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All Journal Operations Research: International Conference Series Jurnal Matematika Integratif
Kaerudin, Nandira Putri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Transportation

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Optimal Portfolio Risk Analysis Using the Monte Carlo Method Kahar, Ramadhina Hardiva; Kaerudin, Nandira Putri; Vimelia, Willen
Operations Research: International Conference Series Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i4.276

Abstract

Investment is an activity carried out with the expectation of gaining profits in the future through the management of investment assets. Investment assets can include buildings, gold, and stocks. Investment activities are inseparable from the concepts of return and risk. The relationship between the expected rate of return and the level of risk is linear. However, risk can be avoided or reduced through portfolio diversification. Evaluating investment risk is crucial for investors to determine which risky assets to choose. One popular method for assessing the risk of a portfolio is using Value at Risk (VaR). In VaR calculations, Monte Carlo is considered the most effective method. In this paper, a risk analysis of the optimal portfolio is conducted using the Monte Carlo method. The analyzed optimal portfolio consists of shares in BBCA, TLKM, BBRI, BBNI, BMRI, ADRO, GGRM, and UNTR. The results indicate that the potential loss for the investor is no more than IDR 705.634,- with an initial fund of 1 billion. 
Pemodelan Indeks Pembangunan Manusia di Kalimantan Timur Menggunakan Spasial Durbin Data Panel Kaerudin, Nandira Putri; Gusriani, Nurul; Ruchjana, Budi Nurani
Jurnal Matematika Integratif Vol 20, No 1: April 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n1.55158.101-115

Abstract

Indeks Pembangunan Manusia (IPM) merupakan salah satu indikator yang dapat digunakan untuk mengukur kemajuan suatu negara. Di Indonesia sendiri masih terdapat ketimpangan IPM antar provinsinya. Provinsi Kalimantan Timur merupakan salah satu provinsi yang memiliki rata-rata IPM tinggi di Indonesia, sehingga perlu dilakukan studi mengenai IPM untuk memberikan gambaran bagi provinsi dengan IPM rendah. IPM di suatu wilayah dipengaruhi oleh wilayah sekitarnya, hal ini disebabkan oleh efek spasial. Analisis regresi spasial merupakan metode yang mampu mengakomodasi efek spasial. Spatial Durbin Model (SDM) adalah salah satu pengembangannya. Selain itu, penggunaan data panel pada model menyebabkan variabilitas pada data. Penelitian ini bertujuan untuk memodelkan IPM di Kalimantan Timur menggunakan spasial durbin data panel meliputi lima kategori: Persentase penduduk miskin; Tingkat Partisipasi Angkatan Kerja (TPAK); Persentase penduduk; Angka Partisipasi Murni (APM); Persentase rumah tangga menurut fasilitas toilet sendiri. Berdasarkan hasil uji Hausman dan Chow, terdapat efek tetap pada setiap kabupaten/kota sehingga FEM merupakan jenis data panel yang digunakan. Selain itu, Hasil uji Moran’s I mengindikasikan adanya dependensi spasial positif dalam data IPM. Koefisien determinasi pada model spasial Durbin data panel menunjukkan nilai 99,92417% yang berarti model ini baik digunakan untuk memodelkan IPM di Kalimantan Timur.
Co-Authors Budi Nurani Ruchjana Kahar, Ramadhina Hardiva Nurul Gusriani, Nurul Vimelia, Willen