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Premium Estimation Using a Spliced Gamma-Gamma Distribution for Long-Tail Insurance Claims Simanjuntak, Erica Grace; Madonna, Nora; Hayati, Ma'rufah
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60648

Abstract

Determining fair premiums that accurately reflect actual risks is a crucial element in insurance risk management, particularly when claim data exhibits long-tail characteristics that are challenging to model using a single distribution. This study aims to develop a premium estimation model using the spliced Gamma-Gamma distribution, which can capture the behavior of small to large claims more flexibly. This model is applied to a collective risk model framework, focusing on calculating the expected value and variance of aggregate claims as the basis for premium estimation. Premium estimation is conducted using three actuarial principles: the expected value principle, the variance principle, and the standard deviation principle. The research indicates that the standard deviation principle yields the most accurate premium estimation, as it accurately reflects the risk level while striking a balance between premium adequacy and affordability for policyholders. This approach considers both the expected loss and its volatility, making it more adaptive to extreme claim risks. This study demonstrates that claim modelling using splicing distributions, combined with volatility-based premium estimation principles, can be a practical and realistic approach to managing risk and estimating premiums more accurately.
Pelatihan Pemanfaatan Looker Studio dalam Analisis Data dan Dashboard Statistik bagi Peningkatan Kompetensi Siswa SMKS Nurul Huda Pringsewu Rosni; Mahrani, Dwi; Fitriawati , Andi; Sofia, Ayu; Yulita, Tiara; Irawan, Agus; Mt, Ma’rufah Hayati; Mahkya, Dani Al; Nasrullah; Simanjuntak, Erica Grace; Irfan, Miftahul; Madonna, Nora; Alfian, Muhammad Nuril; Siregar, Abian Avisena; Lestari, Yushinta Cahya
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 4 No 6 (2025): November
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/jurnalkalandra.v4i6.605

Abstract

This Community Service (PkM) program aims to enhance students’ competencies in data analysis and statistical dashboard management through the utilization of the Looker Studio application. The training was conducted at SMKS Nurul Huda Pringsewu, involving students as participants. The training methods included lectures, demonstrations, and hands-on practice in processing data and presenting it in the form of interactive dashboards. The results of the program showed that students were able to understand the basic concepts of data exploration, the purpose of data visualization, and the use of key features in Looker Studio. In addition, students’ skills in selecting appropriate chart types according to analytical needs improved significantly. Based on the satisfaction survey, most participants rated the activity as very satisfactory (63%) and satisfactory (16%), although a small proportion expressed dissatisfaction (16%) or were not satisfied (5%). Overall, this PkM activity successfully contributed to improving students’ data literacy and digital skills, which are expected to support them in facing both academic challenges and the demands of a data-driven workforce