scholarly journals Modeling of COVID-19 Epidemic Growth Curve in Indonesia

2021 ◽  
Vol 7 (1) ◽  
pp. 67-73
Author(s):  
Muhammad Fajar ◽  
Wahyudi Wahyudi
Keyword(s):  
Growth Curve ◽  
Gompertz Model ◽  
Parametric Modeling ◽  
Coefficient Of Determination ◽  
Cumulative Number ◽  
Maximum Value ◽  
The Government

Aim of this study is to make parametric modeling of the COVID-19 epidemic growth curve so that the maximum value and time at that point can be obtained from the cumulative cases of COVID-19. The data used in this study is the cumulative number of positive confirmed cases of COVID-19 from https://covid19.go.id/. The method used in this study is fitting data with the Logistic and Gompertz models. Result of this study are (1) the Logistic and Gompertz models are very fit in modeling the COVID-19 epidemic growth curve, indicated from the value of R2 (coefficient of determination) which reaches more than 99%; (2) From the Logistics model it is obtained that the estimated amount of the maximum cumulative case at the end of the COVID-19 epidemic is 7,714 positive confirmed cases, achieved in about 82 days (May 22, 2020) from Mar 2, 2020, when the first positive COVID-19 case was announced by the government; and (3) From the Gompertz model, it is obtained that the estimated maximum cumulative case at the end of the COVID-19 epidemic is 33,975 positive confirmed cases, achieved in about 152 days (Jul 30, 2020) from Mar 2, 2020. The results of this study can be used as input to the government to take steps in controlling the spread of COVID-19.

PEMODELAN PARAMETRIK KURVA PERTUMBUHAN EPIDEMI COVID-19 DI INDONESIA

2020 ◽  
Vol 25 (2) ◽  
pp. 45-48
Author(s):  
Muhammad Fajar ◽  
Keyword(s):  
Growth Curve ◽  
Gompertz Model ◽  
Parametric Modeling ◽  
Coefficient Of Determination ◽  
Maximum Point ◽  
Cumulative Number ◽  
Maximum Value ◽  
The Government

The purpose of this study is to carry out parametric modeling of the COVID-19 epidemic growth curve so that the maximum value of the cumulative COVID-19 case and the time when it reaches that maximum point can be obtained. The data used in this study is the cumulative number of COVID-19 positive confirmed cases originating from www.covid19.go.id. The method used in this study is fitting data with the Logistic and Gompertz models. The results obtained from this study are (1) the Logistic and Gompertz mod-els are very fit in modeling the COVID-19 epidemic growth curve, indicated from the value of R2 (coefficient of determination) which reaches more than 99%, (2) From the Logistics model it is obtained that the estimated amount of the maximum cumulative case at the end of the COVID-19 epidemic is 7,714 positive confirmed cases, achieved in about 82 days (22 May 2020) from 2 March 2020 when the first positive COVID-19 case was announced by the Government. (3) From the Gompertz model, it is ob-tained that the estimated maximum cumulative case at the end of the COVID-19 epidemic is 33,975 positive confirmed cases, achieved in about 152 days (30 July 2020) from 2 March 2020 when the first positive COVID-19 case was announced by the Government. From this finding, the results of this study can be used as input to the Government to take steps in controlling the spread of COVID-19

The Effect of Investments and Risk Based Capital (RBC) of Tabarru Funds on Company (Case Study of Sharia Insurance in Indonesia for 2014-2019)

2020 ◽  
Vol 8 (1) ◽  
pp. 87-97
Author(s):  
Nana Diana ◽  
Tati Apriani
Keyword(s):  
Life Insurance ◽  
Statistical Tests ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Insurance Companies ◽  
Coefficient Of Determination ◽  
Verification Method ◽  
Investment Returns ◽  
The Government

