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All Journal EKSAKTA: Journal of Sciences and Data Analysis Statistika Jurnal Ekonomi Modernisasi JURNAL PENGABDIAN KEPADA MASYARAKAT BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED ACCOUNTING AND TAXATION Jurnal Vokasi Indonesia Indonesian Journal of Applied Informatics Jurnal Administrasi Bisnis Terapan Jurnal Statistika dan Matematika (Statmat) Mathematics and Applications (MAp) Journal Journal of Fundamental Mathematics and Applications (JFMA) STATISTIKA Jurnal Vokasi Indonesia
Yulial Hikmah
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ESTIMASI CADANGAN KLAIM IBNR MENGGUNAKAN METODE CHAIN-LADDER DAN BORNHUETTER-FERGUSON PADA PRODUK INDEMNITY DI PT. XYZ Raisha Amini; Yulial Hikmah
MAp (Mathematics and Applications) Journal Vol 4, No 1 (2022)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v4i1.4203

Abstract

Klaim IBNR (Incurred But Not Reported) adalah klaim yang sudah terjadi namun belum dilaporkan. Karena belum dilaporkan, maka totalnya diakumulasikan dalam bentuk cadangan dan dianggap sebagai kewajiban bagi perusahaan asuransi karena sudah terjadi. Klaim yang sudah terjadi namun belum dilaporkan ini disebabkan oleh keterlambatan atau disebut lag/jarak yang disebabkan oleh berbagai faktor. Setiap produk asuransi memiliki lag yang berbeda-beda. Perusahaan asuransi tidak mempunyai data keterlambatan tersebut sehingga data tersebut dapat dibentuk dari data klaim historis menggunakan run-off triangle. Tujuan dari run-off triangle adalah mengetahui berapa lama yang dibutuhkan dari suatu klaim yang terjadi sampai klaim tersebut dilaporkan. Data klaim historis dalam bentuk run-off triangle disebut sebagai incurred sehingga diperoleh gambaran pengalaman klaim dan data tersebut digunakan untuk mengestimasikan masa depan dengan tujuan untuk mendapatkan estimasi ultimate loss. Estimasi ultimate loss adalah estimasi total klaim jika sudah full terlaporkan. Jika sudah didapatkan estimasi ultimate loss dan incurred, maka selisihnya merupakan cadangan klaim yang sudah terjadi namum belum dilaporkan atau IBNR. Terdapat banyak metode untuk memperhitungkan cadangan klaim IBNR. Beberapa Metode yang dapat digunakan adalah dengan metode Chain-Ladder dan Bornhuetter-Ferguson. Hasil menunjukkan bahwa metode Bornhuetter-Ferguson lebih sesuai pada pehitungan cadangan klaim untuk produk indemnity di PT. XYZ. Hal ini disebabkan oleh data klaim historis di penelitian ini memiliki rata-rata waktu penundaan pelaporan klaim lebih dari dua hingga tiga bulan serta estimasi cadangan klaim dengan metode Bornhuetter-Ferguson menghasilkan cadangan klaim lebih besar dibandingkan dengan metode Chain-Ladder. Oleh karena itu, PT. XYZ akan lebih aman untuk menghindar risiko kekurangan cadangan jika menerapkan metode Bornhuetter-Ferguson dibandingkan dengan metode Chain-Ladder.
Proses Klaim Produk Director & Officers (D&O) Liability Insurance di Indonesia Yulial Hikmah
Jurnal Ekonomi Modernisasi Vol. 15 No. 3 (2019): Oktober
Publisher : Fakultas Ekonomika dan Bisnis, Universitas Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (280.344 KB) | DOI: 10.21067/jem.v15i3.4323

Abstract

D&O (Directors & Officers) liability insurance is a protection of guarantees for Directors and Company officials (the insured) for losses arising from third party claims due to negligence around managerial or operational matters carried out by the insured. This study discusses the process of settling claims for D&O liability insurance products, claim adjustments in compensation calculations, and provisions in policies that are considered adjustments to compensation calculations. This research was conducted by interview, observation and literature study. The claim process begins with claims from third parties to the insured, and must be reported directly to the guarantor (insurance company) as soon as possible. After the report is received by the guarantor, the guarantor will begin to follow up on the claim by conducting a survey of claim investigation and collecting supporting documents needed. Furthermore, the guarantor will make a decision whether the claim submitted by the insured is guaranteed or not based on the provisions of the policy. If the claim is rejected, a rejection notice will be sent. However, if it turns out that the claim is declared guaranteed, a claim approval notice will be sent to subsequently make a claim payment. Adjustment in the calculation of compensation is needed to optimize the amount of compensation issued by the insurance company so that it can be minimized in order to achieve corporate profits.
Klasifikasi Minat Korban Banjir terhadap Pembelian Produk Asuransi Dampak Banjir Menggunakan Software Orange (Studi Kasus: Kota Jakarta Timur) Ira Rosianal Hikmah; Yulial Hikmah
IJAI (Indonesian Journal of Applied Informatics) Vol 6, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v6i1.55621

