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Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
ISSN : 27757463     EISSN : 27757455     DOI : https://doi.org/10.46306/bay
Core Subject : Economy, Education,
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.
Articles 74 Documents
APLIKASI KURVA PERTUMBUHAN LATEN PADA DATA INDEKS PEMBANGUNAN GENDER DI JAWA TIMUR Pardomuan Robinson Sihombing; Ade Marsinta Arsani; I Gede Heprin Prayasta; Ida Ayu Candrawati; Nurhidayati Nurhidayati; Sigit Budiantono
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (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.v4i1.75

Abstract

In the context of human development, gender equality is considered an important basic dimension, and one way to measure it is with the achievement of the Gender Development Index (GDI). East Java is one of the provinces in Indonesia whose GDI value consistently increases from year to year. This study aims to model GDI growth with latent growth models. The data used was sourced from the Statistics Indonesia of East Java with the research unit of regency in East Java in the 2017-2021 period. The results obtained were sustainable GDI growth in East Java City District. Modelling in latent growth curve method showed that the variation in growth was explained by 99 percent over the 5-year study period. Implementation in this study requires comprehensive and targeted efforts from policy makers in maintaining and increasing IPG growth in East Java
ANALISIS KLASTER DENGAN METODE K-MEANS BERDASARKAN USIA WARGA YANG DIVAKSIN COVID-19 DI KELURAHAN GROGOL SELATAN Fauziyah Fauziyah; Choirul Basir
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (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.v4i1.76

Abstract

COVID-19 was declared a pandemic because this virus spread throughout the world. In the context of tackling the COVID-19 virus, the Government urges the public to get vaccinated against COVID-19. Therefore, the government mobilized PKK cadres and Dasawisma cadres in collecting data on vaccinations in their respective areas. Vaccine data collection is carried out to find out the number of residents who have been vaccinated and who have not been vaccinated based on age grouping. In an effort to provide vaccinations so that there is no accumulation of residents and adjusted by the vaccine quota available at the location of the vaccine administration. Therefore, the use of the K-Means Cluster Analysis method was used to divide the data into different groups and the researchers implemented the K-Means Clustering Analysis method using manual calculations and using python language with the Google Colaboratory. The attribute used in this study is the number of residents who have been vaccinated and have not been vaccinated against COVID-19. The best results in manual calculations and Python language are 2 clusters. The most dominant cluster is Cluster 0 which consists of 8 members. The government is expected to increase the supply of vaccines because there is a lot of interest in vaccinations, especially booster vaccines
PERBANDINGAN HASIL ANALISIS CLUSTER K-MEANS DAN K-MEDOIDS UNTUK PEMETAAN MUTU SMK Intan Juliana Panjaitan; Tiya Wulandari; Budi Susetyo
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (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.v4i1.77

Abstract

The quality of education in a country is one indicator of the country's progress. Indonesia has formulated an assessment of the quality of education using the National Education Standards (NES). To fulfill the SNP, school accreditation is an obligation that must be fulfilled by all intuitions. The results of the accreditation assessment can be grouped into several groups according to their respective categories. To determine the number of clusters formed, an analysis using the K-Means and K-Medoids methods can be performed with 2 clusters formed. Cluster 1 namely the Provinces of Aceh, Banten, West Kalimantan, Central Kalimantan, North Kalimantan, West Nusa Tenggara, Central Nusa Tenggara, West Sulawesi and Central Sulawesi, and Cluster 2 namely the Provinces of Bali, Bengkulu, DI Yogyakarta, DKI Jakarta, Gorontalo, Jambi, Central Java, East Java, South Kalimantan, East Kalimantan, Bangka Belitung, Riau Archipelago, Lampung, Maluku, North Maluku, Papua, West Papua, Riau, South Sulawesi, Central Sulawesi, North Sulawesi, West Sumatra, South Sumatra, North Sumatra
PERAMALAN HASIL PRODUKSI PADI DI KABUPATEN LAMONGAN MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING Asyiqqotus Saidah; Saiful Bahri
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (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.v4i1.78

