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All Journal International Journal of Mathematics, Statistics, and Computing
Purba, Daniel Victorio Rudolfo
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Computer Science & IT Mathematics

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Portofolio Management with Markowitz Model to Determine Optimal Investment Values Purba, Daniel Victorio Rudolfo; Fasya, Emir Shiddiq
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 3 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i3.120

Abstract

Investment is a commitment to a number of funds or other resources made at this time with the aim of obtaining a number of benefits in the future. Investments can be channeled through several instruments, such as deposits, gold, property, stocks, and many more. With the various types of investments that exist today, the difficulty of finding an investment cannot be an obstacle. In investment, the appropriate allocation of funds can be an important factor in obtaining profits. By using the correct method, the risk factors that may occur can be minimized as well as possible. The method that can be used in determining funds in investment activities is using the Markowitz Model. Then, the  author  initiates  a method  for  optimizing  assets  using  the  Markowitz  method.  In  this  research,  used  data  from  10  stocks  in Indonesia PANI, CLEO, DSSA, UNIC, ADRO, CITA, CAKK, TPIA, MYOR, ANTM. Then, the stocks will be arranged optimally portfolio. The optimal investment weight obtained for stocks from January 1, 2019 to December 31, 2023 using the Markowitz model, each share weighting namely 7,6% PANI, 18,05% CLEO, 8,48% DSSA, 16,902% UNIC, 12,471% ADRO, 10,496% CITA, 7,246% CAKK, 12,946% TPIA, 5,877% MYOR, and 0,464% ANTM company stocks and provide a portfolio ratio of 5.694581 which can also be interpreted that the optimal return ratio profit is 5.694581 times greater than the possible loss or portfolio variance.
Calculation of Life Insurance Premiums with Markov Chain Applications for Patients with Pulmonary Tuberculosis Disease in Indonesia Putra, Fachrul Ananda; Purba, Daniel Victorio Rudolfo
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i4.143

Abstract

This study aims to calculate the premium for Long Term Care (LTC) insurance on Annuity as A Rider Benefit products with a multi-status model. Pulmonary Tuberculosis is one of the major infectious diseases that contribute significantly to morbidity and mortality rates. Therefore, it is necessary to calculate insurance premiums that consider the health risks of sufferers. In this study, Markov chains are used to model the health status transition of individuals with Pulmonary Tuberculosis over time, considering several health states, such as healthy, sick, and dead. Tuberculosis epidemiological data in Indonesia is used to estimate the transition probabilities between health states. The case study used in this research is a 35-year-old man who participates in LTC insurance with a coverage period of 5 years. It is known that the value of compensation when a person dies is IDR 100,000,000. The interest rate used is 5%. The calculation results obtained annual premium for LTC insurance on Annuity as A Rider Benefit product is Rp294,333. Then the calculation of the annual net premium of this insurance is also calculated based on age and gender. When age increases, the premium will be greater, this is influenced by the greater chance of death when age increases. In addition, based on gender, it is found that the male premium is more expensive than the female gender. This is influenced by the chance of death of men is greater than women.
Co-Authors Fasya, Emir Shiddiq Putra, Fachrul Ananda