Abstract

Hampir semua kota di Indonesia mengalami banjir setiap tahun, termasuk DKI Jakarta. Berdasarkan data Badan Nasional Penanggulangan Bencana (BNPB) tahun 2020, Kota Jakarta Timur merupakan kota yang rawan banjir. Banjir merupakan bencana yang relatif paling banyak menimbulkan kerugian. Kerugian yang diakibatkan oleh banjir, terutama kerugian tidak langsung, dapat menempati urutan pertama atau kedua setelah gempa bumi atau tsunami. Menurut BNPB, Kota Jakarta Timur terkena dampak banjir terparah saat bencana banjir awal tahun 2020. Oleh karena itu, perlu adanya upaya mitigasi bencana untuk meminimalisir kemungkinan terjadinya risiko banjir. Salah satu mitigasi risiko akibat bencana banjir adalah dengan membeli produk asuransi dampak banjir sebagai upaya pemidahan risiko yang mungkin akan terjadi. Namun, tidak semua orang membeli produk asuransi dampak banjir karena faktor ekonomi dan sosial. Penelitian ini bertujuan untuk melakukan prediksi terhadap minat penduduk Kota Jakarta Timur terutama yang mengalami banjir terhadap pembelian produk asuransi dampak banjir. Oleh karena itu, penelitian ini menggunakan algoritma supervised learning dengan tujuh pilihan model dan diperoleh tiga model yang dapat direkomendasikan adalah model Random Forest, Naive Bayes, dan SVM yang diperoleh berdasarkan kriteria evaluasi yaitu waktu yang dibutuhkan untuk training dan testing, tingkat akurasi, dan presisi, serta kurva ROC. Almost all cities in Indonesia experience flooding every year, including DKI Jakarta. Based on data from the National Disaster Management Agency (BNPB) in 2020, East Jakarta City is a city that is prone to flooding. Flooding is a disaster that relatively causes the most losses. Losses caused by floods, especially indirect losses, can rank first or second after an earthquake or tsunami. According to BNPB, East Jakarta City was worst affected by flooding during the early 2020 flood disaster. Therefore, disaster mitigation efforts are needed to minimize the possibility of flood risk. One of the risk mitigations due to floods is to buy flood impact insurance products to transfer risks that may occur. However, not everyone buys flood impact insurance products due to economic and social factors. This study aims to predict the interest of residents of East Jakarta City, especially those who experience flooding, to purchase flood impact insurance products. Therefore, this study used a supervised learning algorithm with seven model choices and obtained three models that can be recommended, namely the Random Forest, Naive Bayes, and SVM models obtained based on the evaluation criteria, namely the time required for training and testing, the level of accuracy, and precision, as well as the ROC curve.
Klasifikasi Minat Korban Banjir terhadap Pembelian Produk Asuransi Dampak Banjir Menggunakan Software Orange (Studi Kasus: Kota Jakarta Timur) Ira Rosianal Hikmah; Yulial Hikmah
IJAI (Indonesian Journal of Applied Informatics) Vol 6, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v6i2.73163

