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RAGAM: Journal of Statistics and Its Application
Published by Universitas Lambung Mangkurat
ISSN : -     EISSN : 29628539     DOI : https://doi.org/10.20527/ragam.vXXX
Core Subject : Economy, Humanities, Health, Science, Education,
Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health
RAGAM Journal publishes scientific articles in the field of statistics and its applications, including: * Biostatistics * Parametric and nonparametric statistics * Quality control * Econometrics and business * Industrial statistics * Time series analysis * Spatial statistics * Data mining * Computational statistics * Applications of statistics in the medical, economic, social, environmental, industrial, technological, and other related fields
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 10 Documents
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Search results for , issue "Vol 2, No 2 (2023): RAGAM: Journal of Statistics " : 10 Documents clear
PENERAPAN MANOVA DALAM ANALISIS HUBUNGAN ANTARA LUAS WILAYAH DENGAN CAKUPAN VAKSINASI COVID-19 DI PROVINSI KALIMANTAN SELATAN Muhammad Fadhil Rasyidin; Dewi Anggraini; Hidayatullah Muttaqin
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.v2i2.11331

Abstract

In Indonesia, the problem with the spread of COVID-19 is 1.35 million with 1.17 million recovered and 36,721 deaths as of March 5, 2021. From the data on the spread of COVID-19, it can be seen from the length of time that has passed, the number of cases has increased. Sinovac (CoronaVac) is a vaccine for COVID-19 produced by the Sinovac company, using inactivated virus technology or utilizing attenuated viruses. The coverage of vaccines for dose 1 and dose 2 in South Kalimantan Province is low compared to other provinces, even though South Kalimantan Province is a province that is classified as having the smallest area among other provinces included in Kalimantan Island. The purpose of the study was to find out the relationship between area and coverage of COVID-19 vaccination in South Kalimantan Province. This study uses One-Way Manova because it analyzes one predictor variable, in the form of area and three response variables simultaneously, in the form of COVID-19 vaccination coverage based on the vaccination target category: health human resources, public officers and the elderly. The results of the study using the One-Way MANOVA method showed the Pillai's Trace value of 0.020. The results of the multivariate significance test obtained by Wilk's Lambda   so that it rejects  which means that the significant model or area () has an influence on vaccination coverage (). Based on alleged multivariate regression model and the results of the MANOVA test, both are directly proportional, namely there is a significant relationship that area area has an influence on COVID-19 vaccination coverage. Large areas have vaccination coverage that tends to be low when compared to small areas. Vaccination distribution for a small area can be said to be more efficient than other broad categories and for elderly vaccine recipients, it is lower than the category of vaccine recipients for public officials and health human resources
Pemodelan Regresi Global (Glm) dan Regresi Spasial (Sar Dan Sdm) Pada Kasus Indeks Pembangunan Manusia Di Provinsi Kalimantan Selatan Ana Marliana; Jonathan Adiwinata
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.v2i2.11614

Abstract

The Human Development Index (HDI) is a parameter that functions to assess the success of the quality of human life. The factors used in the research are the severity of poverty, population density and net participation rate. The research carried out aims to see what factors influence the HDI in South Kalimantan Province in 2022, the HDI value for South Kalimantan Province is below the Indonesian HDI value and quite a few regencies/cities in South Kalimantan Province have HDI values below the HDI value. Indonesia. The statistical analysis used is a spatial approach, where the SAR and HR spatial regression models will be searched. The Global Regression Model (GLM) obtained in this study is  ,  while the Spatial Autoregressive (SAR) model is   and Spatial Durbin Model is The best model that can be obtained is the Spatial Durbin Model (SDM) with an AIC value of 52,82654 and an  value of 95,86%.
PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) PADA DATA INDEKS HARGA KONSUMEN (IHK) 5 IBUKOTA PROVINSI DI PULAU KALIMANTAN Muhammad Aldi Relawanto; Yuana Sukmawaty; Dewi Sri Susanti
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.v2i2.11427

Abstract

Generalized Space Time Autoregressive (GSTAR) model is a development model from the generalized STAR (Space Time Autoregressive) model. GSTAR model have autoregressive order to see the effect of the time element and location weighting matrix to see the effect of the location element. Unlike the STAR model, it can assume that each location research has different characteristics. The purpose of this research is to apply the Generalized Space Time Autoregressive (GSTAR) model to the Consumer Price Index (CPI) data in Kalimantan Island, especially in the capital city of each province in Kalimantan Island to find out the best estimation model with the best location weight. The location weights used the distance inverse location weights and the normalized cross-correlation location weights by estimating the parameters of the GSTAR model using the Ordinary Least Square (OLS) method. The best estimated model can be seen from the smallest Akaikae’s Information Criterion (AIC) and Root Mean Square Error (RMSE) value. From the research results, it was found that the best GSTAR prediction model for CPI data for 5 cities in Kalimantan Island was the GSTAR(1,1)-I(1). These results are based on the GSTAR prediction model with the smallest AIC value and the data is differencing 1 time. The best location weight based on the smallest RMSE value for the GSTAR(1,1)-I(1) model is the normalized cross-correlation location weight.
SPATIAL ANALYSIS OF THE RELATIONSHIP BETWEEN HUMAN DEVELOPMENT INDEXES AND ITS DETERMINANT FACTORS IN SOUTH KALIMANTAN PROVINCE: COMPARISON OF SPATIAL REGRESSION MODELING Juhar Latifah; Dewi Sri Susanti
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.v2i2.11608

