Seiring dengan perkembangan dunia industri menuju fase industri 5.0, asuransi memainkan peran krusial dalam mitigasi risiko kerugian yang dapat terjadi akibat berbagai kejadian yang tidak terduga. Untuk mendukung peran tersebut, penelitian ini bertujuan untuk menentukan cadangan klaim Incurred But Not Reported (IBNR), yaitu klaim yang telah terjadi namun belum dilaporkan kepada perusahaan asuransi, menggunakan metode Cape Cod parametrik. Metode Cape Cod parametrik dipilih karena mampu mengatasi kelemahan metode Chain Ladder, Bornhuetter-Ferguson, dan Cape Cod klasik, seperti sensitivitas terhadap outlier, ketidakstabilan estimasi, dan kurang optimalnya penggunaan informasi premi. Metode ini mengadaptasi pendekatan Cape Cod klasik dengan melibatkan informasi premi dan parameter distribusi dari data klaim untuk estimasi cadangan yang lebih akurat. Proses penerapannya diawali dengan penentuan distribusi parametrik yang tepat untuk memodelkan claim cost per unit exposure. Apabila model distribusi yang terpilih merupakan bagian dari keluarga exponensial dispersi, maka metode Cape Cod parametrik dapat diterapkan. Metode Cape Cod parametrik akan diimplementasikan pada data run-off triangle dari Institute of Actuaries of Australia. Hasil penelitian menunjukkan bahwa metode Cape Cod parametrik dapat memberikan estimasi cadangan klaim IBNR dengan tingkat akurasi yang baik. Akurasi prediksi diukur menggunakan Mean Absolute Percentage Error (MAPE) dengan hasil 2.047%.
As the industrial world progresses towards the Industry 5.0 phase, insurance plays a crucial role in mitigating the risks of losses that can occur due to various unforeseen events. To support this role, this study aims to determine the Incurred But Not Reported (IBNR) claim reserves, which are claims that have occurred but have not yet been reported to the insurance company, using the parametric Cape Cod method. The claim data used are run-off triangle data from the Institute of Actuaries of Australia. This method adapts the classical Cape Cod approach by incorporating premium information and the distribution parameters of claim data for more accurate estimates. The parametric Cape Cod method was chosen because it can address the shortcomings of the Chain Ladder, Bornhuetter-Ferguson, and classical Cape Cod methods, such as sensitivity to outliers, instability of estimates, and suboptimal use of premium information. The implementation process includes checking the distribution of claim cost per unit exposure using the Kolmogorov-Smirnov method and calculating dispersion parameters. The results show that the parametric Cape Cod method can provide more stable and accurate IBNR claim reserve estimates, especially in handling volatility and outliers in claim data. Prediction accuracy is measured using the Mean Absolute Percentage Error (MAPE), with results indicating a good level of accuracy of 2.047%.
;Capturing the many ... changes taking place in the state and local government arenas, this book not only helps you understand structure, process, and policy, but also shows why your knowledge of state and local government is so important to your success as a professional and a private citizen. [The authors] help you get to know the players--the political parties, interest groups, media, state political systems, communities, business organizations, civic clubs, religious congregations--and how they interact to produce policy. Along the way, you'll discover how this policy making at the state and local levels affects your life--both personally and professionally--at nearly every turn., Capturing the many ... changes taking place in the state and local government arenas, this book not only helps you understand structure, process, and policy, but also shows why your knowledge of state and local government is so important to your success as a professional and a private citizen. [The authors] help you get to know the players--the political parties, interest groups, media, state political systems, communities, business organizations, civic clubs, religious congregations--and how they interact to produce policy. Along the way, you'll discover how this policy making at the state and local levels affects your life--both personally and professionally--at nearly every turn.]
Penelitian ini membahas dampak Intergovernmental Fiscal Transfers (IFT) terhadap konservasi hutan selama periode 2008-2016 di Indonesia. Penelitian ini menggunakan model panel berupa fixed effect dan Spatial Autoregressive (SAR) fixed effect. Hasil penelitian menyimpulkan bahwa adanya pengaruh transfer pemerintah pusat dalam bentuk Dana Perimbangan berupa Dana Alokasi Khusus dan Dana Bagi Hasil positif memengaruhi perluasan area konservasi hutan di Indonesia level kabupaten/kota. Dana koordinasi berupa Dana Tugas Pembantuan positif signifikan memengaruhi pada level kabupaten/kota sedangkan level provinsi menunjukkan positif saja. Selain itu, dampak dari daerah yang berdekatan atau neighbourhood effect secara empiris terbukti memengaruhi perluasan area konservasi hutan di Indonesia. Dampak tersebut terlihat pada koefisien spasial yang positif. Sehingga dapat disimpulkan pada penyediaan barang publik seperti area konservasi hutan peristiwa yang terjadi justru bukan free rider. Barang publik yang memiliki spillover positif akan memunculkan kejadian berupa mimicry, keikutsertaan penyediaan pada daerah yang berdekatan (neighbour).
In this study aim to look at impact of Intergovernmental Fiscal Transfers (IFT) on forest conservation during the period 2008-2016 in Indonesia. This study uses panels model fixed effect, and Spatial Autoregressive (SAR) fixed effect. The results of this study suggest that Impact of Intergovernmental Fiscal Transfer (IFT) in the form Dana Perimbangan such as Special Allocation Funds (DAK) and Revenue Sharing Funds (DBH) positive significantly influences the expansion of forest conservation areas in Indonesia. Coordination funds in the form Dana Tugas Pembantuan positively significantly affect the district/city level while the provincial level shows just positive. In addition, the impact of adjacent areas or neighborhood effects has been empirically proven to influence the expansion of forest conservation areas in Indonesia. The impact is seen in positive spatial coefficients. It can be concluded that the provision of public goods such as the forest conservation area is occured not a free rider. Public goods that have positive spillover will actually issue a mimicry event, participation in the neighboring area.