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All Journal Jurnal Pendidikan dan Konseling Jurnal Statistika dan Aplikasinya Asian Journal of Management, Entrepreneurship and Social Science
Dian Lestari
Universitas Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Calculation of Dwiguna Life Insurance Premiums using Monte Carlo Simulation with Vasicek Interest Rate Parameter Estimation based on Ordinary Least Square Pretty Lawrencia Connery; Dian Lestari; Arman Haqqi Anna Zili
Jurnal Pendidikan dan Konseling (JPDK) Vol. 4 No. 4 (2022): Jurnal Pendidikan dan Konseling
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.389 KB) | DOI: 10.31004/jpdk.v4i4.6378

Abstract

Premi adalah sejumlah uang yang harus dibayarkan tertanggung kepada perusahaan asuransi setelah kontrak ditandatangani. Beberapa variabel mempengaruhi perhitungan premi, seperti suku bunga. Vasicek merupakan salah satu model suku bunga stokastik. Model ini sering digunakan untuk menghitung premi karena model ini dapat menangkap pergerakan suku bunga pada waktu yang tidak terduga. Parameter laju Vasicek diestimasi berdasarkan Ordinary Least Square. Premi dihitung tanpa dan dengan menerapkan simulasi Monte Carlo. Tujuan dari penelitian ini adalah untuk mengetahui hasil implementasi simulasi Monte Carlo dalam perhitungan premi asuransi jiwa dwiguna. Hasil simulasi Monte Carlo akan dibandingkan dengan tanpa hasil perhitungan Monte Carlo. Hasil penelitian menunjukkan bahwa premi yang dihasilkan oleh simulasi Monte Carlo lebih tinggi dibandingkan dengan premi tanpa simulasi Monte Carlo.
Analisis Faktor-Faktor yang Menjelaskan Kasus AIDS Provinsi Jawa Timur Menggunakan Model Geographically Weighted Logistic Regression (GWLR) Natasha Latifatu Soliha; Dian Lestari; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07104

Abstract

AIDS is the most chronic phase of HIV infection which can weaken the immune system. In 2020, East Java Province is a province which has the most HIV infections and in the third place for the highest total number of AIDS cases in Indonesia. The purpose of this research is to build a model using Geographically Weighted Logistic Regression (GWLR), and to work out the grouping results of regencies/cities using K-means Clustering Analysis. The variables used in this research are Gini Ratio, L Index of Per Capita Expenditure, Gender Ratio, Dependency Ratio, Gender Development Index, and The Number of Pos Pelayanan KB Desa. The proportion levels of AIDS cases are categorized into 2 categories based on cut-point which has been specified, which 0 as the category of low level with the proportion of AIDS cases is less than 0.0006 and 1 as the category of high level with the proportion of AIDS cases is more than or equal to 0.0006. Parameter estimation for GWLR is using Maximum Likelihood Estimation (MLE) method with Fixed Gaussian as weighted kernel function and optimum bandwidth is determined using Akaike's Information Criterion Corrected (AICc). Z-Score of the most suitable model will be grouped using K-means Clustering Analysis, with Z-score is parameter estimator divided by standard error. Grouping results indicates cluster 1 members tend to be regencies/cities that have gender ratio and dependency ratio as significant variables, meanwhile cluster 2 members tend to be regencies/cities that have only dependency ratio as significant variable.
Analisis Faktor-Faktor yang Menjelaskan Pengimplementasian Nilai-Nilai Utama (Corevalues) AKHLAK pada Karyawan di PT TASPEN (Persero) Mohammad Zahran Pratomo; Yekti Widyaningsih; Dian Lestari
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07103

