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All Journal Media Statistika Kubik Journal of Science and Applicative Technology JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Cendekia : Jurnal Pendidikan Matematika Variance : Journal of Statistics and Its Applications KUBIK: Jurnal Publikasi Ilmiah Matematika Griya Journal of Mathematics Education and Application Binawan Student Journal Enthusiastic : International Journal of Applied Statistics and Data Science Smart Society: Community Service and Empowerment Journal Jurnal Pengabdian Masyarakat Bangsa RENATA Jurnal Pengabdian Masyarakat Kita Semua JPMB Parahita Indonesian Journal of Applied Mathematics Jurnal KALANDRA TeknoKreatif: Jurnal Pengabdian kepada Masyarakat
Yulita, Tiara
Institut Teknologi Sumatera
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Perhitungan Nilai Cadangan Premi Tahunan Asuransi Jiwa Dwiguna Menggunakan Metode New Jersey dan Fackler Yulita, Tiara
Indonesian Journal of Applied Mathematics Vol. 5 No. 1 (2025): Indonesian Journal of Applied Mathematics Vol. 5 No. 1 April Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v5i1.2128

Abstract

Endowment life insurance is a type of life insurance that involves two types of benefits, namely the company will provide compensation if the insured remains alive at the end of the policy term or dies during the policy term. Premium reserves are the amount of funds that must be available to the insurance company as funds for preparing claim payments to the insured. The aim of this research is to calculate the annual premium reserve value in one of the assumed cases of Company XYZ with a coverage period of 35 years and a premium payment period of 20 years. Calculation of premium reserves can be done using a prospective and retrospective approach. The New Jersey method is included in one of the prospective premium reserve calculation methods which is an improvement and more effective than the Illinois method, with a minimum premium payment of 20 payments. The Fackler method is a calculation with a retrospective approach. The results of calculating premium reserves using the New Jersey and Fackler methods increase every year and have the same value. The results of these calculations show that the insurance company has sufficient funds to fulfill its obligations to the insured.
ESTIMASI CADANGAN KLAIM MENGGUNAKAN METODE KALMAN FILTER DENGAN STATE SPACE MODEL SCALAR PADA PRODUK ASURANSI UMUM Manurung, Chintya Carissa; Yulita, Tiara; Listiani, Amalia
KUBIK Vol 9 No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Usually, there is a delay in reporting claims from the time of the incident which results in the insurance company having a responsibility or debt. Therefore, insurance companies need to prepare funds to cover these debts, namely with claims reserves. There are two types of claim reserves, namely Incurred But Not Reported (IBNR) and Reported But Not Settled (RBNS). This research focuses on determining the estimation of aggregate claim reserves using the Kalman Filter method with scalar State Space Models (SSMs) which is a model resulting from the development of the Chain Ladder (CL) method. The Kalman Filter method with SSMs is a stochastic method that takes into account the time series model so that it can predict the temporal dynamics of a system more accurately. The results of forecasting claim reserves using the Kalman Filter method with SSMs will be compared with the CL method. Variational Of Coefficient (VOC) is an error predictor to determine the best method. The calculation results using the Kalman Filter method with SSMs produce a smaller VOC value than the CL method, proving that the Kalman Filter method with SSMs is better than CL.
Calculation of The Chain Ladder and Bornhoutter-Ferguson Methods in Calculating Claim Reserves for Insurance of Property Company in Sumatra Julianty, Dila Tirta; Yulita, Tiara; Aprilia, Inaya Sathrani
Journal of Science and Applicative Technology Vol. 9 No. 1 (2025): Journal of Science and Applicative Technology June Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/jsat.v9i1.2041

