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All Journal Journal of Management Review InPrime: Indonesian Journal Of Pure And Applied Mathematics MATHunesa: Jurnal Ilmiah Matematika Jurnal Locus Penelitian dan Pengabdian Indonesian Capital Market Review The South East Asian Journal of Management
Suardi, Lenny
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Aerospace Engineering Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics

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Survival Analysis of Stroke Incidence in National Health Insurance Participants from 2015–2020 Ilmi, Irfan; Suardi, Lenny
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol. 7 No. 2 (2025)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/9dxvy438

Abstract

This study aims to analyze the survival of stroke patients enrolled in the National Health Insurance (Jaminan Kesehatan Nasional, JKN) program and factors affecting it during the 2015–2020 period. Survival analysis was utilized using the Kaplan-Meier estimator and the Cox Proportional Hazards model. The dataset consisted of 12,773 stroke patients sampled from BPJS Kesehatan administrative records. The results indicate that since being registered as BPJS Kesehatan participants or from the baseline year 2015, stroke patients had an average survival time of 2,264 days, with a 95% confidence interval between 2,240 and 2,287 days. The Cox model revealed that patients aged 18–35, 36–50, 51–65, and >65 had Hazard Ratios (HR) of 1.30, 1.69, 2.47, and 3.52, respectively. Female patients exhibited a lower risk of death (HR = 0.81) than males. Employment segment effects were modest, and regional disparities were observed, with the Eastern region showing a higher risk (HR = 1.29). Comorbidities further increased hazards, with hypertension (HR = 1.70) and diabetes (HR = 2.17) significantly raising mortality risk. As one of the first large-scale survival analyses using JKN national data, this study offers novel evidence on key determinants of stroke outcomes in Indonesia. Its findings highlight critical risk factors and support more targeted, data-driven strategies for stroke prevention under universal health coverage. Keywords: Cox Proportional Hazard; Kaplan-Meier; National Health Insurance Agency; Stroke; Survival Analysis.   Abstrak Penelitian ini bertujuan untuk menganalisis survival pasien stroke yang terdaftar dalam program Jaminan Kesehatan Nasional (JKN) dan faktor-faktor yang memengaruhinya selama periode 2015–2020. Metode yang digunakan adalah analisis survival dengan pendekatan Kaplan-Meier dan model Cox Proportional Hazards. Data yang dianalisis diambil dari sampel BPJS Kesehatan peserta JKN selama 2015–2020, yang berjumlah 12.773 pasien. Hasil penelitian menunjukkan bahwa sejak terdaftar sebagai peserta BPJS Kesehatan atau sejak tahun dasar 2015, pasien stroke memiliki waktu survival rata-rata 2.264 hari, dengan interval kepercayaan 95% antara 2.240 dan 2.287 hari. Model Cox mengungkapkan pasien berusia 18–35, 36–50, 51–65, dan >65 memiliki HR masing-masing sebesar 1,30, 1,69, 2,47, dan 3,52. Perempuan memiliki risiko lebih rendah (HR = 0,81) dibandingkan laki-laki. Efek pada segmen pekerjaan relatif kecil, dan disparitas regional teramati, dengan wilayah Timur menunjukkan risiko yang lebih tinggi (HR = 1,29). Komorbiditas semakin meningkatkan risiko, dengan hipertensi (HR = 1,70) dan diabetes (HR = 2,17) secara signifikan meningkatkan risiko mortalitas. Sebagai salah satu analisis survival skala besar pertama yang menggunakan data nasional JKN, studi ini menawarkan bukti baru tentang determinan utama luaran stroke di Indonesia. Temuannya menyoroti faktor risiko kritis dan mendukung strategi pencegahan stroke yang lebih terarah dan berbasis data dalam kerangka jaminan kesehatan semesta. Kata Kunci: Cox Proportional Hazard; Kaplan-Meier; Jaminan Kesehatan Nasional; Stroke; Analisis survival. 2020MSC: 91G05.
Mortality Baseline Model Using Linear Time Series and Linear Mixed Model in Excess Mortality Calculation During COVID-19 in DKI Jakarta Agistia, Maulia Dita; Suardi, Lenny
MATHunesa: Jurnal Ilmiah Matematika Vol. 11 No. 1 (2023)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v11n1.p1-7

Abstract

COVID-19 pandemic has affected the mortality across a globe. To investigate the impact of COVID-19, many countries have recorded number of deaths due to COVID-19. In Indonesia, DKI Jakarta reports the highest number of mortality due to COVID-19. However, the reported data may have discrepancy, for example the scope of testing for COVID-19 that has not been widely implemented, false-negative on testing results and deaths that occur before COVID-19 test. The measurement of excess mortality has been suggested to cover the lack of data. Baseline mortality will be the main component in calculating excess mortality. Monthly deaths data of DKI Jakarta from January 2018 up to February 2021 will be used to generate baseline mortality model. The analysis will compare two models, linear time series and linear mixed model. Model accuracy will be calculated to choose the better baseline mortality model. The better model of baseline mortality will give better estimation of excess mortality during COVID-19. Linear time series provides a better accuracy on baseline mortality model in DKI Jakarta. The result shows that there are 25,553 excess mortality during COVID-19 pandemic in DKI Jakarta from June 2020 until June 2021. The SMR during pandemic COVID-19 is around 133%.
Analysis of Factors Affecting the Financial Health of General Insurance Companies and Life Insurance Companies in Indonesia for the Period of 2013 – 2021 Beaty, Zuly Puspita; Suardi, Lenny
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 11 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i11.5056

Abstract

Financial health is an important factor for insurance companies. This study aims to analyze the factors that affect the level of financial health of general insurance companies and life insurance companies in Indonesia. This study uses logistic regression analysis and survival analysis. The results of the analysis show that the return on assets has a negative influence on the non-fulfillment of the financial health of life insurance companies or the general public. Meanwhile, the claim ratio has a positive influence on the financial health of the insurance company. In life insurance companies, the placement of insurance in bond instruments or debt securities has a negative effect on the non-fulfillment of the financial health condition of the insurance company. The results obtained between logistics regression and survival analysis for life insurance companies are not much different. However, the results of the survival analysis produced for general insurance companies are biased. This study contributes to understanding insolvency risks in emerging-market insurance systems using dual-model analysis, offering practical implications for regulators and practitioners in developing economies with limited policyholder protection mechanisms.
Co-Authors Agistia, Maulia Dita Beaty, Zuly Puspita Dwi Nastiti Danarsari Hakim, Fahmi Husodo, Zaafri Ananto Ilmi, Irfan Jati, Muthaqin Dhamar Widhoro M. Syamsudin, M. Malau, Siska F Nugroho, Joshua Aditia Ratih Dyah Kusumastuti Ririen Setiati Risca Fleureta Hudiyono Soegondo, Dhanawan Prasidya Viverita Viverita