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THE OPTIMALIZATION OF BACKPROPAGATION NEURAL NETWORKS TO SIMPLIFY DECISION MAKING
Ramen Antonov Purba (a*), Samsir (b), Muhammad Siddik (c), Sondang (d), Miftah Faridh Nasir (e)

a,d)Manajemen Informatika, Politeknik Unggul LP3M
Jl. Iskandar Muda No. 3 CDEF, Medan - North Sumatera Indonesia
b)Teknik Informatika, Universitas alwashliyah Labuhanbatu
Jl. sempurna Rantauprapat
c)Teknik Informatika, STIKOM Pelita Indonesia Pekanbaru
Jl. Jend. Ahmad Yani No.82-88 Pekanbaru
e)Akuntansi, Politeknik Unggul LP3M
Jl. Iskandar Muda No. 3 CDEF, Medan - North Sumatera Indonesia

Email : ramen_purba[at]yahoo.com


Abstract

Private or public companies need tools to make easy decision making process. This research conducted at PT. FIF Medan. Focus in decision making to provision motor vehicle loans. The study do because PT. FIF Medan has problems to determining whether consumers are given financing. Research using Back Propagation Neural Network. Back Propagation Neural Network is a method that simplifies complex problems. Simplifying model by taking the most essential core issues. Research will be carried out with the stages of identifying problems, determining needs, analyzing, and choosing alternatives. 8 (eight) criteria will be parameters, including the amount of dependents, length of work, home status, history of finance, employee workplace, vehicle type, financing tenure, and monthly income.

Keywords: backpropagation, decision suport, neural network

Topic: Computer and Communication Engineering

Link: https://ifory.id/abstract/kcCyHD4wBuFr

Conference: The Third International Conference on Innovation in Engineering and Vocational Education (ICIEVE 2019)

Plain Format | Corresponding Author (Ramen Antonov Purba)

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