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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.
Empowering the Future: AI-Based Website Development Training to Boost High School Students' Creativity and Digital Skills Muthoharoh, Luluk; Yuliana, Yuliana; Rassiyanti, Linda; Lailani, Ade; Sofia, Ayu; Yulita, Tiara; Sasongko, Dharu Cahyoaji; Maharani, Khairunnisa; Rahman, Aditya
Smart Society Vol 5, No 1 (2025): June (2025)
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
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.
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 : Department of Mathematics, Faculty of Science and Technology, 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
Pemanfaatan Looker Studio untuk Mengembangkan Kompetensi Analisis dan Visualisasi Data Siswa SMKS Nurul Huda Pringsewu Rosni, Rosni; Madonna, Nora; Fitriawati, Andi; Al Mahkya, Dani; Irawan, Agus; Simanjuntak, Erica Grace; Hayati, Ma’rufah; Nasrullah, Nasrullah; Irfan, Miftahul; Mahrani, Dwi; Sofia, Ayu; Yulita, Tiara; Rivai, Muklas
Jurnal Pengabdian Masyarakat Bangsa Vol. 4 No. 1 (2026): Maret
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v4i1.4194

Abstract

Kemampuan dalam memanfaatkan teknologi, khususnya dalam eksplorasi dan visualisasi data, menjadi tantangan signifikan dalam dunia pendidikan di era digital saat ini. SMKS Nurul Huda Pringsewu sebagai mitra kegiatan pengabdian menunjukkan adanya keterbatasan kompetensi siswa dalam mengolah data dan menyajikannya dalam bentuk visual yang informatif. Menanggapi permasalahan tersebut, tim Pengabdian kepada Masyarakat (PkM) melaksanakan pelatihan menggunakan aplikasi Looker Studio untuk eksplorasi data dan pembuatan dashboard statistik. Looker Studio merupakan platform berbasis web yang memudahkan pengguna dalam mengolah data numerik dan menyajikannya secara visual, sehingga proses pembacaan data tidak lagi dilakukan secara manual. Pelatihan ini bertujuan untuk meningkatkan kemampuan siswa dalam mengolah dan memvisualisasikan data menggunakan teknologi terkini. Hasil dari kegiatan ini menunjukkan peningkatan kompetensi siswa dalam mengeksplorasi data statistik serta peningkatan kualitas pembuatan dashboard yang lebih informatif dan menarik. Kegiatan ini diharapkan dapat menjadi langkah awal dalam membekali siswa dengan keterampilan digital yang relevan dengan kebutuhan industri saat ini.