Abstract

AbstrakHampir semua kota di Indonesia mengalami banjir setiap tahun, termasuk DKI Jakarta. Berdasarkan data Badan Nasional Penanggulangan Bencana (BNPB) tahun 2020, Kota Jakarta Timur merupakan kota yang rawan banjir. Banjir merupakan bencana yang relatif paling banyak menimbulkan kerugian. Kerugian yang diakibatkan oleh banjir, terutama kerugian tidak langsung, dapat menempati urutan pertama atau kedua setelah gempa bumi atau tsunami. Menurut BNPB, Kota Jakarta Timur terkena dampak banjir terparah saat bencana banjir awal tahun 2020. Oleh karena itu, perlu adanya upaya mitigasi bencana untuk meminimalisir kemungkinan terjadinya risiko banjir. Salah satu mitigasi risiko akibat bencana banjir adalah dengan membeli produk asuransi dampak banjir sebagai upaya pemidahan risiko yang mungkin akan terjadi. Namun, tidak semua orang membeli produk asuransi dampak banjir karena faktor ekonomi dan sosial. Penelitian ini bertujuan untuk melakukan prediksi terhadap minat penduduk Kota Jakarta Timur terutama yang mengalami banjir terhadap pembelian produk asuransi dampak banjir. Oleh karena itu, penelitian ini menggunakan algoritma supervised learning dengan tujuh pilihan model dan diperoleh tiga model yang dapat direkomendasikan adalah model Random Forest, Naive Bayes, dan SVM yang diperoleh berdasarkan kriteria evaluasi yaitu waktu yang dibutuhkan untuk training dan testing, tingkat akurasi, dan presisi, serta kurva ROC.AbstractAlmost all cities in Indonesia experience flooding every year, including DKI Jakarta. Based on data from the National Disaster Management Agency (BNPB) in 2020, East Jakarta City is a city that is prone to flooding. Flooding is a disaster that relatively causes the most losses. Losses caused by floods, especially indirect losses, can rank first or second after an earthquake or tsunami. According to BNPB, East Jakarta City was worst affected by flooding during the early 2020 flood disaster. Therefore, disaster mitigation efforts are needed to minimize the possibility of flood risk. One of the risk mitigations due to floods is to buy flood impact insurance products to transfer risks that may occur. However, not everyone buys flood impact insurance products due to economic and social factors. This study aims to predict the interest of residents of East Jakarta City, especially those who experience flooding, to purchase flood impact insurance products. Therefore, this study used a supervised learning algorithm with seven model choices and obtained three models that can be recommended, namely the Random Forest, Naive Bayes, and SVM models obtained based on the evaluation criteria, namely the time required for training and testing, the level of accuracy, and precision, as well as the ROC curve.
PERHITUNGAN PREMI ASURANSI JIWA DWIGUNA DIBAYARKAN PADAAKHIR TAHUN KEMATIAN DENGAN MENGGUNAKAN PACKAGE PERANGKAT LUNAK R Hikmah, Yulial; Hikmah, Ira Rosianal
Jurnal Vokasi Indonesia Vol. 8, No. 2
Publisher : UI Scholars Hub

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

Abstract

In calculating premiums, many insurance companies use commutation tables. Premium calculation can also be done with R software by making the function. Besides that, there is a set of packages available to make it efficient in solving various problems. One of the R packages in the field of insurance and actuarial is lifecontingencies, which can be used to manage life tables, actuarial tables, and perform calculations in actuarial mathematics. To calculate premiums for some customers, the use of lifecontingencies package is more efficient in terms of time because the calculations are carried out simultaneously for all customers compared to calculations using commutation tables manually. Therefore, this research discusses how to calculate the annual premium on an n-year end-to-end life insurance product by using a commutation table manually and by using the lifecontingencies package in Software R based on the illustration given. The results show that by using the commutation table manually and by using lifecontingencies package, the premium calculation results are the same. So, it can be concluded that the calculation of the premium with lifecontingencies package on R is better than the manual calculation because the premium results are the same but with a shorter time.
PERHITUNGAN PREMI LANJUTAN (RENEWAL PREMIUM) PADA ASURANSI KESEHATAN KUMPULAN MENGGUNAKAN METODE EXPERIENCE RATING DI PT ABC Clarissa, Putri Rumondang; Hikmah, Yulial; Hikmah, Ira Rosianal
MAp (Mathematics and Applications) Journal Vol 6, No 1 (2024)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v6i1.8556

Abstract

Asuransi Kesehatan merupakan suatu perlindungan keuangan untuk memberikan jaminan atas biaya pengobatan dan perawatan medis yang dibutuhkan seseorang ketika sakit. Asuransi Kesehatan dibagi menjadi dua kategori, yaitu Asuransi Kesehatan Individu dan Asuransi Kesehatan Kumpulan. Asuransi Kesehatan Kumpulan ditujukan untuk para karyawan dengan Perusahaan Pemberi Kerja sebagai pemegang polisnya. Pada umumnya, Asuransi Kesehatan Kumpulan memiliki kontrak polis yang berjangka satu tahun, dimana ketika polis tersebut sudah berakhir, maka akan dilakukan evaluasi ulang untuk menentukan premi lanjutan (renewal premium). Terdapat beberapa metode yang dapat digunakan untuk menetapkan tarif premi lanjutan pada Asuransi Kesehatan Kumpulan, diantaranya manual rating, experience rating, dan blended rating. Umumnya, perusahaan asuransi menggunakan metode experience rating untuk menghitung premi lanjutan karena metode ini menggunakan data pengalaman klaim dan biaya-biaya yang terjadi di masa lalu. Pada penelitian ini dijelaskan bagaimana proses perhitungan premi lanjutan menggunakan metode experience rating dengan loss ratio. Hasil menunjukkan bahwa proses perhitungan dapat dilakukan dengan empat tahap, yaitu: menghitung loss ratio, menghitung permissible loss ratio, menghitung gross rate, dan terakhir menghitung premi lanjutan (renewal premium). Berdasarkan studi kasus di PT ABC, akan diberikan dua kemungkinan dalam penentuan besar premi lanjutan. Kemungkinan pertama yaitu besar premi lanjutan akan naik (meningkat) dari premi awal. Sementara, kemungkinan keduanya yaitu besar premi lanjutan akan tetap sama pada premi awal sebelumnya. Semakin tinggi besar klaim daripada besar premi pada suatu polis, maka akan semakin tinggi juga kemungkinan premi lanjutan (renewal premium) pada polis tersebut.
The Effect of The Mortality Rate Multiplier on Determination of Contribution to Sharia Group Life Insurance Using TMI III and TMI IV at PT Asuransi Jiwa ABC Jihan Khafidhotin Najah; Hikmah, Yulial; Karin Amelia Safitri; Fia Fridayanti Adam
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.4123

