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Forecasting the Rupiah Exchange Rate Influenced by Several Factors Using the Improve Grey Model (1,3) Pratiwi, Dian Meilin; Firdaniza, Firdaniza; Kusuma, Dianne Amor
Jambura Journal of Mathematics Vol 7, No 1: February 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i1.27954

Abstract

The rupiah exchange rate is one of the important indicators of a country's economic stability, but the rupiah exchange rate often fluctuates following the factors that influence it. Forecasting the rupiah exchange rate is very important for economic planning, it helps the government make monetary policy decisions to maintain the stability of the rupiah exchange rate. Common methods used to forecast the rupiah exchange rate are ARIMA, FTS Markov Chain, and exponential smoothing. These methods are widely used to show the relationship between variables, but these methods have the disadvantage that they must meet the assumptions of data patterns. The contribution of this research is the use of the improve Grey model (1,3) predict the rupiah exchange rate in 2024, which is influenced by inflation and the balance of payments. The improve Grey model (1,3) was chosen because it does not require data distribution assumptions and can consider several external factors, thus providing more specific results for certain fields. The improve Grey model (1,3) uses the Grey model (1,1) to calculate the parameter values of the independent variables in the calculation of the improve Grey model (1,3) whitening equation. The calculation of the improve Grey model (1,3) whitening equation is calculated using a first-order ordinary differential equation. The use of the improve Grey (1,3) model for forecasting the rupiah exchange rate is considered accurate based on the Mean Absolute Percentage Error (MAPE) value. The rupiah exchange rate influenced by inflation and the balance of payments using the improve Grey model (1,3) for 2024 is predicted to increase from the previous year to Rp. 18.076, which indicates a weakening in value. This weakening has a positive impact on the balance of payments and a negative impact on inflation.
Eksistensi Fungsional Frobenius dan Simplektik Linear Form Pada Aljabar Lie aff(3,R) Kurniadi, Edi; Aurillya Queency; Firdaniza, Firdaniza
Mandalika Mathematics and Educations Journal Vol 7 No 2 (2025): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i2.8906

Abstract

Aljabar Lie dari grup Lie Aff(n,R) dinotasikan oleh aff(n,R)  di mana setiap anggotanya dapat dinyatakan dalam bentuk matriks berukuran (n+1) x (n+1). Sifat Frobenius ini mengakibatkan adanya Frobenius fungsional yang bekorepondensi dengan bentuk simplektiknya.  Tujuan penelitian ini adalah untuk menentukan bentuk simplektik pada aff(3,R). Pendekatan yang digunakan dalam penelitian ini adalah kombinasi dari metode kuantitatif berupa penentuan rumus eksplisit simplektik linear 2-form pada aff(3,R) dan metode kualitatif berupa studi literatur. Hasil yang diperoleh bahwa setiap  Frobenius fungsional dari aljabar Lie affine  senantiasa dapat dikonstruksi simplektik 2-form linear yang bersifat skew-simetrik dan non-degenerate sedemikian sehingga aljabar Lie affine aff(3,R) ini bersifat Frobenius. Hasil penelitian ini dapat dikembangkan untuk rumus umum bentuk simplektik aff(n,R), n>=4.
Markov average-based weighted fuzzy time series model to predict PT Kimia farma Tbk stock price Azzahra, Rediva; Firdaniza, Firdaniza; Gusriani, Nurul
Desimal: Jurnal Matematika Vol. 4 No. 3 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v4i3.9675

Abstract

The COVID-19 pandemic impacted various activities in Indonesia, including the stock market. Despite the declining economic condition, people are increasingly interested in investing. Among other companies available on the Indonesia Stock Exchange, companies in the health sector have a particular appeal to potential investors, one of which is pharmaceutical companies. This research used a Markov Average-Based Weighted Fuzzy Time Series model applied to PT Kimia Farma Tbk stock price data. This model develops the previous Markov chain–Fuzzy Time Series model, which has not calculated the weights for recurring events and used the Sturgess rule to determine the interval length. In this research, each recurring event has given a different weight that provides different probability values for transitions from one state to another. The Average-Based method is used to determine the interval length that can reflect the fluctuation of the data used. The stock price prediction of PT Kimia Farma Tbk using this model is categorized as very accurate with a MAPE of 2.632%.
Struktur Simplektik pada Aljabar Lie Affine aff(2,R) Queency, Aurillya; Kurniadi, Edi; Firdaniza, Firdaniza
Jambura Journal of Mathematics Vol 6, No 1: February 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i1.23254