Abstract

The development of the global economy is currently entering the era of Industry 4.0. Industry 4.0 cannot be faced only with technological development, but must involve social dynamics in it. Every company and agency must create a strategy in dealing with this era, including Badan Usaha Milik Negara (BUMN) by establishing main values that become the reference for the behavior of all human resources in BUMN. These core values consist of Trustworthy, Competent, Harmonious, Loyal, Adaptive, and Collaborative (AKHLAK). In practice, AKHLAK has not been implemented properly, even though the corevalues of AKHLAK need to be implemented by all human resources in BUMN. This study examines the significant factors explaining the implementation of AKHLAK core values on PT TASPEN (Persero) employees and to examine the profile of employees who have implementation core values high and low are based on significant factors. The factors used in this study are work motivation, work environment, employee welfare, socialization, employee commitment, religiosity, work stress, age, gender, education level, and years of service. The methods used in solving this research problem are the Partial Least Square (PLS) method and the Classification and Regression Tree (CART) method. The data used is primary data of 209 PT TASPEN (Persero) employees taken using purposive sampling. The results showed that work motivation, socialization, religiosity, and education level can significantly explain the implementation of AKHLAK. The profile of employees who have a high level of implementation of AKHLAK are employees with high level of religiosity, high work motivation, for all categories of educational levels, and work stress levels. The profile of employees who have a low level of implementation of AKHLAK are employees who have low religiosity and work motivation.
Modeling the Number of Acute Hepatitis Sufferers in DKI Jakarta using Negative Binomial Regression Wildan Alrasyid; Dian Lestari; Fevi Novkaniza; Arman Haqqi; Sindy Devila
Asian Journal of Management, Entrepreneurship and Social Science Vol. 3 No. 02 (2023): May, Asian Journal of Management, Entrepreneurship and Social Science
Publisher : Cita Konsultindo Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hepatitis is an inflammation of the liver due to viral infections. All viral hepatitis can cause acute hepatitis. Hepatitis is an infectious disease that is a major health problem in the community because of its relatively easy transmission. DKI Jakarta is the province in Indonesia with the highest cases of acute hepatitis. Therefore, efforts need to be made to reduce the number of acute hepatitis sufferers, especially in DKI Jakarta. Several factors are thought to be closely related to the high number of acute hepatitis cases. The purpose of this study is to find factors that can significantly explain the case of hepatitis disease in DKI Jakarta so that measures can be taken to prevent the emergence of acute hepatitis cases in the community. The data in this study was obtained from the DKI Jakarta health office in 2021. The appropriate modeling for the number of people with acute hepatitis is a poisson regression model because the number of people with acute hepatitis is a count of data. In overcoming cases of overdispersion in poisson regression models, a more suitable Negative Binomial regression model is used as an alternative. In this study, the estimation of model parameters was carried out using the Maximum Likelihood Estimation (MLE) method. The results of the analysis found 3 variables that significantly explain the number of acute hepatitis sufferers in DKI Jakarta, namely the number of places of management that meet health standards, the number of health workers, and the number of HIV sufferers.
Modelling the Number of Stunting Under-Five Children in East Nusa Tenggara Using Negative Binomial Regression Honesty Citra Mar’ati; Dian Lestari; Fevi Novkaniza
Asian Journal of Management, Entrepreneurship and Social Science Vol. 4 No. 01 (2024): Pebruary, Asian Journal of Management Entrepreneurship and Social Science ( AJ
Publisher : Cita Konsultindo Research Center

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Abstract

Malnutrition is an imbalance in a person's energy intake or nutrition. Stunting is one of the nutritional problems in toddlers, where stunting is a condition of growth failure in children under five caused by malnutrition. In Indonesia, East Nusa Tenggara Province has the highest number of toddlers with stunting cases. Therefore, efforts are needed to reduce the number of stunting, especially in East Nusa Tenggara. Several factors are thought to be closely related to the high number of stunting in toddlers. This study aims to find factors that can significantly explain stunting in East Nusa Tenggara to help accelerate the decrease in the number of stunting. This study will explore stunting data from the Ministry of Home Affairs in 2021 for data on East Nusa Tenggara and the Central Statistics Agency of East Nusa Tenggara Province. The appropriate modelling for the number of stunting is the Poisson regression model because the number of stunting is in the form of count data. The proper modelling for stunting cases in toddlers is the Poisson regression model because stunting cases in toddlers are in the form of count data. There is an overdispersion problem to overcome overdispersion in the Poisson regression model; a more suitable Poisson regression model is used as an alternative model. Furthermore, the Maximum Likelihood Estimation (MLE) method estimates the model's parameters. The results showed that the complete immunization variable, pregnant women get nutritional counselling variable, the variable low birth weight babies and the variable of families with beneficiary status had a significant effect on the number of stunting in East Nusa Tenggara.
Co-Authors Alrasyid, Wildan Arman Haqqi Arman Haqqi Anna Zili fevi novkaniza Honesty Citra Mar’ati Mohammad Zahran Pratomo Natasha Latifatu Soliha Pretty Lawrencia Connery Sindy Devila Yekti Widyaningsih