Abstract

Property insurance provides financial protection against the risk of loss due to damage or loss of insured property, such as buildings, vehicles, and equipment. Property insurance companies are required to maintain sufficient reserves to meet future claim obligations. Therefore, these companies need to accurately estimate claim reserves. This study aims to compare two methods of estimating property insurance claim reserves Chain Ladder method and Bornhuetter-Ferguson method. The data used in this research is secondary data obtained from property insurance in Sumatra, covering production and claims data from 2018 to 2023. The Chain Ladder method is a straightforward approach that uses historical claims development patterns to project future claims. The Bornhuetter-Ferguson method combines information from paid claims and estimates of the loss ratio from earned premium to predict reserves. Both methods are compared to assess their accuracy in estimating claim reserves using the Mean Absolute Percentage Error (MAPE). The results of this study indicate that the Bornhuetter-Ferguson method provides better estimates of claim reserves compared to the Chain Ladder method.
Penyuluhan Perencanaan Keuangan Keluarga Berbasis OJK di Masa Pandemik Kepada Masyarakat Korban Banjir Sungai Ciliwung: Counseling of Planning the Family Finance During the Pandemic to the Ciliwung River Flood Victim Communities Tiara Yulita; Divira Iga Firdianti
Jurnal Pengabdian Masyarakat Bakti Parahita Vol. 2 No. 01 (2021): Jurnal Pengabdian Masyarakat Bakti Parahita
Publisher : Universitas Binawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54771/jpmbp.v2i01.197

Abstract

Di masa pandemik, salah satu dampak negatif bagi sebagian besar warga negara Indonesia adalah berkurangnya pendapatan mereka sehari-hari maupun per bulan, sedangkan pengeluaran lebih banyak daripada sebelumnya antara lain digunakan untuk membeli obat-obatan, vitamin, tambahan makanan bergizi dan lain sebagianya. Subjek dari kegiatan ini adalah warga Sungai Ciliwung yang terkena musibah banjir karena meluapnya Sungai Ciliwung. Penyuluhan ini bertujuan agar warga dapat merencanakan keuangan keluarga dengan sebaik mungkin, efisien dan efektif sesuai dengan kondisi keuangan keluarga masing-masing, sehingga tercipta keluarga yang sehat dan sejahtera. Kegiatan penyuluhan dilakukan secara tatap muka (offline) dengan metode ceramah, memberikan contoh yang relevan, dan tanya jawab tentang bagaimana cara menerapkan pola-pola perencanaan keuangan keluarga yang merujuk pada publikasi dari Otoritas Jasa Keuangan (OJK) sebagai lembaga pengawas jasa keuangan terkemuka di Indonesia. Hasil dari kegiatan ini, sebagian besar warga mulai mengerti dan memahami bagaimana cara mengatur keuangan dimana diukur dengan menggunakan kuesioner, serta terlihat bahwa warga sangat memperhatikan dan antusias baik ketika penyampaian materi maupun tanya jawab dimana banyak pertanyaan yang muncul dari warga. Kesimpulan yang dapat diperoleh adalah pemahaman warga tentang pengelolaan keuangan keluarga secara signifikan meningkat dari sebelum dilakukan kegiatan yang diukur dengan pre-test dan post-test. Kendala yang dihadapi yaitu perlunya pendampingan evaluasi setiap bulan terhadap implementasi dari perencanaan keuangan keluarga yang telah ditetapkan sebelumnya.
PENENTUAN PREMI MURNI DARI DATA KLAIM ASURANSI KENDARAAN RODA EMPAT DENGAN JENIS PERLINDUNGAN COMPREHENSIVE Yulita, Tiara; Patricia, Mitha; Hidayat, Agus Sofian Eka
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss1page75-86

Abstract

Produk asuransi kendaraan bermotor sudah banyak digunakan oleh banyak orang karena semakin banyak yang membutuhkan untuk meminimalkan risiko yang didapat oleh pihak tertanggung. Sehingga pihak tertanggung perlu membayarkan kewajiban berupa premi serta mengikuti syarat dan ketentuan yang telah disepakati bersama sebelumnya, untuk mendapatkan haknya berupa pembayaran klaim ketika terjadi suatu kejadian yang merugikan tertanggung. Besarnya premi dapat dilihat dari berbagai faktor seperti jenis perlindungannya yaitu Total Loss Only dan Comprehensive, usia kendaraan, riwayat klaim sebelumnya, dan faktor-faktor lainnya. Pada penelitian ini perhitungan yang dilakukan adalah perhitungan premi yang menggunakan data riwayat klaim dari asuransi kendaraan roda empat periode 2020-2022 dengan jenis perlindungan comprehensive dengan menggunakan metode compound model. Dimana data banyak klaim mengikuti model distribusi Negative Binomial, dan data besar klaim mengikuti model distribusi Lognormal. Selanjutnya nilai ekspektasi dari kedua distribusi ini akan dikalikan untuk menentukan premi murni dari asuransi kendaraan roda empat.
COMPARISON OF THE CHAIN LADDER AND BORNHOUTTER-FERGUSON METHODS IN CALCULATING CLAIM RESERVES FOR REINSURANCE COMPANY IN INDONESIA Yulita, Tiara; Julianty, Dila Tirta; Aprilia, Inaya Sathrani; Inayah, Larasati Nurul
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page155-166

