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All Journal Edutech Wahana Didaktika Jurnal Pendidikan Usia Dini International Journal of Science and Applied Science: Conference Series AL-ISHLAH: Jurnal Pendidikan DWIJA CENDEKIA: Jurnal Riset Pedagogik Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Basicedu Jurnal Informatika Global Tik Ilmeu : Jurnal Ilmu Perpustakaan dan Informasi These proceedings represent the work of researchers participating in The International Conference on Elementary Education (ICEE) which is being hosted by the Elementary Education Study Programme School of Postgraduate Studies, Universitas Pendidikan
Alpin Herman Saputra
Universitas Terbuka
Religion Humanities Chemistry Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences Other

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Journal : Jurnal Informatika Global

 1 
Optimisasi Backpropagation Neural Network dalam Memprediksi IHSG Hartati Hartati; Alpin Herman Saputra; Imelda Saluza
Jurnal Informatika Global Vol 13, No 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i1.2066

Abstract

Covid-19 has become a global epidemic and has spread to many countries in the world, including Indonesia. The COVID-19 pandemic is one source of uncertainty that causes financial data to fluctuate and cause data to be volatile. This outbreak had an impact on financial data, not only on the Rupiah exchange rate but also on the Jakarta Composite Index (JCI). The uncertainty of the JCI makes it difficult for investors, data managers, and business people to predict data for the future. JCI is one indicator of the capital market (stock exchange). The uncertainty of the JCI data causes the need for predictions, so that investors, data managers, and business people can make the right decisions so that they can reduce risk and optimize profits when investing. One of the factors causing the JCI's decline was sentiment caused by investor panic over the rapid spread of COVID-19 in various cities in Indonesia. This research uses Backpropagation Neural Network (BPNN) in making predictions and continues with optimization of BPNN using ensemble techniques. Historical data from the JCI used were obtained from yahoo.finance. The ensemble technique used consists of two approaches, namely combining different architectures and initial weights with the same data and combining different architectures and weights. The results of network performance using ensemble technique optimization show good performance and can outperform the individual network performance of BPNN. Keywords: prediction, JCI, Optimization, BPNN, volatile
Co-Authors Ade Mardiana ANDAYANI ANDAYANI Ardo, Okilanda Bramianto Setiawan Dwi Heryanto Eri Irianto Faiz Hasbullah Hassan Gunawan Wiradharma Hartati Hartati Heryanto, Dwi Imelda Saluza, Imelda Khaerul Anam Laila Meiliyandrie Indah Wardani Melisa Arisanty Muktia Pramitasari Mustika Diana Mustika Diana Nuri Annisa Nuri Annisa Rahmat Sutedi Risma Nuriyanti Risma Nuriyanti Risnawati, Erna Robiansyah, Anton Steven Anthony Steven ANTHONY Sutedi, Rahmat Tatat Hartati Tatat Hartati Teguh Teguh Teguh Teguh Teguh, Teguh Venita Yusup