This study aims to examine the influence of investment returns and Risk Based Capital (RBC) Tabarru Funds to the profit of sharia life insurance in Indonesia from 2014-2019. This study The type of this research is quantitative research with descriptive verification as a method. This research method uses descriptive verification method with quantitative approach. The data used in this study were sourced from the financial statements of Islamic life insurance companies in Indonesia for the 2014-2019 period. Then the data obtained were analyzed using multiple linear regression analysis and hypothesis testing consisting of t test and f test with the help of SPSS 21 software. The sampling technique uses non probability sampling with purposive sampling technique. Based on the results of the study it can be seen that the development of investment returns on Sharia Life Insurance in Indonesia has fluctuated and even suffered losses. While the development of Risk Based Capital (RBC) has increased and decreased but overall above 120% as determined by the government. Likewise, the profits earned in each year fluctuate. The results of statistical tests show that investment results partially have a positive effect on profit and Risk Based Capital (RBC) of Tabarru funds partially has a negative effect on profit. Simultaneously investment return and Risk Based Capital (RBC) affect on profit. In addition, the results of the coefficient of determination (R2) were obtained which obtained a value of 81%. This shows that the variable investment returns and Risk Based Capital (RBC) can affect earnings by 81% and the remaining 19% is influenced by other variables not used in this study.

FRAUD CONFIRMATION, CLIENT SATISFACTION AND CLIENT LOYALTY

2019 ◽  
Vol 1 (1) ◽  
pp. 39
Author(s):  
Ngurah Pandji Mertha Agung Durya
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Client Satisfaction ◽  
Audit Quality ◽  
Hypothesis Test ◽  
Linear Regression Analysis ◽  
Quality Attributes ◽  
Path Model ◽  
Coefficient Of Determination ◽  
The Government

<p>This study aims to find evidence, the influence of Audit Quality Attributes, Client Satisfaction and Client Loyalty, which are moderated by Fraud Confirmation. The research was conducted at the BKM, a community-based organization, formed by the Government, through the <em>Kotaku</em> Program. The research used Regression statistical analysis and conducted a hypothesis test. Regression analysis used includes Simple Linear Regression Analysis, Multiple Regression Analysis, and MRA Regression Analysis, and Path Model Linear Regression Analysis. This study also pays attention to the calculation of the coefficient of determination to give an idea of the ability of the model in explaining the phenomenon of Client Satisfaction and Client Loyalty. The result that both partially and simultaneously, Audit Quality Attributes, Fraud Confirmation affected Client Satisfaction and Loyalty. The research also succeeded in proving that Client Satisfaction mediates the effect of Audit Quality Attributes on Client Loyalty, but failed to provide empirical evidence, that the Fraud Confirmation moderated the effect of Audit Quality Attributes on Client Satisfaction and Loyalty. Contribution to audit practices, where it is important to realize Client Satisfaction through Audit Quality Attributes and Fraud Confirmation, especially in situations where Fraud acts are suspected.</p>

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

scholarly journals Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zuiyuan Guo ◽  
Dan Xiao
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Cumulative Number ◽  
Individual Based Model ◽  
Whole Process ◽  
Coordinate Descent Algorithm ◽  
Initial Stage ◽  
The Government ◽  
Prevention And Control Measures ◽  
And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

scholarly journals A generalized Gompertz growth model with applications and related birth-death processes

2020 ◽  
Author(s):  
Majid Asadi ◽  
Antonio Di Crescenzo ◽  
Farkhondeh A. Sajadi ◽  
Serena Spina
Keyword(s):  
Growth Model ◽  
Growth Curve ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Death Process ◽  
Birth Process ◽  
Failure Data ◽  
First Case ◽  
Gompertz Growth Model ◽  
Birth Death

AbstractIn this paper, we propose a flexible growth model that constitutes a suitable generalization of the well-known Gompertz model. We perform an analysis of various features of interest, including a sensitivity analysis of the initial value and the three parameters of the model. We show that the considered model provides a good fit to some real datasets concerning the growth of the number of individuals infected during the COVID-19 outbreak, and software failure data. The goodness of fit is established on the ground of the ISRP metric and the $$d_2$$ d 2 -distance. We also analyze two time-inhomogeneous stochastic processes, namely a birth-death process and a birth process, whose means are equal to the proposed growth curve. In the first case we obtain the probability of ultimate extinction, being 0 an absorbing endpoint. We also deal with a threshold crossing problem both for the proposed growth curve and the corresponding birth process. A simulation procedure for the latter process is also exploited.

