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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed Saputra, Widodo; Hardinata, Jaya Tata; Wanto, Anjar
JITE (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING) Vol 3, No 1 (2019): EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (218.484 KB) | DOI: 10.31289/jite.v3i1.2704

Abstract

Unemployment is a big problem faced by the Indonesian people from year to year besides poverty. Therefore it is necessary to predict the level of open unemployment in Indonesia so that later the government and private parties have the right references and references to work together to overcome this problem. The prediction method used is Resilient Backpropagation which is one method of Artificial Neural Networks which is often used for data prediction. The research data used is open unemployment data according to the highest education completed in 2005-2018 based on the semester obtained from the website of the Indonesian Central Bureau of Statistics. Based on this data a network architecture model will be formed and determined, including 12-6-2, 12-12-2, 12-18-2, 12-24-2, 12-12-12-2, 12-12-18 -2, 12-18-18-2 and 12-18-24-2. From these 8 models after training and testing, the results show that the best architectural model is 12-18-2 (12 is the input layer, 18 is the number of hidden neurons and 2 is the output layer). The accuracy of the architectural model for semester 1 and semester 2 is 75% with an MSE value of 0.0022135087 and 0.0044974696
Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed Widodo Saputra; Jaya Tata Hardinata; Anjar Wanto
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 3, No 1 (2019): EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v3i1.2704

Abstract

Unemployment is a big problem faced by the Indonesian people from year to year besides poverty. Therefore it is necessary to predict the level of open unemployment in Indonesia so that later the government and private parties have the right references and references to work together to overcome this problem. The prediction method used is Resilient Backpropagation which is one method of Artificial Neural Networks which is often used for data prediction. The research data used is open unemployment data according to the highest education completed in 2005-2018 based on the semester obtained from the website of the Indonesian Central Bureau of Statistics. Based on this data a network architecture model will be formed and determined, including 12-6-2, 12-12-2, 12-18-2, 12-24-2, 12-12-12-2, 12-12-18 -2, 12-18-18-2 and 12-18-24-2. From these 8 models after training and testing, the results show that the best architectural model is 12-18-2 (12 is the input layer, 18 is the number of hidden neurons and 2 is the output layer). The accuracy of the architectural model for semester 1 and semester 2 is 75% with an MSE value of 0.0022135087 and 0.0044974696
Co-Authors Abdi Rahim Damanik Adeita A. Ndraha Agus Perdana Windarto Andini, Yulia Andri Nata Angel Ariski Simatupang Arda Pakpahan Arminarahmah, Nur Astri Veranita Sinaga Aulia Ichwanda Ramadhan Azarya N J Siahaan Batubara, Lokot Ridwan Batubara, Monica Sari Chairani, Yulia Chintya Carolina Situmorang Damanik, Abdi Rahim Damanik, Afriyani Debby Febriani R. Saragih Deddy Wahyudin Purba Dedi Handoko Dedi Handoko Dedi Suhendro Dedy Hartama Dedy Hartama Dewi, Rafiqa Dian Lestari Hutapea Dinda Zefanya Simanjuntak Dudes Manalu Efendi, Elfin Eka Desriani Aritonang Eka Irawan Eka Irawan Eka Irawan Ema Deloris Silaban Exaudi Sirait, Debora Fadillah Alwi Pambudi Ferri Ojak Immanuel Pardede Ferri Ojak Immanuel Pardede Gayus Simarmata GS , Achmad Daengs Hans Lambertus Sidabutar Harefa, Onesimus Hartama, Dedy Hendry Qurniawan Hendry Qurniawan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan, Heru Satria I Irawan Ilham Syahputra Saragih Irfan Sudahri Damanik Jhon Radho Hutahaean, Josua Juli Antasari Br Sinaga Kiki Aidi Saputra Lumbantobing, Gilbert Batahi M Safii M. Fauzan Manurung, Rado Marina Rajagukguk Melda Veby Ristella Munthe Muhammad Arifullah Muhammad Azri Muhammad Fauzan Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Safii Nadeak, Vincentius Danu Bona Arta Nur Arminarahmah Ojak Immanuel Pardede, Ferri Okprana, Harly Pardede, Cierlin Peniel Sam Putra Sitorus Perdamaian Pernando Sitanggang Purba, Eka Yunita Purba, Ningsih Septi Uli Purba, Yuegilion Pranayama Purnama Nuraini Putri Mai Sarah Tarigan Putri Mai Sarah Tarigan Putriyani Matondang Qurniawan, Hendry Ratu Christine Siallagan Rektor Sianturi, Rektor Riama Ester Angelina Sihombing Rick Hunter Simanungkalit, Rick Hunter Riska Oktavia Safii, M Safruddin, S Saifullah Saifullah Saifullah Saifullah Sam Putra Sitorus, Peniel Samosir, Makmur Jaya Samuel Alex Lubis Saragih, Lusi Saragih, Reagan Surbakti siagian, Novita sari Sibagariang, Susy Alestriani Sidabutar, Saudurma S. S. Sidauruk, Adrian Silaban, Lesteria Tri Yani Silalahi, Elisabeth N. R. Silalahi, Serenita Silalahi, Stefani Silitonga, Enjel Debora Simatupang, Yosua Alexandru Simbolon, Maria Etty Simorangkir, Marhite Sinaga, Christa Voni Roulina sinaga, Irene Lestaria Sinaga, Leony Sinta Maria Sinaga Sinurat, Rahul Siti Hadija Sitohang, Septian Trio Sitorus, Peniel Sam Putra Situmorang, Eduward Suhada Suhada, Suhada Sundari Retno Andani Surbakti Saragih, Reagan Tampubolon, Arion Tarigan, Putri Mai Sarah Vina Merina Br Sianipar Vivi Auladina Voni Roulina Sinaga, Christa Wanto, Anjar Widodo Saputra Winanjaya, Riki Wulan Liviana Simbolon Yuegilion Pranavarna Purba Yuegilion Pranayama Purba Yuegilion Pranayama Purba Yulia Andini Yuliana Nainggolan Yuni Arista Saragih Zulaini Masruro Nasution