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All Journal Jurnal Ekonomi Kuantitatif Terapan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Sigit Budiantono
PKN-STAN
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics

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IMPLEMENTATION OF SEM-PLS MODELING ON THE IMPACT OF THE REGIONAL COMPETITIVENESS INDEX ON SOCIOECONOMIC MACRO VARIABLES Pardomuan Robinson Sihombing; Ade Marsinta Arsani; Dyah Purwanti; Sigit Budiantono
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 1 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i1.250

Abstract

The Regional Competitiveness Index (RCI) is one of the essential indicators to measure the ability of a region to compete with other regions in the economic, social, and environmental fields. Increasing regional competitiveness is one of the goals desired by every local government to encourage economic growth and community welfare. This study aims of the research to find out the relationship between the Regional Competitiveness Index (RCI) and socioeconomic macroeconomic variables such as the growth of Gross Regional Domestik Bruto (GRDP), Human Development Index (HDI), Foreign Investment, Domestic Investment, Regional Income and poverty rates in Indonesia in 2022 in Indonesia. The data used are publication data from the National Innovation Research Agency (BRIN) and the Statistic Indonesia (BPS) in 2022. The analysis model used is the PLS Structural Equation Model (SEM) model with SmartPLS software. The results showed that RCI significantly positively affected HDI, GRDP growth, Domestic Investment, Foreign Investment, and Regional Income. On the other hand, RCI significantly negatively affects the percentage of poor people. A comprehensive and targeted policy is needed so that the Regional Saiang Power Index continues to increase. In addition, supervision is needed related to programs that have been running related to regional competitiveness
Determinants of Poverty in East Java after the Covid-19 Pandemic Dyah Purwanti; Sigit Budiantono; Nurhidayati Nurhidayati; Pardomuan Robinson Sihombing; Ade Marsinta Arsani
Jurnal Ekonomi Kuantitatif Terapan 2023: Vol. 16, No. 2, Agustus 2023 (pp.187-360)
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEKT.2023.v16.i02.p06

Abstract

The Covid-19 pandemic has significantly impacted the economy both nationally and nationally. Economic activity slowed down, many businesses closed their businesses, and there was an increase in the poor. The government is conducting fiscal interventions to overcome the impact of the pandemic both on supply and demand. The intervention is expected to keep the economy growing despite being thin. East Java Province had achievements in reducing poverty until the end of 2019; after the pandemic, poverty increased significantly at the end of 2021. This condition is challenging for the Provincial Government and the City / Regency Government in East Java. Therefore, this study analyzes the determinants of poverty in East Java after the pandemic. Data was sourced from the Statistic Indonesia of East Java for 2018-2021. Using a regression of panel data (fixed effect model), we found that the human development index reduced poverty. On the contrary, the Covid pandemic, this ratio, and economic growth positively impact poverty. The implications of the findings suggest the need for comprehensive economic and macro-social policies so that the poverty rate in East Java can be reduced.
PREMIUM RICE PRICE MODELING USING ARIMA MODEL Pardomuan Robinson Sihombing; Ade Marsinta Arsani; Mohamad Arif Kurniawan; Triana Mauliasih Aritonang; Sigit Budiantono; Nurhidayati Nurhidayati
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 3 No. 2 (2023): 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.v3i2.59

Abstract

Rice is a food commodity that has a vital role in meeting the basic food needs of most Indonesian people. Therefore the price of rice significantly impacts the availability, accessibility, and stability of the people's social, economic, and welfare. This study aims to model large prices and conduct nighttime with the ARIMA method. The ARIMA model used based on ACF and PACF criteria is ARIMA (1,1,0). ARIMA modeling (1,1,0) satisfies all assumptions of normality, non-heteroskedastic, non-autocorrelation, and model stability. The model's performance is also good in forecasting with MAPE below 10 percent. Based on forecasting results, premium rice prices continue to increase. Implementing this result requires the government to anticipate rice price increases with comprehensive policies and remain calm so that large prices remain stable
KOMPARASI PEMODELAN REGRESI OLS GAUSSIAN, BETA DAN REGRESI FRACTIONAL PADA DATA RASIO Pardomuan Robinson Sihombing; Ade Marsinta Arsani; Ni Komang Semara Yanti; Putu Pande Wahyu Diatmika; Nurhidayati Nurhidayati; Sigit Budiantono
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 3 No. 2 (2023): 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.v3i2.61

Abstract

The Public Health Development Index (PHDI) is an indicator that describes health problems and plays a role in efforts to increase long and healthy life expectancy. This study aims to compare PHDI modeling in 35 City Districts of Central Java Province using Gaussian-based regression (OLS), beta regression and fractional regression. The independent variables used are the percentage of poor people and the percentage of households accessing proper sanitation. Data is sourced from the Ministry of Health and Central Java Statistics Agency. All three models gave the same results for both simultaneous and partial tests in modeling PHDI modeling cases. Fractional regression models provide the best results with the smallest error value criteria (AIC and BIC). The percentage of poor people has a significant negative effect on IPKM while the percentage of proper sanitation has a significant positive effect on PHDI. Based on these results, it is expected that policy makers can provide comprehensive and targeted policies in improving PHDI in Indonesia
IMPLEMENTATION OF BINARY LOGISTIC ANALYSIS ON DETERMINANTS OF MALARIA STATUS Sigit Budiantono; Dyah Purwanti; Nurhidayati Nurhidayati; Pardomuan Robinson Sihombing; Ade Marsinta Arsani
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.307

Abstract

Malaria is a disease transmitted through mosquitoes; malaria is still one of the endemic diseases in Eastern Indonesia. This study aims to determine the factors that affect malaria status. The independent variables used were region, gender, insect repellent, sowing larvicide powder, draining the bathtub, and mosquito nets. The data comes from the Basic Health Research Report (Riskesdas) 2018. The analysis method used is binomial regression / binary logistics. Based on research states that together all independent variables have a significant effect on a person's malaria status. Partially, the chances of rural status, male sex, not using insect repellent, not using larvicide powder, not draining bathtubs, and not wearing mosquito nets are greater than other categories of malaria status. Therefore, self-awareness of individuals and communities is needed in striving for cleanliness and personal health
Co-Authors Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Dyah Purwanti Mohamad Arif Kurniawan Ni Komang Semara Yanti Nurhidayati Nurhidayati Pardomuan Robinson Sihombing Putu Pande Wahyu Diatmika Triana Mauliasih Aritonang