Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Leibniz: Jurnal Matematika Jurnal Sains dan Teknologi
Puce Angreni
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Dentistry Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Application of ARIMA to Curly Red Chili Prices in Bengkulu City Melda Juliza; Puce Angreni
INSOLOGI: Jurnal Sains dan Teknologi Vol. 2 No. 2 (2023): April 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v2i2.1871

Abstract

Curly red chili in Bengkulu City often experiences price fluctuations from time to time. These price fluctuations are sometimes very extreme, causing public unrest both for food processing industry entrepreneurs and for daily household needs. Therefore, this study uses time series techniques to predict the price of curly red chili in Bengkulu City. This study discusses chili price forecasting using the Box-Jenkins ARIMA model based on curly red chili price data in Bengkulu City from 03 October 2022 to 28 February 2023. This research aims to look at the accuracy of the best model for curly red chili prices in Bengkulu city for the ARIMA model based on ACF & PACF criteria with autocorrelation coefficient values, and the smallest AIC criteria with the auto.arima function in R software. Next, forecast the price of curly red chili in Bengkulu City for the next period with the ARIMA model based on the best criteria obtained. Based on the ADF test, it can be seen that the data is not stationary so the data differencing process is carried out. The analysis results show that the best ARIMA model for curly red chili price data in Bengkulu City is the automatic ARIMA model with the smallest AIC criteria using the auto.arima function with the value of RMSE is 4197.7. The ARIMA model that is formed is the ARIMA (1,1,1) model. Next, the results of forecasting the price of curly red chili for Bengkulu City obtained based on the ARIMA (1,1,1) on 01 March 2023 is Rp 41,700.
Comparison of Geographically Weighted Regression with Adaptive Gaussian and Bisquare Kernel on Open Unemployment Rate in Riau Islands Widya Reza; Buan, Febrya Christin Handayani; Puce Angreni
Leibniz: Jurnal Matematika Vol. 6 No. 01 (2026): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v6i01.705

Abstract

Regression analysis is an analysis to determine the relationship and influence of independent variables on the dependent variable. If the data has a spatial relationship, this analysis has the potential to produce a less accurate model because the regression analysis ignores the influence of the location. One of the data indicated to have a spatial relationship is the open unemployment rate. One spatial analysis that can be used to accommodate spatial relationships is the Geographically Weighted Regression (GWR) model. In the GWR model, a spatial weighting matrix is required whose size depends on the proximity between locations. In this study, two spatial weighting matrix were used: Adaptive Gaussian Kernel and Adaptive Bisquare Kernel. Based on the results of the analysis, it is known that the factors influencing the open unemployment rate in the Riau Islands in 2024 at several locations are the human development index, Economic Growth, and Minimum Wages by Regency/City. Based on the R2 value and AIC value, the best spatial weight matrix produced is the Adaptive Bisquare Kernel weighting function with an R2 value of 93.32% and an AIC value of 15.2835.
Co-Authors Febrya Christin Handayani Buan Melda Juliza Widya Reza