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All Journal Generation Journal Joutica : Journal of Informatic Unisla
Muhammad Hasan Wahyudi
Universitas Islam Lamongan
Computer Science & IT Control & Systems Engineering

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IMPLEMENTASI ALGORITMA BACKPROPAGATION UNTUK MEMPREDIKSI JUMLAH PENGUNJUNG WISATA MUSIUM (STUDI KASUS DI MUSIUM SUNAN DRAJAT) Muhammad Hasan Wahyudi; Purnomo Hadi Susilo
Joutica Vol 6, No 1 (2021): Jurnal Teknik Informatika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.9 KB) | DOI: 10.30736/jti.v6i1.518

Abstract

Metode peramalan dalam teknologi komputasi sangatlah beragam, beberapa metode yang ada antara lain Peramalan ARIMA, Adaptive Neuro-Fuzzy Inference System (ANFIS), dan Jaringan Saraf Tiruan (JST). Pada artikel ini menyampaikan tentang usaha sebuah penelitian dengan tujuan untuk menerapkan dan mengetahui kinerja jaringan saraf dalam memprediksi jumlah pengunjung wisata museum (studi kasus di musium Sunan Drajat Lamongan). Metode yang digunakan adalah Matlab yang digunakan untuk menganalisis sebuah data yang kemudian dibentuk sebuah arsitektur jaringan terbaik aktif meramalkan jumlah pengunjung musium Sunan Drajat dengan skema 2-6-1 (2 neuron masukan, lapisan tersembunyi 6 neuron, satu neuron output) dengan nilai MSE terkecil 0,00000000277. Nilai MSE selama pelatihan sebesar 7858.75 sedangkan pada saat pengujian di 5.309.807.667. Kesalahan rata-rata hasil simulasi peramalan jumlah wisatawan ke musium Sunan Drajat dalam periode dari Maret hingga Mei 2019 sebesar 9,5%.
The Application of The C4.5 Algorithm Method Calculation The Number of Sales of Paving Production on CV. SR Lamongan Agus Setia Budi; Muhammad Hasan Wahyudi
Generation Journal Vol 10 No 2 (2026): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v10i2.27766

Abstract

Paving production is essential for ensuring proper road infrastructure for the community. The amount of paving demand in each month is uncertain, so it is challenging for company owners to maintain optimal inventory levels to maximize profits. The purpose of this research is to design a decision support system (SPK) to help company owners determine sales decisions in the future and make it easier to decide whether or not the paving sales are in demand. The method used in this study is the C4.5 Algorithm method. From the results of this study, it was found that the C4.5 Algorithm method is the most appropriate method in determining sales decisions in the next period. The sample used is data from CV. SR Lamongan has been in sales for the last 2 years. There are 25 paving production data used for the sample. From there, the recommended method in calculating sales in the following year can be obtained, namely using the C4.5 Algorithm method due to its higher accuracy rate, achieving up to 76%.
Co-Authors Agus Setia Budi Purnomo Hadi Susilo, Purnomo Hadi