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All Journal Statistika International Journal of Supply Chain Management
Wan Muhamad Amir W Ahmad
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Transportation

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Efficiency of General Insurance in Malaysia Using Stochastic Frontier Analysis Mohamad Arif Awang Nawi; Wan Muhamad Amir W Ahmad; Nor Azlida Aleng
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 11, No 2 (2011)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v11i2.1050

Abstract

General insurance comprises insurance of property against fire and burglary, floods, storms,earthquakes and so on. The purpose of the current study is to measure the relative efficiency of generalinsurance in Malaysia by using SFA for the year 2007 until 2009, consist of 26 general insurancecompanies by using the software FRONTIER to obtain the maximum likelihood (ML) and to get therelative efficiency. The finding showed that Oriental Capital Assurance Bhd (OCA) is at rank 1 for thethree years. The 0.03975 value for the variance gamma ( γ ) parameter in this study is far from one,suggesting that all of the residual variations are not due to the inefficiency effects, but to randomshocks. It can therefore, be concluded that the technical inefficiency effects associated with theproduction of the total profits by the input of the general insurence are very low.
Identifying Unwanted Conditions Using Lower Boundaries on Individual Control Charts in the Context of Supply Chain Economic Resilience of Cities in Indonesia Purwandari, Titi; Sukono, Sukono; Hidayat, Yuyun; Ahmad, Wan Muhamad Amir W
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.5346

Abstract

This study presents the unwanted conditions determination. The economic resilience model without taking into account the level of disruption and unwanted conditions is unrealistic model. The Objective is to determine unwanted conditions as a key criterion in determining the economic resilience status of a city. This study used data on Concern variables group and Control variables groups from website of Central Bureau of Statistics Indonesia. These data covered all 514 cities in Indonesia and are observed for a 5-year period from 2014 to 2018. The data is useful to develop a statistical model that can explain well the pattern of relationships between concern variables and control variables. Piecewise linear regression is applied to identify statistics model between Pc and Z, Lower Control Limit (LCL) for variable Z using Individual control Chart is applied to determine the unwanted conditions.  We obtained that the control variable, Z is the ratio between the original income of the region (PAD) with the number of poor people in a city and the concern variable is income per capita, Pc of a city. Piecewise linear regression with breakpoint 126,255,066 can explain well the pattern of relationships between Z and Pc variables. The equation is: Pc = 26,660,263+0.28Z, R-square = 70.48%. LCL value is.1.884.059.5 so all cities that have a Z value below 1.884.059.5 fall into the unwanted condition area and after careful examination is obtained percentage of cities classified as do not have economic resilience , PER =28%. Cities that fall into unwanted conditions are defined as cities that cannot bear receiving economic shocks.
Co-Authors Mohamad Arif Awang Nawi Nor Azlida Aleng Sukono . Titi Purwandari Yuyun Hidayat