Abstract

In the insurance industry, calculating claims reserves plays a crucial role in managing both risk and the financial stability of an insurance company. When a claim is filed, the insurer must allocate a reserve fund to anticipate potential future losses. In general insurance, claim settlements are often not completed immediately because there is usually a time gap between the occurrence of an incident and the reporting of the claim. Unresolved claims create liabilities or obligations for the insurance company. These allocated funds are referred to as claim reserves, which are generally categorized into two types: Incurred but Not Reported (IBNR) and Reported but Not Settled (RBNS). This research focuses on determining estimates of claim reserves using the Chain Ladder and Bornhuetter-Ferguson methods for loss insurance data for the property business class of reinsurance companies in Indonesia for the period 2011 to 2021. The results show that the claims reserves for each method are IDR 2,499,456,710,993 and IDR 2,266,000,657,647 with MAPE value of 1.38% and 2.10%. The results of the MAPE value calculation show that the claim reserves estimate using the Chain Ladder method is better than the Bornhuetter-Ferguson method.
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
Determination Premiums Motor Vehicle Insurance Using Bonus-Malus Optimal Listiani, Amalia; Patricia, Mitha; Yulita, Tiara
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art2

Abstract

The increasing number of motor vehicles in Sumatera has heightened accident risks, emphasizing the need for motor vehicle insurance to distribute risk between policyholders and insurers. Determining fair and risk-based premium requires consideration of each policyholder’s claim history. This study aimed to determine motor vehicle insurance premiums using the optimal bonus-malus system based on claim data for the minibus category with comprehensive coverage in Sumatera during 2022. The proposed model extended the Bayesian bonus-malus framework by incorporating the trust region reflective (TRR) method for estimating claim severity and the Newton-Raphson method for estimating claim frequency, thereby enhancing parameter estimation accuracy and numerical stability. This approach offers a more equitable and precise premium adjustment mechanism aligned with individual risk levels, contributing to improved risk-based pricing, reduced underwriting losses, and greater transparency for policyholders. The results showed that the claim frequency followed the Poisson-Lindley distribution, while claim severity followed the lognormal-gamma distribution. Based on these models, the premium was computed by multiplying the basic premium by the relative value of the subsequent year and dividing it by the base relative value. Premium decrease in the absence of claims and increase when claims occur.
Empowering the Future: AI-Based Website Development Training to Boost High School Students' Creativity and Digital Skills Luluk Muthoharoh; Yuliana Yuliana; Linda Rassiyanti; Ade Lailani; Ayu Sofia; Tiara Yulita; Dharu Cahyoaji Sasongko; Khairunnisa Maharani; Aditya Rahman
Smart Society Vol. 5 No. 1 (2025): Smart Society
Publisher : FOUNDAE (Foundation of Advanced Education)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/smartsociety.v5i1.658

Abstract

In the rapidly evolving digital era, Artificial Intelligence (AI) has become one of the key technologies playing a significant role in various fields, including website development. AI-based website development training is a strategic step to enhance the skills and creativity of the younger generation in the era of digitalization. This activity was conducted at SMA Al Huda, South Lampung, with the aim of equipping students with an understanding of basic concepts, steps for creating websites, and how AI can be utilized to enhance creativity in the digital world. The methods used included interactive presentations, demonstrations, hands-on practice, and discussions. The activity also assessed students' knowledge before and after the training through an interactive quiz using Quizizz. The results of the study showed a significant improvement in students' understanding of AI-based website development. In conclusion, this training program was effective in enhancing students' skills and creativity in the digitalization world, particularly in creating AI-based websites
Comparison of Mack Chain-Ladder and Bootstrap Methods for Claim Reserve Estimation under IFRS 17 in Lampung General Insurance Tiara Yulita; Putri Isnaini Cahyaning Baiti; Dila Tirta Julianty; Ayu Sofia; Dwi Mahrani; M. Naufal Athaatmaja
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 3 (2026): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i3.38485

