Record Details

Konstruksi Forecasting System Multi-Model untuk pemodelan matematika pada peramalan Indeks Pembangunan Manusia Provinsi Nusa Tenggara Barat

Register: Jurnal Ilmiah Teknologi Sistem Informasi

View Archive Info
 
 
Field Value
 
Title Konstruksi Forecasting System Multi-Model untuk pemodelan matematika pada peramalan Indeks Pembangunan Manusia Provinsi Nusa Tenggara Barat
 
Creator Sucipto, Lalu
Syaharuddin, Syaharuddin
 
Subject Exponential Smoothing; Forecasting System Multi-Model; FSM; Human Development Index; IPA; Indeks Pembangunan Manusia; mathematical model; NTB; Nusa Tenggara Barat; pemodelan matematika; West Nusa Tenggara
 
Description Penelitian ini bertujuan untuk mengembangkan produk Forecasting System Multi-Model (FSM) guna menentukan metode terbaik dalam sistem peramalan (forecast) dengan mengkonstruksi beberapa metode dalam bentuk Graphical User Interface (GUI) Matlab dengan menghitung semua indikator tingkat akurasi guna menemukan model matematika terbaik dari data time series pada periode tertentu. Pada tahap simulasi, tim peneliti menggunakan data Indeks Pembangunan Manusia (IPM) Provinsi Nusa Tenggara Barat (NTB) tahun 2010-2017 guna memprediksi IPM NTB tahun 2018. Adapun metode yang diuji adalah Moving Average (SMA, WMA dan EMA), Exponential Smoothing Method (SES, Brown, Holt, dan Winter), Naive Method, Interpolation Method (Newton Gregory), dan Artificial Neural Network (Back Propagation). Kemudian model dievaluasi untuk melihat tingkat akurasi masing-masing metode berdasarkan nilai MAD, MSE, dan MAPE. Berdasarkan hasil simulasi data dari 10 metode yang diuji diketahui bahwa metode Holt paling akurat dengan hasil prediksi tahun 2018 sebesar 67,45  dengan MAD, MSE, dan MAPE berturut-turut sebesar 0,22654; 0,075955 dan 0,34829.   The purpose of this research is to develop a product was called Forecasting System Multi-Model (FSM) to determine the best method in the forecasting system by constructing several methods in the form of Graphical User Interface (GUI) Matlab. It was done by all indicator accuration to find the best mathematical model of time series data in a certain period. In the simulation phase, this research used the Human Development Index (HDI) data of West Nusa Tenggara (NTB) Province in 2010 - 2017 to predict the HDI data of NTB in 2018. The methods tested were Moving Average (SMA, WMA and EMA), Exponential Smoothing Method (SES, Brown, Holt, and Winter), Naive Method, Interpolation Method (Newton Gregory), and Artificial Neural Network (Back Propagation). Then the models/methods were evaluated to see the level of accuracy of each method based on the value of MAD, MSE, and MAPE. Based on data simulation result from 10 tested method known that Holt method is most accurate with prediction result of 2018 equal to 67,45 with MAD, MSE, and MAPE respectively equal to 0.22654, 0.075955 and 0.34829.
 
Publisher Information Systems - Universitas Pesantren Tinggi Darul Ulum
 
Contributor LPPM UIN Mataram
 
Date 2018-07-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://journal.unipdu.ac.id/index.php/register/article/view/1263
10.26594/register.v4i2.1263
 
Source Register: Jurnal Ilmiah Teknologi Sistem Informasi; Vol 4, No 2 (2018): July; 114-124
Register: Jurnal Ilmiah Teknologi Sistem Informasi; Vol 4, No 2 (2018): July; 114-124
2502-3357
2503-0477
10.26594/register.v4i2
 
Language eng
 
Relation https://journal.unipdu.ac.id/index.php/register/article/view/1263/pdf
https://journal.unipdu.ac.id/index.php/register/article/downloadSuppFile/1263/84
 
Rights Copyright (c) 2018 Register: Jurnal Ilmiah Teknologi Sistem Informasi
http://creativecommons.org/licenses/by/4.0