RANCANGAN SISTEM REKOMENDASI PEMILIHAN JENIS SMARTPHONE DENGAN METODE JARINGAN SYARAF TIRUAN

Ilham Ramadhani, - (2019) RANCANGAN SISTEM REKOMENDASI PEMILIHAN JENIS SMARTPHONE DENGAN METODE JARINGAN SYARAF TIRUAN. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] PDF
AWAL.pdf

Download (521kB)
[img] PDF
ABTRAK.pdf

Download (88kB)
[img] PDF
BAB I.pdf

Download (219kB)
[img] PDF
BAB II.pdf
Restricted to Repository UPNVJ Only

Download (590kB)
[img] PDF
BAB III.pdf
Restricted to Repository UPNVJ Only

Download (226kB)
[img] PDF
BAB IV.pdf
Restricted to Repository UPNVJ Only

Download (810kB)
[img] PDF
BAB V.pdf

Download (204kB)
[img] PDF
DAFTAR PUSTAKA.pdf
Restricted to Registered users only

Download (195kB)
[img] PDF
RIWAYAT HIDUP.pdf
Restricted to Registered users only

Download (180kB)
[img] PDF
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only

Download (679kB)
[img] PDF
artikel_skripsi_ilham_ramadhani.pdf
Restricted to Registered users only

Download (706kB)

Abstract

Newley Purnell announced that this increase also discusses the protection of consumers in Southeast Asia who prefer smart phone products at varying prices with high-end features such as camera features, design, and battery and storage capacity. In this study, using backpropagtion artificial nerves is expected to provide another alternative in estimating and predicting the level of smartphone purchases. From the results of the study, the best network architecture was obtained from the 4-10-4-5 network pattern architecture and the best training algorithm. Artificial Neural Network backpropagation method for rating system in smartphone selection has a high level of accuracy which produces 85.52% and which the system cannot read by 14.48%. Such as gender, age, type of work, salary and so on

Item Type: Thesis (Skripsi)
Additional Information: [No. Panggil : 1410312048] [Penguji Utama : Reda Rizal] [Penguji I : Nurfajriah] [Penguji II/Pembimbing : Arrahmah Aprilia]
Uncontrolled Keywords: Recommendation System, ANN, Classification
Subjects: T Technology > TS Manufactures
Divisions: Fakultas Teknik > Program Studi Teknik Industri (S1)
Depositing User: Jayanta
Date Deposited: 09 May 2019 01:31
Last Modified: 09 May 2019 01:31
URI: http://repository.upnvj.ac.id/id/eprint/302

Actions (login required)

View Item View Item