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"[ABSTRAKDalam dunia bisnis selalu terdapat persaingan, yang menuntut kemampuan perusahaan untuk beradaptasi dalam rangka mencapai keunggulan bersaing. Bisnis asuransi kerugian, dengan jumlah pemain 85 perusahaan, merupakan bisnis dengan tingkat persaingan cukup ketat. Kondisi persaingan ini menstimulasi keharusan bagi perusahaan untuk menetapkan tarif premi secara tepat, yang mampu menyesuaikan kondisi tertanggung dan mempunyai daya saing di pasar.Metode kredibilitas Buhlmann, merupakan salah satu metode kredibilitas yang dapat digunakan dalam melakukan perhitungan premi. Metode Buhlmann digunakan dalam penelitian ini untuk menghitung premi asuransi marine cargo dengan objek penelitian PT Tugu Pratama Indonesia. Proses perhitungan dilakukan dengan memprediksi ekspektasi aggregate loss dimasa yang akan datang dengan melibatkan pengalaman klaim masa lalu sebagai dasar perhitungan. Perhitungan aggregate loss dilakukan untuk tiap grup risiko, yakni grup oil, grup export import material, grup inter island material, dan grup gas and lubricant. Hasil ekpektasi aggregate loss akan digunakan untuk menghitung premi murni yang dikenakan kepada tertanggung tiap jenis risiko. Premi murni yang dihasilkan akan dibandingkan dengan premi aktual perusahaan yang digunakan perusahaan.Hasil penelitian menunjukkan bahwa premi murni untuk grup risiko oil adalah sebesar 0,098%, grup risiko export import material 0,107%, grup inter island material 0,078% dan grup gas and lubricant 0,339%. Setelah dibandingkan dengan premi aktual perusahaan, premi grup oil, grup export import material, dan grup inter island material mempunyai nilai lebih tinggi dibandingkan premi Buhlmann. Sehingga, terdapat ruang bagi perusahaan untuk menurunkan premi sampai batas premi kredibilitas Buhlmann. Sedangkan, premi grup risiko gas & lubricant mempunyai nilai di bawah premi Buhlmann. Sehingga, perusahaan dapat menaikkan premi untuk mengurangi risiko kerugian dimasa mendatang.

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ABSTRACTIn the business world, there is a competition, which requires company to adapt in order to achieve competitive advantage. Insurance business, with the number of players 85 companies, is a business with tight level of competition. This competition stimulates the requirement for companies to establish appropriate premium rates, which is able to adjust the condition of the insured and competitive in the market.Buhlmann credibility method, is one of credibility methods that can be used in premium calculation. In this research, Buhlmann method is used to calculate the premium of marine cargo insurance in PT Tugu Pratama Indonesia. Calculation process performed by predicting the expected future aggregate loss by involving past claims experience as the basis for calculation. Aggregate loss calculation is processed for each risk group, they are the group of oil, export import material group, inter-island group material, and the gas and lubricant group. Results of aggregate loss expectation will be used to calculate pure premiums that will be charged to the insured for each type of risk. Generated pure premium will be compared to the actual premium.The results showed that the pure premium for the risk group of oil is equal to 0.098%, the risk group of import export of material 0.107%, inter island group and group material 0.078% and gas & lubricant 0.339%. After compared to the company's actual premium, group premium oil, import export group material and group material inter island are greater than premium Buhlmann. Thus, there is a chance for company to reduce premiums to the extent premiums Buhlmann credibility. Meanwhile, the risk premium gas and lubricant group has a value below the premium Buhlmann. Thus, the company can raise premiums to reduce the risk of future losses., In the business world, there is a competition, which requires company to adapt in order to achieve competitive advantage. Insurance business, with the number of players 85 companies, is a business with tight level of competition. This competition stimulates the requirement for companies to establish appropriate premium rates, which is able to adjust the condition of the insured and competitive in the market.Buhlmann credibility method, is one of credibility methods that can be used in premium calculation. In this research, Buhlmann method is used to calculate the premium of marine cargo insurance in PT Tugu Pratama Indonesia. Calculation process performed by predicting the expected future aggregate loss by involving past claims experience as the basis for calculation. Aggregate loss calculation is processed for each risk group, they are the group of oil, export import material group, inter-island group material, and the gas and lubricant group. Results of aggregate loss expectation will be used to calculate pure premiums that will be charged to the insured for each type of risk. Generated pure premium will be compared to the actual premium.The results showed that the pure premium for the risk group of oil is equal to 0.098%, the risk group of import export of material 0.107%, inter island group and group material 0.078% and gas & lubricant 0.339%. After compared to the company's actual premium, group premium oil, import export group material and group material inter island are greater than premium Buhlmann. Thus, there is a chance for company to reduce premiums to the extent premiums Buhlmann credibility. Meanwhile, the risk premium gas and lubricant group has a value below the premium Buhlmann. Thus, the company can raise premiums to reduce the risk of future losses.]"

