signifikan, meskipun 2 kernel dari SVM menunjukan perbedaan yang tidak signifikan. Kata Kunci— Letakkan 4-8 kata kunci Anda di sini, kata kunci dipisahkan dengan koma.