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Variansi : Journal of Statistics and Its Application on Teaching and Research
Published by Universitas Negeri Makassar
ISSN : -     EISSN : 26847590     DOI : https://doi.org/10.35580/variansiunm
Core Subject : Economy, Health, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Public Health
VARIANSI: Journal of Statistics and Its application on Teaching and Research memuat tulisan hasil penelitian dan kajian pustaka (reviews) dalam bidang ilmu dasar ataupun terapan dan pembelajaran dari bidang Statistika dan Aplikasinya dalam pembelajaran dan riset berupa hasil penelitian dan kajian pustaka.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 8 Documents
 1 
Search results for , issue "Vol 3, No 2 (2021)" : 8 Documents clear
PENDEKATAN MARKOV CHAIN UNTUK MENGANALISIS PERENCANAAN SUMBER DAYA MANUSIA DI KEPOLISIAN SEKTOR TAMALATE KOTA MAKASSAR Suhartin M; Ruliana Ruliana; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23856

Abstract

this research, an analysis of Human Resources planning in the Makassar City Tamalate Police Sector uses Markov Chain. The data used are sourced from secondary data in the Makassar City Tamalate Police Sector from the last two years period, from 2018 to 2019. The Markov Chain is used to find out transfers that occur between police positions with the first process being determining states, calculating inter-state probability values, forming a transition probability matrix, and predicting the number of police officers for the next six years. Based on the research conducted, it can be concluded that five states were formed, the ranks of the Second Police Brigadiers up to the Chief Police Brigadier are classified as Non-Commissioned Officers positions, state two the ranks of Second Police Inspector Adjutant up to First Pollice Inspector Adjutant are clarified as Warrant Officers position, state three Second Police Inspector up to Police Commissioner Adjutant are clarified Low-Rank Officers, four state Pollice Coommisioner are clarified of Mid Rank Officer, state five additional and reduction of Police Members. Based on the results of forecasting, the probability for the most Police Members in the year 2020 to 2025 is a member domiciled as a Non-Commissioned Officers, the probability of a large number of Non-Commissioned Officers is relatively stable at 0.54 from 2020 to 2024 and will decrease by 0.01 in 2025. Probabilities the number of Warrant Officers has increased quite dramatically, in 2020 amounting to 0.35 continues to increase until 2025 which is equal to 0.42. Whereas the probability for the number of Police Members to be Low-Rank Officers has decreased every year from 2020 to 0.08 to 0.03 in 2025. Then for Mid Rank Officers the probability for the number of Police Members to remain stable every year is 0.01. The probability of the number of Police officers in 2020 is 0.02 and in 2025 it is 0.01
REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI KEMISKINAN DI SULAWESI SELATAN Muh. Qodri Alfairus; Muhammad Arif Tiro; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23857

Abstract

Poverty is a condition of economic inability to meet the average standard of living of the people in an area. The percentage of poverty in Indonesia reaches 9.41% or reaches 25.14 million people. On the island of Sulawesi, the poverty percentage of the population is still quite high. One of the regions with the highest percentage of poverty in Sulawesi Island is South Sulawesi Province with a poverty percentage of 8.69%, which is ranked 18th nationally. Poverty can be seen with two indicators, namely the percentage of poor people and the poverty depth index. This study uses 5 factors that are thought to affect poverty in South Sulawesi which include the Literacy Rate, Average Length of Schooling, Open Unemployment Rate, PDRB Per Capita, and School Participation Rate. The data used in this research is data from 2018 which comes from the Central Statistics Agency of South Sulawesi. The method used to model the percentage of poor population and the depth of poverty index is a multivariate spline nonparametric regression. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita. This method is used because it is suitable in modeling data whose patterns change at certain subintervals. The best model that is produced from the nonparametric multi-variate spline regression in South Sulawesi is the knot 2 model and the most influencing factors are the School Participation Rate and GRDP Per Capita
PENDEKATAN REGRESI NONPARAMETRIK SPLINE TRUNCATED PADA INDEKS PEMBANGUNAN MANUSIA DI SULAWESI SELATAN Selvi Meilinda; Sudarmin Sudarmin; Muhammad Nusrang
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23860

Abstract

The human development index is an improvement in the quality of life for the society which is used as a benchmark for human development which consists of 3 basic aspects, namely health, education, and life worthiness. In South Sulawesi, the Human Development Index (HDI) has been categorized as high even though its growth tends to slow down. There are several factors that are thought to influence HDI in South Sulawesi, namely, Life Expectancy, Average Length of Schooling, Population Percentage, Morbidity Rate, and Gross Regional Domestic Product (GRDP). Modeling is done by using the spline truncated nonparametric regression analysis method with the Generalized Cross-Validation (GCV) approach to obtain the best optimal value that is the minimum optimal value. The results of this study indicate that based on the fishery significance test of the model parameters, it can be seen that there are variables that significantly influence the Human Development Index in South Sulawesi, namely Gross Regional Domestic Product (x5). Based on the research, the minimum GCV value was 0.08 which was obtained from 3 knots with a value of 90.94%.Keywords: GCV, Human Development Index, Spline Truncated Nonparametric Regression
MODEL HIBRIDA DEKOMPOSISI-ARIMA UNTUK PERAMALAN INFLASI DI KOTA MAKASSAR Muhammad Fahmuddin; Zulkifli Rais
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23889