Pengaruh Sistem Pengendalian Internal Pemerintah Terhadap Kinerja Pemerintah Daerah

2021 ◽  
Vol 2 (2) ◽  
pp. 100-109
Author(s):  
Mattoasi Mattoasi ◽  
Didiet Pratama Musue ◽  
Yaman Rauf
Keyword(s):  
Control System ◽  
Internal Control ◽  
Local Governments ◽  
Quantitative Research ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Quantitative Research Methods ◽  
Internal Control System ◽  
The Government

PThis study aims to determine the effect of the internal control system on the performance of local government Case Study in Gorontalo Regency. This study uses quantitative research methods, and the data sources use primary data obtained from questionnaires distributed to respondents. Meanwhile, the data analysis used in this research is descriptive quantitative analysis using statistical t-test and coefficient of determination test (ajusted R-Square). The results showed that the internal control system had a positive effect on the performance of local governments with a determinant value of 48.7%. The result of this study contribute to the government to establish and implement a more effectives Internal Constrol Systems (ICS).  

CRITICAL FACTORS INFLUENCING IMPLEMENTATION OF ROAD PROJECTS IN KENYA

2019 ◽  
Vol 4 (2) ◽  
pp. 1-22
Author(s):  
Nelly Jebitok ◽  
DR. Joyce Nzulwa
Keyword(s):  
Project Management ◽  
Survey Design ◽  
Target Population ◽  
Coefficient Of Determination ◽  
Critical Factors ◽  
Policy And Practice ◽  
Water Projects ◽  
Factors Influencing ◽  
The Government ◽  
Resource Support

Purpose: The Purpose of the study was to establish Critical factors influencing implementation of road projects.Methodology: The study adopted a descriptive survey design. The target population of the study was all the road engineers, middle managers in department of KRB. The sample size was 188 respondents. Data collected was cleaned, pretested, validated, and coded, summarized and analyzed using statistical package of SPSS V23.  The study findings were presented using graphs, histograms, bar charts and pie charts.  Conclusions were derived based on the P.value and the coefficient of determination.  Results: The study found that the key significant determinants of sustainability of water projects in Machakos County were capacity of the project management, government policies, monitoring and resource support. The study concluded that project management capacity had the greatest determinant ofsustainabilityofwater projects in Machakos County, followed by resource support, then monitoring while government policy had the least determinant of sustainability of water projects in Machakos County.Contribution to policy and practice: The study recommends that the government should advocate for proper planning with involvement of the benefiting community and timely implementation with the required results. This can be done through making of a policy by the ministry demanding for the practice of the same by the involved organizations. The project committee should set up financial structures considering both rising of funds and dissemination of the same in relation to operating and maintaining of the project. This can be done through learning and training on the same. The study also recommended that water beneficiaries and management should be sensitized to improve their knowledge on conservation and protection of water facilities.

scholarly journals ANALISIS POLA KONSUMSI DAN MODEL PERMINTAAN IKAN MENURUT KARAKTERISTIK RUMAH TANGGA DI INDONESIA

2018 ◽  
Vol 13 (1) ◽  
pp. 73 ◽  
Author(s):  
Freshty Yulia Arthatiani ◽  
Nunung Kusnadi ◽  
Harianto Harianto
Keyword(s):  
Fish Consumption ◽  
Income Elasticity ◽  
Fish Distribution ◽  
Consumption Patterns ◽  
Demand System ◽  
Coefficient Of Determination ◽  
Almost Ideal Demand System ◽  
Demand Model ◽  
Demand Models ◽  
The Government

