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All Journal Jurnal Matematika Jurnal Ilmu Komputer Buletin Udayana Mengabdi E-Jurnal Matematika AdMathEdu : Jurnal Ilmiah Pendidikan Matematika, Ilmu Matematika dan Matematika Terapan PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah International Journal of Applied Mathematics and Computing.
LUH PUTU IDA HARINI
Program Studi Matematika, FMIPA, Universitas Udayana
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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PENGGUNAAN SIMULASI MONTE CARLO DALAM ESTIMASI VALUE AT RISK (VaR) PORTOFOLIO YANG DIBENTUK DARI INDEKS HARGA SAHAM MULTINASIONAL NABILA NUR JANNAH; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 11 No 3 (2022)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2022.v11.i03.p381

Abstract

Investment is buying an asset that is expected in the future can be resold and get a high profit value. There are two factors that must be considered when you want to invest in stocks, namely the rate of return on stocks and risk factors. By forming a portfolio is expected to minimize a risk. Value at Risk (VaR) is a form of measurement of risk when making investments. In this study VaR will be calculated using the Monte Carlo Simulation method and the Historical method. This study aims to find out var portfolio estimates involving JCI and DJIA stock indices from two different countries as well as to find out the differences between VaR using Historical and VaR using Monte Carlo Simulations. From the stock index data obtained further determined the value of the parameters, namely the expected return and standard deviation values used to calculate the value of the VaR Portfolio, while the confidence increase used in this study was 99% and with a period of 1 or the next day. Based on the results of the VaR value study using the Monte Carlo Simulation method and the Historical method, the Historical method obtained results of 3,650,506 and 1,029,103. The results showed that VaR values using the Monte Carlo Simulation method got greater results than using the Historical method, because the Monte Carlo Simulation performed repeated iterations by including random number generators.
Klasifikasi Calon Nasabah Debitur KSP. Samudra Harta Dengan Recurrent Neural Network Gusti Ayu Rica Ananda*; Luh Putu Ida Harini; I GN Lanang Wijayakususma
JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Vol 8, No 4 (2023): Agustus, Social Religious, History of low, Social Econmic and Humanities
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jimps.v8i4.27093

Abstract

Klasifikasi merupakan suatu susunan yang sistematis dalam kelompok atau menurut aturan atau standar yang telah ditetapkan. Mengklasifikasikan dapat diartikan sebagai upaya mengelompokkan suatu benda menurut jenis-jenisnya. klasifikasi dapat dengan mudah dilakukan salah satunya dengan menggunakan metode Recurrent Neural Network (RNN), metode ini muncul karena adanya operasi yang sama pada setiap elemen secara berurutan, dimana output yang dihasilkan dipengaruhi oleh input yang diberikan pada operasi saat ini. dan operasi sebelumnya. Mengambil kredit atau pinjaman merupakan salah satu cara mendapatkan uang tambahan dengan proses yang cepat dan mudah. Kredit adalah suatu fasilitas keuangan yang diberikan oleh suatu lembaga keuangan bank atau bukan bank, yang memungkinkan seseorang atau suatu lembaga meminjam uang yang harus dikembalikan secara angsuran dalam jangka waktu yang disepakati bersama. Pemberian kredit tentunya menimbulkan beberapa permasalahan, salah satunya adalah risiko kegagalan pembayaran kredit. Penelitian ini akan membahas tentang klasifikasi calon nasabah debitur Samudra Harta. Metode Recurrent Neural Networks mengantisipasi risiko gagal bayar kredit akibat pencairan kredit yang tidak sesuai dengan kemampuan membayar pelanggan. MAPE yang diperoleh dari program ini adalah 18,6% dan nilai lainnya adalah Accuracy 70%, Precision 83,3%, Recall 71%, F-1 Score 76,53%. Dari nilai tersebut kita dapat menyimpulkan bahwa program ini bagus.
MODEL MATEMATIKA SIR PADA PENYEBARAN PENYAKIT COVID-19 DENGAN EFEKTIVITAS VAKSIN NI LUH GEDE SHINDYA ARMITA; LUH PUTU IDA HARINI; IDA AYU PUTU ARI UTARI
E-Jurnal Matematika Vol 13 No 1 (2024)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2024.v13.i01.p439