Abstract

Abstract. The human mortality rate is an important factor in determining premiums. Information about mortality rates can be obtained through mortality tables that describe the probability or the probability of individual deaths. This study examines the effect of the mortality rate multiplier on gross premium determination in sharia-term life insurance using TMI III and TMI IV at PT Asuransi Jiwa ABC. This research method includes data analysis in the form of claim estimation data and claim realization data for several years from members in the Sharia group term life insurance products. The results of the analysis show that the difference in the mortality rate multiplier value between TMI III and TMI IV affects the gross premium value, especially in certain age ranges, there is a mortality rate value in TMI III that is greater than that in TMI IV, but the resulting premium value is the opposite: the premium in TMI IV is greater than the premium value in TMI III.
EXPERIENCE STUDY: EFFECT OF UNDERWRITING METHODS ON MORTALITY RATE FOR LIFE INSURANCE PRODUCT AT PT. ABC (2015-2020 PERIOD) Imani, Alvira Adya; Hikmah, Yulial
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.806 KB) | DOI: 10.30598/barekengvol16iss1pp031-040

Abstract

In creating complex mortality tables, some insurance companies do not have enough data to build credible tables based on their experiences. Therefore, insurance companies usually carry out their analysis by comparing the company's actual mortality rate with the expected mortality rate based on industry tables, which is the "A/E ratio". This study aims to determine the best estimates for the mortality rate in PT ABC's underwriting method and its effect on the mortality rate and gross premium. The method used is the actual to expected analysis (A/E Ratio) method. The results of the research and analysis conclude that the more complex the underwriting process assigned to a product, the lower the mortality rate and gross premium.
LOGISTIC MODELING TO PREDICT THE INTEREST OF THE INDONESIAN PEOPLE FOR BUYING FLOOD IMPACTED INSURANCE PRODUCTS Hikmah, Yulial
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.749 KB) | DOI: 10.30598/barekengvol17iss1pp0323-0330

Abstract

Indonesia is a country located on the equator and in the form of an archipelago. It has a high potential for various types of hydrometeorological-related disasters, such as floods, flash floods, droughts, extreme weather, etc. Almost all cities in Indonesia experience flooding every year, including DKI Jakarta, the capital city of Indonesia. Based on data from the National Disaster Management Agency (BNPB) in 2020, East Jakarta is a city that is prone to flooding. According to BNPB (2013), flooding is a disaster that relatively causes the most losses. Losses caused by floods, especially indirect losses, may rank first or second after an earthquake or tsunami. Floods cause so many losses, and it is necessary to have disaster mitigation efforts to minimize the possibility of flood risks. One risk mitigation due to natural disasters is buying insurance products. However, not everyone buys flood-impact insurance products due to economic and social factors. This study aims to create a model with the Logistics Regression Model to determine the factors influencing Indonesian people's interest in purchasing flood-impact insurance products. The research data is from 140 households in East Jakarta, Indonesia, using a non-probability purposive sampling technique. Furthermore, with a significance level of 10%, the logistic regression model obtained 14 significant regression coefficients. In the end, the obtained model is evaluated based on its level of accuracy. The results showed that the accuracy rate was almost excellent, namely 89.3%.
Co-Authors Adam, Fia Fridayanti Birawani Dwi Anggraeni Clarissa, Putri Rumondang Imani, Alvira Adya Ira Rosianal Hikmah Isriani Isriani Jihan Khafidhotin Najah Julyet Cipta Fauziyah Kasim, Elsie Sylviana Raisha Amini Safitri, Karin Amelia Sandra Aulia