Abstract

In this research, we studied the affine Lie algebra aff(2,R). The aim of this research is to determine the 1-form in affine Lie algebra aff(2,R) which is associated with its symplectic structure so that affine Lie algebra aff(2,R) is a Frobenius Lie algebra. Realized the elements of the affine Lie algebra aff(2,R) in matrix form, then calculated the Lie brackets and formed the structure matrix of the affine Lie algebra aff(2,R). 1-form of the affine Lie algebra aff(2,R) is obtained from the determinant of the structure matrix of the affine Lie algebra aff(2,R). Furthermore, proved that the 2-form is symplectic and related to the 1-form. The result obtained is that the affine Lie algebra aff(2,R) has 1-form α=ε_12^*+ε_23^* on aff(2,R)^* which is related to its symplectic structure, β=ε_11^*∧ε_12^*+ε_12^*∧ε_22^*+ε_21^*∧ε_13^*+ε_22^*∧ε_23^* such that the affine Lie algebra aff(2,R) is a Frobenius Lie algebra. For further research, it can be developed into an affine Lie algebra with dimensions n(n+1).
Klasifikasi Aljabar Lie Forbenius-Quasi Dari Aljabar Lie Filiform Berdimensi ≤ 5 Pratiwi, Putri Nisa; Kurniadi, Edi; Firdaniza, Firdaniza
Jambura Journal of Mathematics Vol 6, No 1: February 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i1.22481

Abstract

In this research, we studied quasi-Frobenius Lie algebras and filiform Lie algebras of dimensions â‰¤ 5 over real field. The primary objective of this research is to classify the classification of filiform Lie algebras of dimensions â‰¤ 5 into quasi-Frobenius Lie algebras. The method employed in this research involves constructing a skew-symmetric 2-form in real Lie algebra, which also a nondegenerate 2-cocycle. The outcomes of this research reveal that there exists a class of filiform Lie algebras of dimensions $\le 5$ that can be classified as a quasi-Frobenius real Lie algebra. Furthermore, this research can be developed to classify higher dimensional filiform Lie algebras as quasi-Frobenius real Lie algebras.
Robust Optimization Model for Twitter Sentiment Analysis of PeduliLindungi Application Fatimathuzahra, Alfia Azizah; Chaerani, Diah; Firdaniza, Firdaniza
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8624

Abstract

Technological advances during the COVID-19 pandemic in Indonesia gave rise to the PeduliLindungi application which is developed by the government to prevent the spread of COVID-19. The advantages and disadvantages of developing PeduliLindungi can be seen from the responses and opinions from users, one of which is through the Twitter. A person's opinion about PeduliLindungi based on the tweet can be classified into positive, negative, or neutral categories using a Machine Learning approach with the Support Vector Machine (SVM) algorithm. In this paper, multiobjective optimization modeling is used to maximize the performance metrics, which are the value of Accuracy, Precision, Recall, and F1-Score. The value of the performance metrics is considered to contain uncertainty factors. Therefore, the optimization problem is solved by using Robust Optimization to handle the uncertainty factor. The data uncertainty is assumed to be belongs to polyhedral uncertainty set thus the resulted robust is computationally tractable. Numerical experiment is presented to complete the discussion.
Estimation of Labor Force Participation Rate (TPAK) in Java's Data-Scarce Areas Using Ordinary Cokriging Angelina, Sofia; Gusriani, Nurul; Firdaniza, Firdaniza
Jurnal Matematika Integratif Vol 21, No 2: Oktober 2025
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v21.n2.65239.229-244

Abstract

The quality of the labor force is crucial for economic development, and the Labor Force Participation Rate (TPAK) is a key employment indicator. In 2024, TPAK data collection in Java Island faced gaps in DKI Jakarta and Banten Provinces, limiting comprehensive labor mapping. To overcome this, spatial estimation methods are needed using data from surrounding areas and auxiliary variables. The Open Unemployment Rate (TPT) has a strong inverse relationship with TPAK, each 1\% TPAK increase lowers TPT by 14,82\%, making it a suitable auxiliary variable. This study estimates the 2024 TPAK for DKI Jakarta and Banten using the ordinary cokriging method, with TPT as the secondary variable. Spatial autocorrelation analysis confirmed that TPAK and TPT exhibit spatial patterns, are normally distributed, and meet stationarity assumptions. The best cross semivariogram model was identified using k-fold cross validation, which selected the spherical model with the lowest average RMSE of 4,24. The resulting ordinary cokriging model accurately predicted TPAK values, achieving a MAPE of 3,25\%. These estimates enable spatial visualization of TPAK in previously unobserved areas, contributing to a more complete understanding of labor participation across Java Island.