Abstract

Corona Virus Disease (COVID-19) is one of the disease outbreaks that has spread throughout the world since the end of 2019. This disease causes infected individuals to experience infections in the respiratory tract with a fairly high risk. One branch of mathematics that can help overcome this case is the formation of mathematical models. The model formed is the SIR model basically describes the spread of disease in the Susceptible (S), Infected (I), Recovered (R) classes, but in this study the Infected (I) class was classified into two and added parameters to decrease vaccine effectiveness. The former model is then used to find a solution in the form of a disease-free equilibrium point, where the point will be used to form a basic reproduction number. To prove that the equilibrium point found to be stable, a stability analysis will be carried out and in the model that has been formed it is found that the disease-free equilibrium point is locally asymptotic stable with the condition that. After analysis, it was found that the rate of decline in vaccine effectiveness was quite influential on the class of infection .
ANALISIS PORTOFOLIO OPTIMAL PADA INVESTASI LOGAM MULIA EMAS MENGGUNAKAN METODE MEAN ABSOLUTE DEVIATION (MAD) DENGAN ESTIMASI PARAMETER GARCH(1,1) FEBBY VERENNIKA; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 13 No 2 (2024)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2024.v13.i02.p454

Abstract

This study aims to analyze the optimal portfolio in gold precious metal investments using the Mean Absolute Deviation (MAD) method combined with the GARCH(1,1) parameter estimation. The MAD method was chosen for its ability to measure portfolio risk more stably and simply compared to other methods like Mean-Variance. Meanwhile, the GARCH(1,1) model is used to estimate the volatility of gold prices, which are often influenced by global economic and geopolitical uncertainties. The data used in this study include daily stock prices of gold companies from January 2017 to June 2021. The analysis results show that the combination of the MAD method and GARCH(1,1) can provide a more comprehensive view of forming an optimal portfolio that maximizes returns and minimizes risks for gold investors. Based on the calculations, the optimal portfolio with the best performance was identified using the Sharpe, Treynor, and Jensen indices, which indicate the superiority of the first portfolio in terms of return and risk.
Estimasi Risiko Kredit Obligasi Dengan Suku Bunga Stokastik Berdasarkan Probability Of Default Surma, Odilia Gratiaplena; Dharmawan, Komang; Ida Harini, Luh Putu
Jurnal Matematika Vol 13 No 2 (2023)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2023.v13.i02.p166

Abstract

Bonds as a fairly safe short-term and long-term investment product certainly still have potential investment risks. One of the risks in bond products is credit risk in the form of default, where the issuer fails to pay obligations to investors. The Merton model is one method that can be applied in estimating credit risk on bonds. The interest rate applied in the Merton model is generally a constant interest rate so that in this study the constant interest rate will be replaced by the stochastic interest rate of the Cross Ingersoll Ross (CIR) model. This study aims to calculate the probability of default by applying the CIR model interest rate in the Merton model of BRI bank based on a bond value of 605 billion and a bond contract period of 7 years. The results of the calculation of the CIR model interest rate of 7.28% by substituting it into the Merton model calculation obtained a probability of default value of 0.0% which indicates that there is no risk of default by BRI bank at maturity
Klasifikasi Calon Nasabah Debitur KSP. Samudra Harta Dengan Recurrent Neural Network Gusti Ayu Rica Ananda*; Luh Putu Ida Harini; I GN Lanang Wijayakususma
JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Vol 8, No 4 (2023): Agustus, Social Religious, History of low, Social Econmic and Humanities
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jimps.v8i4.27093

Abstract

Klasifikasi merupakan suatu susunan yang sistematis dalam kelompok atau menurut aturan atau standar yang telah ditetapkan. Mengklasifikasikan dapat diartikan sebagai upaya mengelompokkan suatu benda menurut jenis-jenisnya. klasifikasi dapat dengan mudah dilakukan salah satunya dengan menggunakan metode Recurrent Neural Network (RNN), metode ini muncul karena adanya operasi yang sama pada setiap elemen secara berurutan, dimana output yang dihasilkan dipengaruhi oleh input yang diberikan pada operasi saat ini. dan operasi sebelumnya. Mengambil kredit atau pinjaman merupakan salah satu cara mendapatkan uang tambahan dengan proses yang cepat dan mudah. Kredit adalah suatu fasilitas keuangan yang diberikan oleh suatu lembaga keuangan bank atau bukan bank, yang memungkinkan seseorang atau suatu lembaga meminjam uang yang harus dikembalikan secara angsuran dalam jangka waktu yang disepakati bersama. Pemberian kredit tentunya menimbulkan beberapa permasalahan, salah satunya adalah risiko kegagalan pembayaran kredit. Penelitian ini akan membahas tentang klasifikasi calon nasabah debitur Samudra Harta. Metode Recurrent Neural Networks mengantisipasi risiko gagal bayar kredit akibat pencairan kredit yang tidak sesuai dengan kemampuan membayar pelanggan. MAPE yang diperoleh dari program ini adalah 18,6% dan nilai lainnya adalah Accuracy 70%, Precision 83,3%, Recall 71%, F-1 Score 76,53%. Dari nilai tersebut kita dapat menyimpulkan bahwa program ini bagus.
Detection of Political Hoax News Using Fine-Tuning IndoBERT Jocelynne, Charlotte; Wijayakusuma, IGN Lanang; Harini, Luh Putu Ida
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8989

