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Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Published by Universitas Bina Bangsa
ISSN : 27757463     EISSN : 27757455     DOI : https://doi.org/10.46306/bay
Core Subject : Economy, Education,
Economics, Econometrics & Finance Mathematics
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika adalah Jurnal Ilmiah yang terbit secara daring pada bulan MARET dan SEPTEMBER. untuk menyebarluaskan hasil-hasil penelitian dalam bidang Statistika, Ekonometrika dan sub ilmu statistika lainnya.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 74 Documents
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IMPLEMENTATION OF HOLT-WINTER METHOD TO FORECAST FOOD SUB-GROUP OF CONSUMER PRICE INDEX IN SERANG CITY Febrianti, Tanti; Mahuda, Isnaini; Rahmatullah, Asep; Mursyidah, Himmatul
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 2 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i2.85

Abstract

Serang City is belong in 90 inflation cities in Indonesia and first ranking in the city with the highest inflation rate in Banten Province in 2021. Consumer Price Index (CPI)is an index used to measure the rate of inflation/deflation. The one of CPI category is Food. This research aims to predict the value of the CPI at COICOP of Food in Serang City after pandemic of Covid-19. The data used is secondary CPI data for the Food sub-group in Serang City for the period January 2020 to June 2022 obtained from the official website of the Central Statistics Agency (BPS). In this research, to predict the CPI of the Food Sub-group in Serang City using the Holt-Winter method. Results of the research showed that the CPI data pattern of the Food Sub-group in Serang City had a Multiplicative Holt-Winter pattern with seasonal length is 12. The accuracy of the forecasting value was carried out by calculating the average MAPE and MSE errors. The optimal parameter weight of Holt-Winter Multiplicative method obtained alpha is 0.5, gamma is 0.3 and delta is 0.1. Forecasting using Holt-Winter Multiplicative method obtained a significant increase in the CPI value from July to December 2022 with the MAPE accuracy value is 0.72261 and the MSE is 1.33681
ANALISIS CLUSTER INDEKS PEMBANGUNAN MANUSIA DENGAN MENGGUNAKAN METODE HIERARKI PADA KABUPATEN/KOTA DI PROVINSI BANTEN Sukmawati, Sri; Alam, Tubagus Bakhrul; Rahmatullah, Asep; Abdullah, Syarif; Sukandar, Rani Septiani
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 2 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i2.86

Abstract

A high Human Development Index (HDI) greatly determines the ability of the population to absorb and manage sources of economic growth, both in relation to technology and institutions as an important means to achieve economic growth. The purpose of this study is to group districts/cities in Banten Province and find out the characteristics of each group based on the Human Development Index indicators. HDI is a composite index that shows the achievement of successful human development in a region. The research data used is secondary data with the population of all districts/cities in Banten Province. Cluster analysis is a technique used to group objects into different groups. The results of the study were obtained in 2 clusters using the single linkage, average linkage, and complete linkage methods which included the first cluster, namely Tangerang City, Tangerang Regency, Serang City, Pandeglang Regency, Serang Regency, Lebak Regency, and Cilegon City, while the second cluster was Tangerang City and South Tangerang City
IMPLEMENTATION OF ARIMA METHOD TO FORECAST CPI FOR COICOP OF FOOD, BEVERAGE AND TOBACCO IN NEW NORMAL PERIOD Mahuda, Isnaini; Rahmawati, Septi Dwi; Sukmawati, Sri; Abdullah, Syarif
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 2 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i2.87

Abstract

CPI is one of the economic indicators that can provide information on development of prices for goods and services paid by consumers or the society, especially urban societies. CPI is usually used to measure price changes, but not to measure the price level. In addition, the CPI also can be used as a benchmark to determine inflation or deflation in a certain area. CPI value after the COVID-19 pandemic is the object to be predicted. There are 11 category in the CPI. This category is named COICOP which one of it is food, beverage and tobacco. The purpose of this research was to determine the ARIMA model to forecast the CPI value in the COICOP of food, beverage and tobacco in Banten Province. The data used is CPI data of COICOP for food, beverage and tobacco in Banten period January 2019 to April 2022. Based on these data obtained several prospective ARIMA models that passed the model diagnostic stage. The Models are ARIMA (0.3,1), ARIMA (1,3,0) and ARIMA (2,3,0) with MSE 1.1294, 1.9496 and 1.2484. The ARIMA (0.3.1) model was chosen because it has the smallest MSE value of 1.1294. Forecasting using the ARIMA (0.3.1) model obtained a significant increase in the CPI value from May to December 2022
CLUSTER ANALYSIS USING HIERARCHIC METHOD BASED ON HUMAN DEVELOPMENT INDICATORS OF DISTRICT/CITY IN BANTEN PROVINCE Muhartini, Ajeng Afifah; Mahuda, Isnaini; Sukmawati, Sri; Agusutrisno, Agusutrisno
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 2 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i2.88

Abstract

Human Development Index is a measure of human development achievement based on a number of basic components from quality of life. Cluster analysis is a technique used to categorize objects into different groups from another groups. The purpose of this research is to classify districts/cities based on indicators of Human Development Index (HDI) with the hierarchic method in Banten Province. This research was conducted to determine the characteristics of each group based on HDI indicators in Banten Province. The data used is secondary data with the population are all regencies/cities in Banten Province which includes Tangerang City, South Tangerang City, Serang Regency, Pandeglang Regency, Lebak Regency, Tangerang Regency, Cilegon City and Serang City. Cluster analysis was carried out using single linkage, average linkage, and complete linkage methods. The results of the study obtained 2 clusters in each of these methods with different characteristics. The first cluster is a cluster with characteristics of District, while the second cluster is a cluster with characteristics of City. The conclusion from this research is that the characteristics of each first cluster have a lower average value than the second cluster

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