Abstract

Forecasting is an art and predicting science about future events. Forecasting could be basic for short-term, mid-term, and long-term planning. The aim of this study is to create a hybrid decomposition model - ARIMA to forecast inflation data in Makassar City. The decomposition method is used for decomposition the inflation data into trend components, seasonal, and random. Furthermore, the decomposition method could be used to forecasting the tren component dan seasonal. Whereas, the ARIMA method was used to forecasting the random component. The result of this study shows ARIMA model used for forecasting the random component is ARIMA (0,0,[3]) with an AIC score of 171,6973Keywords: Decomposition, ARIMA, inflation
METODE KAPLAN MEIER UNTUK ANALISIS KETAHANAN HIDUP PENDERITA KANKER PAYUDARA DI RSUD KOTA MAKASSAR Mahrani Mahrani; Muh.Nadjib Bustan; Suwardi Annas
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm23853

Abstract

this research, using survival analysis with the Kaplan Meier method. The purpose of this research is to know the life resistance of breast cancer survivors in the Regional General Hospital of Makassar city based on the age group of patients, cancer stage group of patients, and measures chemotherapy group of patients. The results of this research show that (i) the survival rate of breast cancer patients (with a sample size of 74 patients over a period of three years) is more than 354 days with a probability of 0.285 or 28.5%. (ii) When viewed from an early age infected the survival rate for 45 years of age is 1 or 100 for 45 years of an age exceeding 354 days with a probability of 0.229 or 22.9%. The probability of survival for breast cancer patients based on stage level variables, namely stage II of 1 or 100%, survival of stage III breast cancer patients exceeding 21 days with a probability of 0.929 or 92.9%, and survival of stage IV breast cancer patients exceeding 354 days with a probability of 0. The survival of patients following chemotherapy exceeded 354 days with a probability of 0.292 and the survival of patients who did not follow chemotherapy exceeded 17 days with a probability of 0.727
PEMODELAN ANALISIS REGRESI SPASIAL PADA KASUS KEMISKINAN KABUPATEN/KOTA DI JAWA TIMUR TAHUN 2020 Kiki Laila Nirmala; Wara Pramesti
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm24477

Abstract

The percentage of poor people is still a problem in Indonesia, and one of them is in East Java Province, where based on the results of the SUSENAS, in the March 2020 period, the country's poverty line increased by 2.93% or increased by Rp. 11,829,- per capita per month, ie from Rp. 404,172,- per capita per month in September 2019 to Rp. 416,001,- per capita per month in March 2020. Although the increase is not high, it is still a concern. The increase and decrease in the percentage of poverty of course some factors influence, and to determine the influencing factors can be used but presents the possibility of regression analysis is also influenced by the surrounding conditions so that the assumption of independent possibility is not met. To overcome this problem, a Spatial Regression approach can be used, which in the analysis has taken into account the surrounding area. The results show that the percentage is influenced by factors that have a significant effect, also influenced by neighbors, and the appropriate spatial regression analysis modeling is the Spatial Autoregressive Model (SAR).Keywords: Poverty, Spatial Regression, SAR
ANALISIS PELUANG PENYEBARAN COVID-19 MENGGUNAKAN RANTAI MARKOV DI SULAWESI SELATAN M. Nadjib Bustan; Ruliana Ruliana; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm25170

Abstract

Virus Corona sudah menyebar ke seluruh negera termasuk salah satunya di Indonesia. Karena transmisi Covid-19 dari manusia ke manusia telah dikonfirmasi dan mobilitas manusia juga merupakan faktor penguat persebaran Covid-19, sehingga diperlukan suatu informasi yaitu data harian Covid-19 yang berguna untuk melihat laju persebaran Covid-19. Oleh karena itu, diperlukan suatu pendekatan untuk menganalisis peluang penyebaran covid-19 di setiap wilayah sehingga pengambilan keputusan menjadi tepat. Pada penelitian ini, dilakukan analisis dengan rantai markov diskrit untuk memprediksi peluang penyebaran Covid-19 pada kabupaten/kota di Sulawesi Selatan. Penelitian ini adalah penelitian yang bersifat kuantitatif dengan menggunakan konsep stokastik. Pada bagian awal dilakukan kajian sumber-sumber pustaka dengan cara mengumpulkan data atau informasi yang berkaitan dengan masalah, mengumpulkan konsep pendukung yang diperlukan dalam menyelesaikan masalah, sehingga didapatkan suatu ide mengenai bahan dasar pengembangan upaya pemecahan masalah.  Hasil penelitian menunjukkan bahwa pada saat pengamatan (28 Agustus 2021) di Sulawesi Selatan (Sulsel), Kota Makassar menjadi daerah dengan peluang penyebaran yang paling tinggi, sedangkan Kabupaten Bantaeng dengan peluang penyebaran terendah. Pada hasil analisis dengan rantai Markov, terlihat bahwa terjadi penurunan peluang infeksi untuk setiap Kabupaten/Kota di Sulawesi Selatan dan cenderung menjadi homogen.Keywords: covid-19, Markov chain, peluang bersyarat
Pengelompokan Daerah Penyebaran Demam Berdarah Dengue Alam Dengan Menggunakan Algoritma K-Means Di Kota Makassar Zulkifli Rais; Misveria Villa Waru
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm25657

Abstract

This study proposes the k-means method to map the endemic areas of dengue fever in the city of Makassar. Data were obtained from the health department based on the number of patients affected by dengue hemorrhagic fever (DHF) in every sub-district in Makassar City. The k-means method has mapped the area into 3 groups. These results indicate that group 1, which is the area that has the highest number of DHF sufferers, is Rappocini, Panakukang, and Manggala villages. Furthermore, Tamalate and Biringkanaya villages are members of group 2. And group 3 is an area that has a low number of dengue patients, namely Mamajang, Makassar, Tamalanrea, Mariso, Ujung Pandang, Bontoala, Tallo, Ujung Tanah, Wajo. Keywords: k-means, dengue hemorrhagic fever (DHF)

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