"Asuransi mobil merupakan aspek penting dalam masyarakat modern untuk melindungi individu dari kerugian finansial akibat kejadian tak terduga pada kendaraan mereka. Model penetapan tarif asuransi mobil yang digunakan sebelumnya umumnya mengasumsikan bahwa frekuensi klaim dan tingkat keparahan klaim adalah independen. Namun, seiring perkembangan waktu, penelitian lebih lanjut telah menghasilkan model klaim asuransi yang lebih canggih dengan mempertimbangkan adanya ketergantungan antara frekuensi klaim dan tingkat keparahan klaim. Meski begitu, model-model tersebut memiliki beberapa keterbatasan yang menyebabkan mereka belum mampu menangkap sepenuhnya interaksi kompleks antara frekuensi dan tingkat keparahan klaim. Selain itu, pembahasan mengenai proses yang mendasari ketergantungan tersebut masih sangat terbatas. Oleh karena itu, penelitian ini bertujuan untuk menunjukkan hubungan ketergantungan antara frekuensi klaim dan tingkat keparahan klaim, serta mempelajari dan memahami konsep bonus hunger sebagai elemen perilaku pengemudi yang menjadi fenomena umum dalam kontrak asuransi dengan sistem bonus-malus. Dalam penelitian ini, konsep bonus hunger dimasukkan ke dalam model frekuensi-keparahan klaim yang digabungkan dengan sistem bonus-malus standar dan direpresentasikan sebagai tingkat retensi optimal, yang dihitung menggunakan algoritma Lemaire. Model frekuensi-keparahan klaim ini didasarkan pada kerangka Generalized Linear Model (GLM), di mana frekuensi klaim dimodelkan menggunakan model regresi binomial negatif, sementara tingkat keparahan klaim dimodelkan menggunakan model regresi Gamma. Sementara itu, sistem bonus-malus dimodelkan dengan pendekatan model relasi tipe Bayesian. Hasil aplikasi data menunjukkan adanya hubungan ketergantungan antara frekuensi klaim dan tingkat keparahan klaim, serta mengonfirmasi fenomena bonus hunger sebagai tingkat retensi optimal dalam sistem bonus-malus.

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Automobile insurance is a necessary aspect of modern society for protecting individuals from the financial losses of their vehicles due to accidents, theft, natural disasters, or other unforeseen events. Within the automobile insurance industry, actuarial ratemaking models are essential in modeling both premiums and insurance claims for each policyholder. Earlier auto-ratemaking models have traditionally assumed independence between claim frequency and severity. Since then, subsequent studies have developed more sophisticated insurance claim models that accommodate dependence between claim frequency and severity. However, these models have several limitations that prevent them from accurately capturing the complex interactions between claim frequency and severity. Moreover, there has been little discussion as to the underlying process that causes this dependence. Therefore, this study aims to showcase the dependent relationship between claim frequency and severity, as well as study and understand bonus hunger as a behavioral element of the driver and a prevalent phenomenon in insurance contracts within the bonus-malus system. The bonus hunger is incorporated into a frequency-severity model coupled with the standard bonus-malus system and represented as an optimal retention level, calculated using the Lemaire algorithm. The frequency-severity model is based on a generalized linear model (GLM) framework in which the frequency is modeled using the negative binomial regression model. In contrast, the severity is modeled using the Gamma regression model. Meanwhile, the bonus-malus system is modeled using a Bayesian-type relativity model. The data application results show the dependent relationship between claim frequency and severity, as well as the bonus hunger phenomenon as an optimal retention level."