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All Journal RAGAM: Journal of Statistics and Its Application
Fuad Muhajirin Farid
Program Studi Statistika Fakultas MIPA Universitas Lambung Mangkurat
Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health

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PERMODELAN REGRESI NONPARAMETRIK SPLINE TERHADAP INFLASI DI PROVINSI KALIMANTAN SELATAN Geofani Setiawan; Fuad Muhajirin Farid; Nur Salam
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7337

Abstract

Inflation is a condition of increasing prices continuously for a certain time. One of the factors thought to influence inflation, namely the Consumer Price Index (CPI), the Consumer Price Index (CPI) is an indicator that can be said to be important in determining the level of economic stability of a country. Seeing the relationship between the Consumer Price Index (CPI) and inflation, this study aims to explain how the influence and how the best model of the Consumer Price Index (CPI) on inflation in South Kalimantan Province uses Spline Nonparametric Regression. The use of the Spline Nonparametric Regression method in this study is because the data used has significant fluctuations so that it is estimated that the data is not normal. In the process, the Spline Nonparamteric Regression method is used to obtain the estimated regression curve through a data fitting approach. This method is also very suitable for use with data that changes frequently, spline is a model that has statistical, visual interpretation and has the ability to be generalized to complex and complex statistical models. The result of this research is that the best model is found at one knot point and the Consumer Price Index (CPI) has an effect on the inflation variable by 13.23 percent.Keywords:  Inflation, Consumer Price Index, Spline Nonparametric Regression 
PETA KENDALI MULTIVARIAT np irma irma; Dewi Anggraini; Fuad Muhajirin Farid
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7387

Abstract

In general, a production process requires the control of multiple quality characteristics (variables). Multivariate control charts can be used to control many quality attributes and identify the root cause of an out-of-control condition or signal. It was used in the production of Hexagon Bolt M16x75mm. However, research regarding the theory of multivariate control charts remains limited. The np multivariate control chart is obtained by combining the processes of parameter estimate, control limit determination, and out-of-control signal detection.  Keywords:  Control Charts, Multivariate np, Out of Conrol Signal.
PEMODELAN REGRESI DATA PANEL PADA TINGKAT PARTISIPASI ANGKATAN KERJA PEREMPUAN DI PROVINSI KALIMANTAN SELATAN Putri Norhikmah; Fuad Muhajirin Farid; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7383

Abstract

Women’s Labor Force Participation Rate (LFPR) is an indication that can shows how much participation of women in the process development. The purpose of this study is to provide an overview of LFPR women in the Province of South Kalimantan, explaining the expected variables influence on women’s LFPR in South Kalimantan Province and determine the best model. This research data is sourced from the Centra Statistics Agency of South Kalimantan Province with a time period of 2017-2020. Variable independen research, namely female workers, female residents who are still in school and taking care of the household, the average length of schooling for women, female population according to the highest education ever graduate from senior high school above, female household heads, status of married and unmarried women marriage, district/city minimum wage, human development index women and regional domestic income growth at constant prices while the dependent variable is female LFPR. The results of data analysis, can be conclude that the Fixed Effect Model as the best model of panel regression. Women’s LFPR in South Kalimantan Province by producing two recommendation with Fixed Effect Model an R-Squared in the first model of 99,40%.Keywords:  Women’s LFPR, Panel Data Regression, South Kalimantan
PEMODELAN REGRESI SPASIAL PADA ANGKA PARTISIPASI MURNI JENJANG PENDIDIKAN SMA SEDERAJAT DI PROVINSI KALIMANTAN SELATAN Suci Anshari; Dewi Sri Susanti; Fuad Muhajirin Farid
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7318

Abstract

This research is done for modeling of the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province that uses analysis of spatial regression. The purpose of this analysis is to construct the modeling of spatial regression of the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province and to identify the significant factors that influent the pure enrollment rate (PER). The result of this research shows that the modeling of spasial regression is suitable for use in the Pure Enrolment Rate (PER) at the senior high school level in South Kalimantan Province in 2017 – 2019 is the Spatial Autoregressive Model (SAR). The model form can be seen that in 2017 there is no significant influence factors to the PER, in 2018 the ratio of the student number to the school number (X5) and the ratio of the student number to the teacher number (X6) that are the influence factors significantly to the Pure Enrollment Rate (PER), while in 2019 only the factor of the ratio of the students number to the schools number (X5 ) that influents significantly to the PER.Keywords:   PER, Education, and Spatial Regression Analysis
Co-Authors Dewi Anggraini Dewi Sri Susanti Geofani Setiawan irma irma Lestia, Aprida Siska Nur Salam Putri Norhikmah Suci Anshari