Abstract

Indeks Pembangunan Manusia (IPM) berfungsi sebagai metrik penting yang mencerminkan tingkat kesejahteraan suatu wilayah melalui dimensi kesehatan, pendidikan, dan pendapatan. Dalam upaya untuk memahami lebih lanjut mengenai faktor-faktor yang mempengaruhi IPM, penelitian ini fokus pada Keparahan Tingkat Kemiskinan (X1), Kepadatan Manusia Penduduk (X2), dan Angka Partisipasi Kasar (X3) sebagai variabel kunci yang mungkin berdampak pada pembangunan, khususnya di provinsi Kalimantan Selatan. Metode yang digunakan meliputi regresi klasik, gabungan regresi spasial, dan model kesalahan spasial. Model ketiga ini akan dibandingkan dan ditentukan model dengan kinerja terbaik. Berdasarkan temuan penelitian, Structural Equation Model (SEM) muncul sebagai model yang paling efektif dalam menganalisis faktor-faktor yang mempengaruhi IPM di Kalimantan Selatan. Nilai R-square yang diperoleh sebesar 0,8946 menunjukkan tingkat daya penjelas yang tinggi, melampaui nilai R-square model lainnya.
ANALISIS MODEL LOGIT KUMULATIF UNTUK MENENTUKAN DETERMINAN USIA KAWIN PERTAMA WANITA DI KABUPATEN BALANGAN Aulia Syifa Annisa; Dewi Sri Susanti
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.v2i2.10518

Abstract

The Province of South Kalimantan is one of the five provinces in Indonesia with the highest teenage marriage rate from 2017 to 2020.  Based on 13 South Kalimantan regencies/cities, it is known that Balangan Regency has the greatest percentage of women's age at first marriage under 19 years compared to other regencies/cities, which is 55.58%. The purpose of this study is to identify the factors that influence women's age at first marriage in Balangan Regency in 2020. In this investigation, ordinal logistic regression with the cumulative logit model was used.  The findings revealed that the highest education ever/currently obtained by a woman (X1), parents' age at first marriage (X2), the highest diploma of the head of the household (X3), employment status of the head of the family (X4), location of place of residence (X5), poverty status (X6), and migration (X7) had no significant effect.  Furthermore, using the Spearman rank correlation coefficient, it was discovered that the highest education ever/currently obtained by a woman  (X1) has a substantial correlation/closeness of link with women's age at first marriage by 28%.  Women with a higher degree of education are less likely to marry at a young age, whereas women with a lower level of education are more likely.
PENERAPAN MODEL GEOGRAPHICALLY WEIGHTED PANEL REGRESSION PADA TINGKAT KEMISKINAN DI PROVINSI KALIMANTAN SELATAN Akhmad Fajar Maulana; Yuana Sukmawaty; Maisarah Maisarah
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.v2i2.11332

Abstract

South Kalimantan Province is one of the provinces in Indonesia which has the lowest poverty rate or percentage of poor people on the island of Kalimantan, even in Indonesia. The percentage of poor people in South Kalimantan Province in March 2022 was 4.49% or in the 2nd lowest poverty position in Indonesia, below the Bangka Belitung Islands Province and above the Bali Province. Geographically Weighted Panel Regression (GWPR) is a local regression model with repeated data at location points for each observation at different times. This study aims to estimate the GWPR model parameters and test the significance of the GWPR model parameters to determine the factors that influence poverty in South Kalimantan Province. The independent variables used affect the dependent variable in the form of the Percentage of Poor Population, namely Life Expectancy, Open Unemployment Rate, Economic Growth, Average Years of Schooling and Number of Crimes. The analysis in this study is descriptive analysis using thematic maps, panel data regression analysis to determine the global model and GWPR by combining the panel data model with the GWR model. The results of this study show that the fixed effect model is a global model and the fixed bisquare weighting function is the best weighting function for estimating the GWPR model. Based on the GWPR model formed, there are 7 model groups based on significant independent variables. Hulu Sungai Utara and Hulu Sungai Tengah districts are districts where poverty in these areas is influenced by many variables compared to other regions in South Kalimantan Province.
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.
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.
PENGARUH BUDIDAYA LEBAH MADU TERHADAP PEREKONOMIAN MASYARAKAT DI KOTA PALANGKA RAYA Amalina Putri Syahira; Muhammad Riza Hafizi; Hasnita Handayani
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.v2i2.11902

Abstract

The aim of this research is to determine the effect of honey bee cultivation on the economy of the people in Palangka Raya and from a Sharia Economic perspective. type of research causal research. The researcher's data collection method uses questionnaires. The population in this study were honey bee cultivation managers from the 3 (three) Forest Farmer Groups (KTH) supported by the Central Kalimantan Provincial Forestry Service, totaling 40 people, while the sample in this study was 40 people from all members of the population. The data analysis technique used is a simple linear regression analysis technique using the SPSS 25 program. The results of the research show that the honey bee cultivation variable has a significant positive effect on the community economy, which means that the higher the value of the honey bee cultivation variable, the higher the value of the community economic variable. Based on a sharia economic perspective, this is appropriate because honey bee cultivation managers have implemented the indicators that researchers use, such as social solidarity, transparency and trust.

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