ABSTRAKTujuan penelitian ini adalah untuk mendeskripsikan pola konsumsi ikan di Indonesia dan mengidentifikasi faktor-faktor yang mempengaruhi permintaan ikan menurut karakteristik rumah tangga di Indonesia. Penelitian ini menggunakan data SUSENAS yang dilaporkan oleh Badan Pusat Statistik pada bulan Maret 2016. Pola konsumsi ikan dianalisis menggunakan statistik deskriptif dan model permintaan ikan dianalisis dengan menggunakan pendekatan model Linnear Approximation Almost Ideal Demand System (LA/AIDS). Hasil riset menunjukkan bahwa pola konsumsi rumah tangga di Indonesia dikelompokkan menjadi konsumsi ikan air laut segar sebesar 22.10 kg/kapita/tahun, ikan air tawar/payau segar sebesar 16.75 kg/kapita/tahun, udang segar sebesar 9.58 kg/kapita/tahun dan ikan olahan sebesar 4.22 kg/kapita/tahun. Dugaan model permintaan memberikan hasil cukup baik dengan 82.15% dari semua peubah berpengaruh signifikan terhadap fungsi permintaan kelompok ikan dan koefisien determinasi sebesar 27.06%. Nilai elastisitas pendapatan mengindikasikan bahwa seluruh kelompok ikan merupakan barang normal dan ikan olahan cenderung inelastis, sedangkan dari nilai elastisitas harga menunjukkan tanda negatif yang sesuai dengan teori ekonomi. Nilai elastisitas silang antar kelompok ikan menunjukkan hubungan yang bervariasi antar kelompok. Implikasi kebijakan yang dapat disarankan untuk meningkatkan konsumsi ikan segar adalah dengan peningkatan ketersediaan ikan melalui kebijakan peningkatan produksi dan peningkatan efektifitas distribusi ikan. Kebijakan promosi dan edukasi masih diperlukan untuk meningkatkan konsumsi ikan olahan karena sifatnya yang inelastis  terhadap perubahan harga dan pendapatan.Title: Analysis of Fish Consumption Patterns and Fish Demand Model Based on Household’s Characteristics in IndonesiaABSTRACTThis study aims to describe the pattern of fish consumption in Indonesia and to identify factors affecting household’s fish demand in Indonesia as well as estimating the elasticities of income and price. The data analyzed were mainly obtained from the SUSENAS Database-a nation social economy survey  conduct by the Indonesian Bureau of Statistic (BPS- during march 2016. Fish consumption patterns were analyzed using descriptive statistical analysis, while fish demand models were analyzed by Linnear Approximation Almost Ideal Demand System (LA/AIDS). Research shows that household consumption patterns in Indonesia are grouped into consumption of marine fish at 22.10 kg / capita / year, freshwater/brackish fish at 16.75 kg / capita / year, fresh shrimp at 9.58 kg / capita / year and processed fish amounted to 4.22 kg / capita / year. The estimation of the demand model gives quite good results with82,15% of all variables have a significant effect on the demand function of fish groups and the coefficient of determination is 27.06%. The value of income elasticity showed that all fish groups are normal goods and were negatively related to prices. The cross elasticities showed variation relationship between fish groups. With such result, in order for the government to be able to push the fish consumption level furtherwould require an increasing fish availbility through policies to increase production and effectiveness of fish distribution for fresh fish. Meanwhile education and promotion policies are necessary to increase consumption of processed fish because of their inelastic demand for changes in prices and income.

scholarly journals Analysis of second wave of COVID-19 cases in Nepal with a logistic model

2021 ◽  
Vol 12 (10) ◽  
pp. 20-26
Author(s):  
Radha Krishna Joshi ◽  
Sarita Bhatt ◽  
Tika Ram Lamichhane ◽  
Madhav Prasad Ghimire
Keyword(s):  
Infectious Disease ◽  
Health Policy ◽  
Logistic Model ◽  
Control Strategies ◽  
Coefficient Of Determination ◽  
Data Modelling ◽  
Wave Impact ◽  
New Variant ◽  
The Government ◽  
Second Wave

Background: COVID-19, caused by SARS-CoV-2, is a newly identified highly infectious disease. It has affected almost every country including Nepal causing a pandemic situation. Most of the properties of SARS-CoV-2 are not known and still under intense investigation. Due to high mutation rate, it reappears in many countries in the form of new variant. In Nepal, second wave impact of COVID-19 is mainly caused by newly found delta variant of SARS-CoV-2. In this case, the mathematical modelling is noted to play important role to understand control strategies for the spread of coronavirus. Aims and Objective: To analyze the second wave impact by modelling the data of COVID-19 cases in Nepal. Materials and Methods: We have analyzed COVID-19 daily cases and deaths reported by Ministry of Health and Population, Government of Nepal from April 1 to May 31, 2021. A logistic model has been used to present the trend line of COVID-19 infection in Nepal, based on the law of population growth developed by Verhulst. Results: The results show a good fit between observed and predicted data by logistic model as indicated by coefficient of determination having value near to unity. The point of inflection from the logistic model predicted a maximum of 9951 daily new cases. The maximum number of cumulative cases estimated at the end of second wave was found to be 307293 with 95% confidence interval. Conclusion: Logistic model properly describes the growth of COVID-19 cases with time. This type of data modelling and analysis will be very useful in predicting the upcoming trend of COVID-19 in Nepal as a basis for making health policy management by the government.

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