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Leksikostatistik Bahasa Aceh, Bahasa Alas, dan Bahasa Gayo: Kajian Linguistik Historis Komparatif SARI, KURNIA NOVITA
SULUK INDO Volume 2, Nomor 1, Tahun 2013
Publisher : Sastra Indonesia, Fakultas Ilmu Budaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.73 KB)

Abstract

Leksikostatistik yaitu suatu teknik yang berusaha menemukan keterangan-keterangan atau data-data untuk suatu tingkat waktu yang tua dalam bahasa gunamenentukan usia bahasa dan pengelompokan bahasa-bahasa (Keraf, 1996:121122).Penelitian ini mengkaji bahasa Aceh, bahasa Alas, dan bahasa Gayo yangtermasuk ke dalam rumpun Austronesia atau Melayu Polinesia. Asumsi mengenaikekerabatan ketiga bahasa yakni pada kenyataan adanya kesamaan dan kemiripandalam bentuk dan makna yang merupakan pantulan dari warisan sejarah yangsama.  Hubungan kekerabatan dan waktu pisah antara bahasa Aceh, bahasa Alas,dan bahasa Gayo dalam penelitian ini dikaji dengan menggunakan metodepengelompokan bahasa serta teknik leksikostatistik. Tahap pertama,mengumpulkan 300 kosakata dasar yang disusun oleh Morris Swades. Metodeyang digunakan dalam penyediaan data ini adalah metode referensial, sedangkanteknik yang digunakan adalah teknik catat. Kedua, menetapkan pasanganpasanganmanadariketigabahasatadiyangmerupakanbahasakerabat(cognate).Ketiga,menghitung usia dan waktu pisah ketiga bahasa. Keempat, menghitungjangka kesalahan untuk menetapkan waktu pisah yang lebih tepat. Hasil penelitian menunjukan bahwa bahasa Aceh, bahasa Alas, dan bahasaGayo termasuk dalam kategori keluarga (family) bahasa. Persentase kata kerabatbahasa Aceh dan bahasa Alas sebesar 53%, bahasa Aceh dan bahasa Gayo sebesar57%, bahasa Alas dan bahasa Gayo sebesar 62%. Bahasa Aceh dan bahasa Alasmerupakan bahasa tunggal pada 1590-1336 tahun yang lalu, diperkirakan mulaiberpisah dari bahasa Proto kira-kira tahun 422-676 M. Bahasa Aceh dan bahasaGayo merupakan bahasa tunggal pada 1411-1177 tahun yang lalu, diperkirakanmulai berpisah dari bahasa Proto kira-kira tahun 601-835 M. Bahasa Alas dan bahasa Gayo merupakan bahasa tunggal pada 1207-995 tahun yang lalu,diperkirakan mulai berpisah dari bahasa Proto kira-kira tahun 805-1017 M(dihitung pada tahun 2012).
Pemodelan Besar Klaim menggunakan Distribusi Berekor dan Tail-Value-at-Risk (TVaR) pada Data Sampel Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan Widodo, Vicko Regenio; Adiyansyah, Firman; Anwar, Yusril Rais; Sari, Kurnia Novita
Jurnal Statistika dan Aplikasinya Vol. 7 No. 2 (2023): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07203

Abstract

Information about amount of insurance claims is needed by insurer to set premium or other decisions in the future. Amount of claims modeling is a way to determine the characteristics of a distribution of claims data and can be used to predict the amount of claims that may occur. A commonly used model for amount of insurance claims data is the distribution model for heavy tails. The discussion in this article focuses on modeling amount of insurance claims using Lognormal, Pareto and Weibull distributions, and also using Gamma distribution for comparison. The data used is sample data from Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan in 2015-2016. The data contains membership data and details of the amount of each participant's claim. The analysis is carried out to find out the best candidate model that matches the amount of insurance claims data for both inpatient and outpatient categories. In addition, the Tail-Value-at-Risk (TVaR) of the model will be calculated to determine the amount of capital that will be required with a 75% confidence level. Based on the results of the study, the best model for large data samples of claims for outpatient and inpatient categories is the Lognormal model. TVaR for the outpatient category is Rp492,596 and for the inpatient category is Rp7,672,726.
THE BENEFITS OF FAMILY ANNUITY CALCULATION WITH VINE’S COPULA AND FUZZY INTEREST RATE Sari, Kurnia Novita; Deautama, Randi; Febrisutisyanto, Ady
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2461-2470

