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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
M Fauzan
STIKOM Tunas Bangsa, Pematangsiantar, Medan, Indonesia
Computer Science & IT Control & Systems Engineering

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Implementasi Algoritma Backpropagation Dalam Memprediksi Harga Bahan Pangan Deni Saputra; M Safii; M Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.37

Abstract

Foodstuffs are raw materials in the form of agricultural, vegetable, and animal products used by the food processing industry to produce a food product. Prices of foodstuffs sometimes rise and fall erratically. The purpose of this research is to predict the price of foodstuffs by using the Backpropagation algorithm. The data used in this study is food price data from 2016 to 2019, originating from the Pusat Informasi Harga Pangan Statistics (PIHPS). This research uses the neural network method of the Backpropagation algorithm, which uses several architectural models, and the results of this test will yield the best accuracy value.
Analisis Algoritma Analytic Network Process (ANP) Dalam Pemilihan Material Furniture Pada Interior Rumah Tinggal Fadilla Anissa; Agus Perdana Windarto; M Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.39

Abstract

The purpose of this research is to recommend furniture materials in the interior of a residential house. In this study, the authors used a decision support system technique using the Analytic Network Process (ANP) algorithm. The research data source is by conducting interviews and giving questionnaires to furniture users in Pematangsiantar City. In the selection of furniture materials, the author uses five assessment criteria, among others: Quality (C1), Design (C2), Price (C3), Material Maintenance (C4), Room Arrangement (C5). In this study, the alternatives used as samples are Solid Wood (A1), Particle Wood (A2), Plywood Wood (A3), MDF Wood (A4), and Teakblock Wood (A5). From the study results using the Analytic Network Process (ANP) technique, it was found that from the five alternatives selected, obtained A1 became the best recommendation with a value of 0.12. It is hoped that this research can provide input to the public, especially in Pematangsiantar City, in choosing furniture materials to create a comfortable and ideal residence
Co-Authors Agus Perdana Windarto Deni Saputra Fadilla Anissa M Safii