Dewi, Krishnanti (2018) Prediksi Indeks Harga Konsumen (IHK) Kelompok Perumahan, Air, Listrik, Gas Dan Bahan Bakar Menggunakan Metode Support Vector Regression. Sarjana thesis, Universitas Brawijaya.
Abstract
Salah satu indikator yang paling sering digunakan untuk mengukur tingkat inflasi adalah Indeks Harga Konsumen (IHK). Prediksi indeks harga konsumen kelompok perumahan, air, listrik, gas dan bahan bakar sangat diperlukan untuk mengetahui indeks harga di masa yang akan datang sehingga dapat mempermudah pihak-pihak terkait dalam mengambil keputusan untuk menghindari terjadinya inflasi. Prediksi yang dilakukan pada penelitian ini menggunakan metode Support Vector Regression (SVR). Tahapan metode SVR yang dilakukan meliputi normalisasi data, menghitung matriks Hessian dengan menggunakan fungsi kernel Radial Basis Function (RBF), melakukan proses sequential learning, menghitung fungsi regresi untuk mendapatkan hasil prediksi dan melakukan evaluasi hasil prediksi dengan metode Mean Absolute Percentage Error (MAPE). Data yang digunakan sebanyak 72 data historis dari bulan Januari 2011 – Desember 2016 dari website resmi Bank Indonesia (www.bi.go.id). Hasil pengujian yang dilakukan terhadap prediksi indeks harga konsumen kelompok perumahan, air, listrik, gas dan bahan bakar menggunakan metode SVR didapatkan nilai MAPE minimum sebesar 2,399% dengan nilai parameter a = 50; y = 1; cLR = 0,0005; e = 0,0005; C = 1000; jumlah data training 36 dan 12 data testing serta iterasi sebanyak 100. Rata-rata hasil prediksi yang diperoleh adalah sebesar 112,19605 dengan rata-rata selisih antara data aktual dengan hasil prediksi sebesar 1,52645. Nilai MAPE yang dihasilkan < 10% sehingga dapat dikategorikan sangat baik untuk memprediksi indeks harga konsumen kelompok perumahan, air, listrik, gas dan bahan bakar.
English Abstract
One of the most commonly used indicators to measure the inflation rate is Consumer Price Index (CPI). Prediction of consumer price index group housing, air, electricity, gas and fuel groups is needed to know the price index in the future so that it can facilitate the parties involved in taking the decision to avoid inflation. In this research, prediction were performed with Support Vector Regression (SVR) method. The stages of the SVR method include normalization of data, calculates Hessian matrix by using Radial Basis Function (RBF) kernel function, sequential learning process, calculate the regression function to get predicted results and evaluates predicted results with Mean Absolute Percentage Error (MAPE). The data that used are 72 historical data, recorded from January 2011 – December 2016 from the official website of Bank Indonesia (www.bi.go.id). The result of the test on the forecasting consumer price index of housing, water, electricity, gas and fuel using SVR method obtained MAPE minimum of 2.399% with parameter value σ = 50; λ = 1; cLR = 0.0005; ε = 0.0005; C = 1000; Number of training data 36 and testing data 12 and 100 iterations. The average result of forecasting is 112.19605 with the average difference between actual data with forecasting result 1.52645. The result of MAPE value is <10% that can be categorized as very well for prediction of consumer price index group housing, water, electricity, gas and fuel.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2018/168/051801155 |
| Uncontrolled Keywords: | Prediksi, Indeks Harga Konsumen (IHK), Support Vector Regression (SVR), Radial Basis Function (RBF), Mean Absolute Percentage Error (MAPE) |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data > 005.1 Programming |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Yusuf Dwi N. |
| Date Deposited: | 28 May 2018 02:14 |
| Last Modified: | 26 Oct 2021 09:01 |
| URI: | http://repository.ub.ac.id/id/eprint/11140 |
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