Abstract

Food crops are an agricultural sub-sector that has a high contribution to the economy of Lamongan Regency. The increase in population growth rate affects the demand for food. In this study, the double exponential smoothing approach is used to forecast in order to avoid food shortages, especially rice. This method requires two parameters (α and β). This study uses data on rice production from the period 2009 to 2022. The results show that the best parameter values are α = 0,9 and ꞵ = 0,1 with a MAPE value of 11,72%. Based on the MAPE value, it is known that the forecasting model is good
PENGELOMPOKKAN TINGKAT PENYAKIT PADA SETIAP DAERAH DI JAWA TIMUR MENGGUNAKAN K-MEANS Danang Abimanyu Iqbal Mahendra
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (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.v4i1.79

Abstract

Tuberculosis, also known as TB, is an infectious disease caused by the bacteria Mycobacterium tuberculosis. The main symptoms of pulmonary tuberculosis include a persistent cough lasting for more than three weeks, sometimes accompanied by bloody sputum, fever, night sweats, fatigue, and weight loss. According to data from the Indonesian Ministry of Health, in 2020, there were approximately 372,851 newly diagnosed cases of TB in Indonesia. The objective of this study is to determine the prevalence of the disease in each region. In this study, clustering was performed on each variable, namely TB, pneumonia, leprosy, and malaria. The clustering resulted in three cluster categories. Cluster 1 consists of the following areas: Malang, Jember, Sidoarjo, Bojonegoro, Gresik, and Surabaya (city). Cluster 2 represents provinces with a medium number of cases and includes Lumajang, Banyuwangi, Situbondo, Probolinggo, Jombang, Pasuruan, Tuban, and Lamongan. Cluster 3 consists of Pacitan, Ponorogo, Trenggalek, Tulungagung, Blitar, Kediri, Bondowoso, Mojokerto, Nganjuk, Madiun, Magetan, Ngawi, Kediri (city), Blitar (city), Malang (city), Probolinggo (city), Pasuruan (city), Mojokerto (city), Madiun (city), and Batu (city)
PENGARUH TINGKAT PENGANGGURAN, PERTUMBUHAN PENDUDUK, DAN IPM TERHADAP TINGKAT KEMISKINAN DI PROVINSI JAWA TENGAH Dana Putra, Marshell Bahreiza; Furqon, Imahda Khoiri
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.v4i2.80

Abstract

One of the socioeconomic problems that every region is responsible for is poverty. Poverty is a social problem that has existed for a long time and is difficult to eradicate until now. So what can affect poverty and how to influence it. The majority of developing countries, including Indonesia, experience poverty. This research is quantitative research, with data analysis techniques, namely multiple linear regression analysis. The data used in this study are secondary data sourced from bps. The results showed that the unemployment rate has a negative effect on poverty, population growth has a negative effect on poverty, and HDI has a negative effect on poverty. Simultaneously, the three variables have no effect and are not significant on poverty
ANALISIS PENGARUH CONSUMER PRICE INDEX DAN PENDIDIKAN TERHADAP PERTUMBUHAN EKONOMI DI ASIA TIMUR DAN PASIFIK Khairunnisa, Nabila
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.v4i2.81

Abstract

This study aims to analyze the factors influencing economic growth in East Asia and the Pacific. The data used was taken in 2012-2022. A multiple linear regression model with the development of a model using the Ordinary Least Square (OLS) method was used to analyze the relationship between economic growth and independent variables such as the consumer price index (CPI) and education. The results of the study show that all independent variables have a positive and significant influence on the dependent variable, namely economic growth
IMPLEMENTASI APPROXIMATE BAYESIAN COMPUTATION-SEQUENTIAL MONTE CARLO MENGGUNAKAN DATA WABAH CAMPAK 2010 DI MALAWI Sektiaruni, Arfiah Kania; Dwi Rahmi, Salsabila; Nurfatimah, Dinda Khamila; Hafizhoh, Zulfa; Pratiwi, Oktavia Galih; Sulistiyowati, Anis
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.v4i2.82

