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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Fisika FLUX Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) Media Bina Ilmiah RAGAM: Journal of Statistics and Its Application
Nur Salam
Dosen Program Studi Statistika, FMIPA, Universitas Lambung Mangkurat
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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 
PERAMALAN ANGKA PERCERAIAN DI KABUPATEN JEMBER PADA TAHUN 2022 MENGGUNAKAN METODE ARIMA ana safitri; Nur Salam; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11333

Abstract

Jember Regime is a locale that has the largest number of separation cases in Indonesia. Subsequently, it is important to have a measurable estimating where information from the past is utilized to foresee future prospects. The reason for this study is to break down the attributes of the information, examine the best ARIMA (Autoregressive Coordinated Moving Normal) model and conjecture utilizing the best model in Jember Regime in June - December 2022. The kind of information is quantitative with relapse estimating techniques and Box-Jenkins. Assurance of the ARIMA model is done when the information is fixed and has met the background noise prerequisites and is typically conveyed. The best demonstrating is resolved in light of huge boundaries in view of the estimation aftereffects of the Sum squared resid (SSE), Adjusted R-squared, Akaike info criterion (AIC), dan Schwarz criterion (SBC). The outcomes acquired from this study are separate from case information in Jember Rule isn't great and lopsided so doing information stationarity is vital. After the information is fixed, the best ARIMA model that meets the necessities is the ARIMA model (2,1,1). The consequences of the ARIMA (Autoregressive Coordinated Moving Normal) model (2,1,1) with the situation Zt = 0,91 Zt-1 + 0,19 Zt-2 + 0,1 Zt-3 + ?t + 0,78 ?t-1.
PENERAPAN MODEL REGRESI PANEL KOMPONEN DUA ARAH PADA POLA CURAH HUJAN PROVINSI KALIMANTAN TENGAH Vichario Indra Pradana; Yuana Sukmawaty; Nur Salam
RAGAM: Journal of Statistics & Its Application Vol 2, No 1 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i1.8303

Abstract

Rainfall is the climate element that is most closely related to supporting the life processes of Indonesian people such as agricultural production, plantations, fisheries, and aviation. In 2014-2016, Indonesia experienced a drought due to a global climate anomaly called the El Nino phenomenon, where annual rainfall at that time tended to decrease from other years. While in 2020-2022, rainfall in Indonesia tends to increase from other years, this event is called the La Nina phenomenon. This study aims to describe the rainfall patterns that occur in each phenomenon and analyze the regression model of rainfall panels in Central Kalimantan province with a two-way component approach. Random Effects Model (REM) is the most appropriate model to be used in the phenomenon of La Nina. Fixed Effect Model (FEM) is the most appropriate model to be used in the El Nino phenomenon. Feasible Generalized Least Square is a parameter estimation method that is focused and used to estimate regression parameters in this study. Based on the results of regression analysis of panel data, for the phenomenon of La Nina obtained R2 value of 51.66% and found that the average air temperature variable tested significant. For the El Nino phenomenon, the value of R2 is 75.35% and it is found that there are no significant independent variables tested. Therefore, it can be expected that the increase in average air temperature can decrease the average rainfall value when the La Nina phenomenon occurs in Central Kalimantan province.
PRAKIRAAN INDEKS KEKERINGAN MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) BERDASARKAN DATA STANDARDIZED PRECIPITATION INDEX (SPI) KOTA BANJARBARU Nabila Septiani; Nur Salam; Khairullah Khairullah
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11334

Abstract

Drought is a disaster that has a bad impact, especially in the city of Banjarbaru. There are  various ways to reduce the impact of drought in the future, one of which is by looking for information regarding the predicted drought index for the following year. The data used in this research to find the drought index value is Banjarbaru City rainfall data for 2007-2022. Seasonal Autoregressive Integrated Moving Average (SARIMA) method  is a calculated method for predicting rainfall data  and the data obtained is a forecast of rainfall in the city of Banjarbaru for the next 12 periods, namely SARIMA (0,2,3) (0,1,1)12. This model is a model that is suitable for use because it has fulfilled several tests, namely stationarity of variance and mean, significance test, white noise test and normality test with an AIC value of 1022,60 and an equation model obtained from SARIMA (0,2,3) (0,1,1)12 is (1-B)2 (1-B12) Zt=(1+1,77B-0,54B2+ 0,23B3 )(1-0,96B12 )εt. After obtaining forecast rainfall data for the next 12 periods. Rainfall data for 2007-2022 and forecast results for 2023 were used to find the drought index value using the Standardized Precipitation Index (SPI) method. It was found that the highest negative drought index value occurred in January, namely -1,774, including the dry category and the drought index had a positive value The highest occurred in June, namely 0,582, including the normal category.  The calculation results of this drought index forecast are used to provide additional information to anticipate drought disasters in the future. Keywords:   Drought Index, Rainfall, SPI Method, SARIMA Method, AIC
ANALISIS FAKTOR UNTUK PEMBENTUKAN INDEKS KESEHATAN IBU DI PROVINSI KALIMANTAN SELATAN Noorsa'adah Noorsa'adah; Nur Salam; Dewi Anggraini
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11489