Abstract

Claim  reserves are funds set aside by insurance companies to pay for reported claims (RBNS) as well as claims that have not yet been reported (IBNR), and they are crucial because they directly affect the financial health of the company. In 2024, there were customer complaints in Lampung regarding delays in claim payments by general and life insurance companies. Therefore, this study uses claim data from general insurance companies in Lampung for the period 2013–2024. The novelty of this study lies in comparing the Mack Chain Ladder analytical method and the Bootstrap simulation method for estimating claim reserves within the IFRS 17 framework using regional insurance data from Lampung, which has not been widely explored in previous studies. This study aims to estimate claim reserves and estimate the Liability for Incurred Claims (LIC),The objective of this study is to compare claim reserve values using an analytical approach (Mack Chain-Ladder) and a simulation approach (Bootstrap), implemented in accordance with the International Financial Reporting Standard (IFRS) 17. The IFRS 17 components to be calculated include the Liability for Incurred Claims (LIC) , Best Estimate Liability (BEL), and Risk Adjustment (RA) under IFRS 17. . Accurate estimation of claim reserves and the implementation of IFRS 17 play a vital role in ensuring the sustainability of insurance companies. The Mack Chain-Ladder (MCL) method is used to obtain equations for the expected value and variance of future claims as well as the prediction error rate. Meanwhile, the Bootstrap method generates numerous simulated claim datasets that reflect various possible scenarios. The advantage of the simulation approach is its ability to provide a full predictive distribution, which can be used to estimate the risk adjustment under IFRS 17. The empirical results show that the estimated claim reserve using the Mack Chain-Ladder (MCL) method is 234,740,644, while the Bootstrap method with 5.000 simulations produces a reserve range ofIn addition, this study also discusses methods for calculating capital requirements based on Value at Risk and for estimating risk adjustment using risk measures applied to the simulated distribution of claim liabilities over the contract period. 233,158,004-236,320,156. These results provide empirical insights into claim reserve estimation and support the implementation of IFRS 17 in regional insurance companies by calculating the BEL, RA, and LIC values, whose results are based on the claim reserve calculation .
Co-Authors Ade Lailani Adhitya Ronnie Effendie, Adhitya Ronnie Aditya Rahman Agus Irawan Agus Irawan Agus Sofian Eka Hidayat Agus Sofian Eka Hidayat Alfian, Muhammad Nuril Amalia Listiani Andi Fitriawati Aprilia, Inaya Sathrani Ayu Sofia Ayu Sofia Azzanina, Nanda Baiti, Putri Isnaini Cahyaning Berliana Ratam, Aldila Nur Indah Chaterine Theresia Lubis Chintya Carissa Manurung Dani Al Mahkya Dani Al Mahkya Dewi, Karina Sylfia Dharu Cahyoaji Sasongko Dila Tirta Julianty Divira Iga Firdianti Dwi Mahrani Erica Grace Simanjuntak Fitriawati , Andi Fuji Lestari Gilang Primajati Gustina K. S, Annisa Hevita Hardi Suyitno Hidayat, Agus Sofian Eka Inayah, Larasati Nurul Indah Gumala Andirasdini Irfan, Miftahul Irwan, Sri Efrinita Khairunnisa Maharani Lestari, Yushinta Cahya Linda Rassiyanti Listiani, Amalia Luluk Muthoharoh M. Naufal Athaatmaja Madonna, Nora Manurung, Chintya Carissa Marisa Marisa Ma’rufah Hayati Miftahul Irfan Miftha Ulya Nazima Mt, Ma’rufah Hayati Muklas Rivai Nasrullah Nasrullah Nasrullah Nora Madonna Patricia, Mitha Putri Isnaini Cahyaning Baiti Rivai, Muklas Rosni Rosni Rosni, Rosni Siregar, Abian Avisena Sitorus, Kristiani Sugiman Sugiman Yuliana Yuliana Yushinta Cahya Lestari