Abstract

Indonesia has experienced a surge in the spread of political hoax news, posing a potential threat to democratic and social stability. This study aims to develop a model for detecting political hoax news in the Indonesian language using IndoBERT, a language model optimized for Indonesian text. The dataset was sourced from Kaggle and comprises 20,928 factual news articles and 2,251 hoax news articles from major Indonesian media outlets, including CNN, Kompas, Tempo, and Turnbackhoax. The imbalance between factual and hoax news articles was addressed through undersampling, resulting in 1,302 samples for each class. The research stages include data collection, preprocessing, IndoBERT model training, and model evaluation. Results indicate that fine-tuning IndoBERT can detect political hoax news with an accuracy of 94.1% and an ROC AUC of 0.991, demonstrating high performance in accuracy and generalization capability. This research is expected to contribute to minimizing the spread of political hoax news in Indonesia and enhance media literacy among the public.
Determining the Price of Asian Type Call Option Contracts Using the Monte Carlo Stratified Sampling Method Susanti Marito Barus; Komang Dharmawan; Luh Putu Ida Harini
International Journal of Applied Mathematics and Computing Vol. 2 No. 2 (2025): April: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i2.188

Abstract

Determining the price of option contracts is a crucial aspect of financial markets, particularly for investors aiming to manage risk and make informed investment decisions. In this study, the price of an Asian call option is calculated using the Monte Carlo Stratified Sampling method based on the stock price data of Tesla, Inc. (TSLA) from January 2021 to December 2023. This method has been proven to reduce variance compared to the Standard Monte Carlo simulation, leading to faster price convergence and more efficient results. The parameters used in the simulation include the initial stock price (S_0), number of simulations (N), maturity time (T)dividend = 0, risk-free rate (r), strike price ( K), and volatility
Co-Authors AA Sudharmawan, AA ANGGIE EZRA JULIANDA HUTAPEA COKORDA BAGUS YUDISTIRA DESAK PUTU DEVI DAMIYANTI Desak Putu Eka Nilakusmawati Eka N. Kencana EKA N. KENCANA FEBBY VERENNIKA FITRI ANANDA DITA SARASWITA G. K. GANDHIADI GEDE AGUS HENDRA YOGANGGA Gusti Ayu Rica Ananda* I GEDE ARI SUDANA I GEDE ARYA DUTA PRATAMA I GEDE DICKY ARYA BRAMANTA I GEDE HARDI KARMANA I Gede Santi Astawa I GN Lanang Wijayakususma I GUSTI PUTU NGURAH MAHAYOGA I KADEK MENTIK YUSMANTARA I KADEK SONA DWIGUNA I KETUT RESTU WIRANATA I MADE DWI UDAYANA PUTRA I NYOMAN DICKY WIJAYA I Nyoman Widana I PUTU AGUS DARMAWAN DARMA YADNYA I PUTU ARYA YOGA SUMADI I Putu Eka Nila Kencana I PUTU YUDI PRABHADIKA I Wayan Sumarjaya I WAYAN YOGA ASTAWA IDA AYU EGA RAHAYUNI Ida Ayu Putu Ari Utari ISTIQOMAH ISTIQOMAH Jocelynne, Charlotte KADEK INTAN SARI Kartika Sari Ketut Jayanegara Komang Dharmawan KOMANG WAHYUDI SUARDIKA LIA APRIYANI MADE ADI GUNAWAN MADE ASIH Made Susilawati Mahardika, Putu Harry MOH. HERI SETIAWAN NABILA NUR JANNAH Ngurah Agus Sanjaya ER NI KADEK DESI PUJA ANTARI Ni Kadek Emik Sapitri NI KADEK MAYULIANA Ni Ketut Tari Tastrawati NI KOMANG AYU SEDANA DEWI NI LUH GEDE SHINDYA ARMITA NI LUH PUTU RATNA DEWI Ni Luh Putu Suciptawati PANDE GDE DONY GUMILAR PRADITA Z. TRIWULANDARI Putri Cahyaning Putu Harry Mahardika Putu Harry Mahardika PUTU IKA OKTIYARI LAKSMI PUTU SAVITRI DEVI RISKA YUNITA SANI SAEFULOH SARAH VERONICA HUTABALIAN SAYID QOSIM Surma, Odilia Gratiaplena Susanti Marito Barus TIRA CATUR ROSALIA Tjokorda Bagus Oka TRI YANA BHUANA VALERIA TRISNA YUNITA WAYAN ARTHINI Wijayakusuma, I Gusti Ngurah Lanang