Abstract

Maternal health is an important health problem because mothers are the printers of the next generation. Maternal health can describe the quality of the child to be born, so maternal health is very important to pay attention to. In Indonesia, the government has made various efforts to improve maternal health, which is still far from being expected. In this improvement effort, it is necessary to have a measure that can be used to monitor and evaluate the health development carried out, especially in the Province of South Kalimantan. Therefore, this study aims to establish a measure that can be used to describe maternal health through a composite index approach. The formation of the composite index is carried out using a technique offered by the Organization for Economic Co-Operation and Development (OECD), namely using factor analysis. Factor analysis was conducted to reduce indicators that were not significant in describing maternal health. Furthermore, the composite index formed is used to group districts/cities to make it easier to set priorities for maternal health development in South Kalimantan Province. Based on factor analysis results, the final indicators used to form the maternal health index amounted to 24 of the 30 initial indicators. After that, from the formation of the maternal health index using the composite index, it was found that the best maternal health was dominated by the cities of Banjarbaru and Banjarmasin. Meanwhile, the worst maternal health index is in Hulu Sungai Selatan District. Keywords:  Maternal Health , Composite Index, Factor Analysis.
PERAMALAN JUMLAH PENUMPANG BUS RAPID TRANSIT (BRT) BANJARBAKULA DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE WITH EXOGENOUS VARIABLE (ARIMAX) DENGAN EFEK VARIASI KALENDER Eka Ayu Frasetyowati; Nur Salam; Yeni Rahkmawati
RAGAM: Journal of Statistics & Its Application Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i1.12789

Abstract

Banjarbakula Bus Rapid Transit (BRT) is an inner-city bus-based mass transit system that provides a sense of comfort, safety, speed in mobility, and low cost in serving the citizens of Banjarmasin City and Banjarbaru City. Based on data on the number of passengers on the Banjarbakula BRT for the period April 2020 - February 2023, public interest in using the Banjarbakula BRT as a mode of transportation is quite high. However, the limited units and operational schedules make the Banjarbakula BRT unable to fully meet the needs of the public. Forecasting the number of passengers of BRT Banjarbakula for the next 12 periods is one of the measures to prepare the infrastructure, quality and units of BRT Banjarbakula in order to facilitate the public and create a better transportation system. In the Banjarbakula BRT passenger data, there is an increase in the number of passengers at certain times such as during religious holidays and school holidays, so this increase in passenger numbers is thought to be due to the influence of the calendar variation effect. This research intends to forecast the number of passengers of BRT Banjarbakula using the best ARIMAX model with the effect of calendar variation. The results indicate that the ARIMAX (0, 1, 1) model is the best ARIMAX model to forecast the number of passengers of BRT Banjarbakula for the next 12 periods. The forecast results indicate an increase in the month where the Christmas celebration and also the memorial haul guru sekumpul, so that the variable Christmas celebration and memorial haul guru sekumpul significantly affect the number of passengers of BRT Banjarbakula.Keywords: Forecasting, BRT Banjarbakula, ARIMAX with calendar variation effects
Co-Authors Ahmad Yusuf Akhriyandi Wijanarta ana safitri Annisa Halida Aprida Siska Lestia Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Dwi Anggraeni Eka Ayu Frasetyowati Fuad Muhajirin Farid Fuad Muhajirin Farid Geofani Setiawan Gt.Khiruddin Indra Permana Jainal Jainal Khairullah Khairullah Lestia, Aprida Siska Mida Yanti Nabila Septiani Nadya Pratiwi Noorsa'adah Noorsa'adah Selvi Annisa Silvi Risaria Dewi Vichario Indra Pradana Yeni Rahkmawati Yuana Sukmawaty Yunita Alisia Zainal Zainal Zakiah Zakiah