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VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Published by Universitas Negeri Makassar
ISSN : -     EISSN : 26847590     DOI : http://dx.doi.org/10.35580/variansiunm26374
Core Subject : Economy, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics
VARIANSI: Journal of Statistics and Its application on Teaching and Research memuat tulisan hasil penelitian dan kajian pustaka (reviews) dalam bidang ilmu dasar ataupun terapan dan pembelajaran dari bidang Statistika dan Aplikasinya dalam pembelajaran dan riset berupa hasil penelitian dan kajian pustaka.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 4 Documents
 1 
Search results for , issue "Vol. 6 No. 03 (2024)" : 4 Documents clear
Peramalan Suhu Rata – Rata Kota Padang Panjang dengan Membandingkan Metode SARIMA dan Holt – Winter Additive Putri, Fadhira Vitasha; Ikhsan, Easbi; Fitri, Fadhilah
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm237

Abstract

Padang Panjang City, situated at an altitude of 650 to 850 meters above sea level and surrounded by high mountains, experiences significant temperature changes that affect various aspects of life such as public health, agriculture, and tourism. This study aims to forecast the monthly average temperature of Padang Panjang City from January 2017 to December 2023 by comparing SARIMA and Holt-Winters Additive forecasting methods. The results show that the SARIMA method, with an MSD value of 0.2206, is more accurate compared to the Holt-Winters Additive method, which has an MSD value of 0.29821. With the SARIMA model as the best method, the forecast indicates that the highest average temperature in Padang Panjang City will reach 23.1418 degrees Celsius in May 2024. These results are expected to provide a strong basis for planning and decision-making related to the temperature changes occurring in Padang Panjang City.
Penerapan Extreme Learning Machine (ELM) untuk Meramalkan Laju Inflasi di Indonesia Fahmuddin S, Muhammad; Annas, Suwardi; nurismi, Nur ismi
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm92

Abstract

Inflation is generally the tendency for the prices of goods and services to rise continuously. An artificial neural network (ANN) is an information processing model that closely resembles how an organism's memory system works, such as information transmission processes in the brain. Forecasting is the activity of determining future events based on past data. A time series is a set of observations that occur consecutively in the correct amount of time based on a time index. The data used in this study are Indonesian monthly inflation data. Extreme Learning Machine (ELM) is an artificial neural network approach that uses a single hidden layer feedforward neural network architecture (SLFN). The advantages of ELM over traditional learning algorithms are learning speed, improved generalization performance, and simplified implementation. An error value of RMSE of 0.1992215 was obtained based on the analysis performed using the Extreme Learning Machine (ELM) method.
Perbandingan Metode ARIMA dan Single Exponential Smoothing dalam Peramalan Nilai Ekspor Kakao Indonesia Fahmuddin S, Muhammad; Ruliana; Mustika M, Sitti Sri
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm373

Abstract

Indonesia is a country with an open economy, one of the sources of foreign exchange needed by a country with an open economy is exports. Cocoa is one of Indonesia's main export commodities that makes an important contribution to the country's economy, but the value of Indonesian cocoa exports fluctuates, that is there are inconsistent changes from time to time. The purpose of this study is to determine the results of forecasting the value of Indonesian cocoa exports, as well as to determine the best method for forecasting. This research compares the ARIMA and Single Exponential Smoothing methods to determine the best forecasting method. The best method is selected based on the smallest MAPE value. Based on the results of data analysis, the best forecasting model using the ARIMA method is the ARIMA (1, 0, 1) model, which has a MAPE value of 10.38060%. Meanwhile, the best forecasting model using the Single Exponential Smoothing method is with α = 0.16, which has a MAPE value of 10.92874%. So that the best method for forecasting the value of Indonesian cocoa exports is the ARIMA method.
Penerapan Analisis Regresi Nonparametrik Spline Truncated pada Pemodelan Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran Terbuka di Provinsi Jawa Barat Rais, Zulkifli; Ruliana; Mukhtazam Aqil Mukhtar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 03 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm199

Abstract

Unemployed is someone who has entered the workforce, but does not have a job and is looking for work, setting up a business, and who already has a job but has not yet started working. One indicator that can be used to measure unemployment is The Unemployment Rate. West Java Province is the province in first place with the highest unemployment rate in Indonesia. Based on BPS data, the unemployment rate in West Java Province in 2022 reaches 8.31%. The method that can be used to model factors that are thought to influence the unemployment rate in West Java Province in 2022 is nonparametric spline regression. The nonparametric spline regression method was used in this research because this method is very good at modeling data that has changing patterns at certain intervals. The aim of this research is to get the best model of the factors that influence the unemployment rate and find out what factors significantly influence the unemployment rate in West Java Province in 2022. Based on parameter significance testing, it was found that all the variables used, namely Labor Force Participation Rate, Percentage of Poor Population, District/City Minimum Wage, Government Expenditures, and Average Years of Schooling had a significant effect on TPT in West Java Province in 2022. The value of the determination coefficient obtained was 99.5%.

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