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All Journal Nusantara Hasana Journal
Nanda Azzanina
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Agriculture, Biological Sciences & Forestry Humanities Economics, Econometrics & Finance Education Nursing

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PEMODELAN PREMI ASURANSI BERDASARKAN DATA SEVERITY MENGGUNAKAN MODEL LOGNORMAL Cahyaning Baiti, Putri Isnaini; Annisa Hevita G.K.S; Karina Sylfia Dewi; Nanda Azzanina
Nusantara Hasana Journal Vol. 5 No. 3 (2025): Nusantara Hasana Journal, August 2025
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v5i3.1603

Abstract

The insurance industry in Indonesia requires reliable quantitative approaches to accurately determine premium rates and manage claim risks effectively. This study aims to model pure insurance premiums based on claim severity data using the lognormal regression approach. The data used consist of historical individual claim amounts (severity) obtained from a general insurance company in Indonesia, covering the period from 2009 to 2015. Initial data exploration revealed that the distribution of claim values is positively skewed, indicating the suitability of lognormal modeling. Three models were evaluated: Generalized Linear Model (GLM) with Gamma distribution, GLM with Inverse Gaussian distribution, and linear regression with lognormal transformation. Model selection was based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The results show that the lognormal model had the lowest AIC and BIC values, indicating superior performance compared to the other models. The selected model was then used to forecast pure premiums for the next 12 months, followed by the calculation of commercial premiums with a 30% loading factor. The prediction results show a consistent and proportional upward trend in premiums, demonstrating the model’s effectiveness in capturing historical claim patterns and supporting data-driven premium setting.
PERAMALAN CONSTRUCTION COST INDEX (CCI) DI INDONESIA MENGGUNAKAN MODEL SEASONAL ARIMA Indriyani, Armelia; Nanda Azzanina
Nusantara Hasana Journal Vol. 5 No. 11 (2026): Nusantara Hasana Journal, April 2026
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v5i11.1932

Abstract

The construction sector is a crucial pillar of Indonesia's economic development, reflected in its contribution to Gross Domestic Product (GDP). The Construction Cost Index (CCI) is closely related to this sector as an indicator of changes in construction costs over time. Fluctuations in the CCI, influenced by trends, seasonal patterns, and external factors, pose challenges in project cost planning, necessitating an accurate forecasting method. This study applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) to forecast the quarterly CCI for the period 2010–2024, as published by Badan Pusat Statistik (BPS). The analysis includes stationarity testing, model identification using ACF and PACF, parameter estimation, diagnostic testing, and model selection based on MAPE. The best model is  with a MAPE of less than 10%, indicating excellent accuracy. The results are expected to serve as a reference for cost planning and risk reserves for construction projects in Indonesia.
Co-Authors Cahyaning Baiti, Putri Isnaini Gustina K. S, Annisa Hevita Indriyani, Armelia Karina Sylfia Dewi