Abstract

Infectious disease is an infectious condition caused by the proliferation of microorganisms that can be transmitted to other healthy individuals. One of the infectious diseases is measles. Measles is an infectious disease caused by a highly contagious and potentially fatal virus. Measles continues to be one of the leading causes of child death, particularly in Sub-Saharan Africa and South Asia. In 2010, there was a major measles outbreak that caused 134,000 cases and 304 deaths in Malawi. This study aims to estimate parameter values ​​in the 2010 measles outbreak model in Malawi using the ABC-SMC method. The purpose of estimating parameter values ​​is to validate and measure the predictive accuracy of the model. The ABC-SMC algorithm provides a computationally efficient estimation procedure compared to the ABC rejection algorithm. This method can be used for very complex models and does not require the requirement of a likelihood function. The results obtained from this study show that the ABC-SMC method can be used effectively to model the spread of infectious measles with age structure, the parameter estimation results show that this method can replicate the actual population distribution with high accuracy, and through five generation iterations it succeeded in producing more accurate parameter estimates
EKONOMI YANG INKLUSIF DAN BERKELANJUTAN: ANALISIS KEUANGAN DAERAH, KEMISKINAN, DAN TEKNOLOGI UNTUK MEWUJUDKAN SDGS 2030 Herman, Nur Ashilah Raihanah; Muchtar, Masruri; Sihombing, Pardomuan Robinson
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.v4i2.83

Abstract

The Sustainable Development Goals (SDGs) emerged as a universal commitment to address social issues, prioritize inclusive economic growth, and reduce inequality. Regional governments are the main pillar in achieving the 2030 SDGs in addition to other factors, namely GDP per capita and economic inclusivity by emphasizing regional equity and increasing local independence. This study analyzes the impact of regional finance, poverty, and technology on economic growth in order to realize an inclusive and sustainable economy. The data is sourced from the Central Statistics Agency and the Directorate General of Financial Balance for 2020-2022 which covers all provinces in Indonesia. Using a fixed effect model, the test results found that local income, profit-sharing funds, and technology had a positive impact on per capita economic growth, but poverty showed a negative influence. The implications of these findings show the need for a comprehensive study related to the implementation of fiscal decentralization and technology investment so that it can achieve the 8th goal of the 2030 SDGs
ANALISIS KESEJAHTERAAN RAKYAT PROVINSI BANTEN DENGAN MENGGUNAKAN METODE REGRESI LOGISTIK BINER Megasari, Anggita; Sukmawati, Sri; Rahmatullah, Asep; Handayani, Yolla Sukma; 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.v4i2.84

Abstract

People's welfare is the development target of every region in Indonesia. Banten Province ranks 3rd in the level of people's welfare on the island of Java. So that a factor analysis is needed to find out the influence of the people's welfare. This study aims to find out the binary logistic regression model based on factors that significantly affect the level of people's welfare in Banten Province and to find out how much the classification accuracy of the model obtained. The type of research used is quantitative research with the population of all people in Banten Province by looking at household characteristics, while the sample of 380 is secondary data from BPS Banten Province based on the results of Susenas activities with the Systematic Random Sampling technique. The results of the research obtained from this study are three factors that affect the level of people's welfare, namely the Head of Household Education factor (X3(2)) category of Junior High School Equivalent and the Head of Household Education factor (X3(3)) category of High School Equivalent and the Number of Household Members (X5(1)) category > 4 Members. The form of the binary logistic regression equation obtained is  with a model classification accuracy value of 89.7%, the classification accuracy obtained reaches > 50% which means that the binary logistic regression logit function is considered to be precise and quite good