Abstract

One example of a multiple life annuity product (covering more than one person) is a reversionary annuity, which is a life annuity product for two or more annuitants whose annuity payments will begin after one of the annuitants specified in the contract dies first until the other annuitant also dies. This type of annuity is modified into a family annuity consisting of husband, wife, and child. The marginal distribution is constructed from a combined model of several mortality models such as Heligman-Pollard, Costakis, and Kannisto-Makeham models to capture mortality at young and old ages.This study takes this dependency into account when modeling the joint distribution of remaining life expectancy between the parties. The joint distribution of remaining lifetime between annuitants is modeled with a Vine’s copula constructed from the marginal distribution of each annuitant. This research also takes account the actuarial margin rate using BI-7-day (reverse) repo rate data estimated with fuzzy sets. The annuity benefits calculation is assumed with some Kendall's tau () values. The result shows the value of annuity benefits increases as the value of increases.
CONSTRUCTION OF INDONESIA MORBIDITY TABLE FOR GENITOURINARY SYSTEM-RELATED DISEASES TO FACILITATE INDONESIA’S ECONOMIC EXPANSION Sari, Kurnia Novita; Adiyansyah, Firman; Sergio, Steven; Antonius, Enrico
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1549-1562

Abstract

The disease of the genitourinary system is one of the most common diseases in Indonesia. The disease shows some risk, especially in health and economic aspect. To overcome the risk posed by disease of the genitourinary system, a morbidity table can be used to reduce the number of people infected by the disease, and in this research, morbidity table based on sample data of BPJS Kesehatan from 2015 to 2016 will be constructed. Data processing starts with obtaining the empirical probability value of the disease of the genitourinary system. Then, the result obtained was interpolated in numerous preferences of methods. After the best interpolation model was known, the extrapolation process was run at an age range from age 80 to age 85 using Whittaker-Henderson smoothing method. The age range chosen is due to the fact that for ages over 80 years, the number of exposures is minimal, which can affect the number of claims in that age group. Extrapolation is extended up to the age of 85 years because the Morbidity Table for Critical Illness sets the age of 85 years as the upper limit for extrapolation. The model derived from interpolating age groups with a knot shows the highest R-square value, making it the most optimal model. It shows that Indonesians' probability to contract the disease is increasing significantly from about age 25 until around age 65, and the probability slowly declines after age 65. This result can be used as a reference by the Government of Indonesia to produce regulations leading to health protection for all citizens of Indonesia, especially for those who are classified as the labor force. Health protection provided by the government should improve welfare in Indonesian society. Moreover, the regulation should protect the productivity of the manpower and raise Indonesia’s Gross Domestic Product (GDP). BPJS Kesehatan can also use this predicted morbidity table to determine the right contribution fee. Hence, the contribution can be beneficial to pay any expense of the patient who contracted the disease, but on the other hand, not sending BPJS Kesehatan into bankruptcy. All of abovementioned efforts have one bold intention—to support Indonesia’s economic expansion as Indonesia aims to reach Golden Indonesia Vision by 2045.
MODELING CUSTOMER LIFETIME VALUE WITH MARKOV CHAIN IN THE INSURANCE INDUSTRY Mahdiyasa, Adilan Widyawan; Pasaribu, Udjianna Sekteria; Sari, Kurnia Novita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp687-696

Abstract

In the competitive insurance industry, accurately predicting Customer Lifetime Value (CLV) is vital for sustaining long-term profitability and optimizing resource allocation. Traditional static models often fail to capture the dynamic and uncertain nature of customer behavior, which is influenced by factors such as life changes, economic conditions, and evolving product offerings. To address these limitations, this paper proposes an advanced modeling approach that integrates Markov Chains with survival analysis. Markov Chains are well-suited for modeling stochastic processes, where future states depend on current conditions, while survival analysis provides insights into event timing and likelihood for estimating the insurance premium. The proposed model combines these approaches to make a more complete and accurate prediction of CLV. This helps insurers make better decisions and improves the overall performance of their business. We employ the data of customer behavior from the insurance company in Bandung, Indonesia from 1994 to 2020. We found that CLV in the insurance industry is significantly affected by customer behavior.
Exploring Multivariate Copula Models and Fuzzy Interest Rates in Assessing Family Annuity Products Sari, Kurnia Novita; Febrisutisyanto, Ady; Deautama, Randi; Azirah, Nursiti; Mahani, Pida
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.17467

Abstract

This research explores the development of a reversionary annuity product transformed into a family annuity covering three individuals: husband, wife, and children. The innovative design of this product considers the sequencing of annuity payments post-participant's demise, aiming to mitigate the risk of parents' death impacting their children. Recognizing the inadequacy of assuming independence among individuals in premium calculations, the study employs a multivariate Archimedean Copula model to account for interdependence. The primary objective is to compute the survival single-life function for each individual taken from TMI IV 2009. Then the copula model is implemented with Clayton and Frank copulas at varying Kendall’s tau values (0.25, 0.5, and 0.75). Meanwhile, the interest rates are modeled using the BI-7-day (reverse) rate with a Triangular Fuzzy α-cut. The findings reveal that increasing Kendall’s tau values lead to higher pure premiums, and notably, the Frank Copula model yields higher premium values than the Clayton Copula model. This research contributes valuable insights into the actuarial assessment of family annuity products, shedding light on the significance of considering dependencies among individuals for more accurate premium calculations.