Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Limits: Journal of Mathematics and Its Applications
Adelia Sukma Dwiyanto
Unknown Affiliation
Computer Science & IT Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisis Nilai Inflasi Bulanan Indonesia Menggunakan Regresi Nonparametrik Estimator Kernel Azzah Nazhifa Wina Ramadhani; Adelia Sukma Dwiyanto; Nuzulia Anid; Muhammad Hafidzuddin Nahar; Dita Amelia
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 2 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

High levels of inflation are plaguing Indonesian society. Inflation occurs due to price increases as indicated by the increase in most expenditure group indices. This can lead to a higher poverty rate in Indonesia. This study aims to identify the best method that can be used to estimate Indonesia's monthly inflation value based on a nonparametric regression approach with a kernel estimator and analyze the results of predicting Indonesia's monthly inflation value for the next four months. The data used in this study is secondary data sourced from Bank Indonesia, with the variable used is the value of Indonesian inflation during the period January 2019 to July 2024. The collected data were analyzed using descriptive statistics and analytical statistics in the form of nonparametric regression with kernel estimators and predictions using kernel estimator and non-seasonal ARIMA methods. The results showed that triweight kernel regression was the best kernel function model with a minimum bandwidth value of 1.214, value of 99.990, MSE of 0.00016, and MAPE of 0.348%. The results of data prediction for the next thirteen months provide that triweight kernel estimator was better than non seasonal ARIMA method, with a MAPE value of 10.92%, so that the nonparametric regression method with the triweight kernel function is good or accurate in predicting data, which also can be used to analyze and predict Indonesia's monthly inflation data.
Co-Authors Azzah Nazhifa Wina Ramadhani Dita Amelia Muhammad Hafidzuddin Nahar Nuzulia Anid