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All Journal Dimas: Jurnal Pemikiran Agama untuk Pemberdayaan Jurnal Pendidikan Matematika RAFA Phenomenon : Jurnal Pendidikan MIPA Sinkron : Jurnal dan Penelitian Teknik Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics Jurnal Informatika dan Rekayasa Perangkat Lunak Square : Journal of Mathematics and Mathematics Education Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Edumatica: Jurnal Pendidikan Matematika Journal Focus Action of Research Mathematic (Factor M) Indonesian Journal of Statistics and Its Applications
emy siswanah, emy
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Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Extreme Learning Machine and Multilayer Perceptron Methods for Predicting COVID-19 Yustisio, Dheva; Siswanah, Emy; Tafrikan, Mohamad
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14029

Abstract

The number of positive COVID-19 cases in Semarang City has increased over the last year. In anticipating and preparing proper health facilities, the government must predict the number of cases. This research applies Extreme Learning Machine (ELM) and Multilayer Perceptron (MLP) to indicate the number of positive COVID-19 cases. These newly developed methods are part of Artificial Neural Network (ANN). The type of data used in the study is secondary data. Covid-19 patient data was taken from the Semarang City Health Office. The data on the number of positive Covid-19 cases used is data from April 9, 2020 to December 15, 2022. The prediction results of the ELM and MLP methods were then compared to determine which method was more effective in predicting the number of positive Covid-19 cases. The results of the study showed that both methods had an error of less than 10%, meaning that both methods were feasible for predicting the number of positive Covid-19 cases. However, based on the Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) values, the MLP method had a smaller error rate than the ELM method. In predicting the number of COVID-19 positive cases, ELM has 93.436331% accuracy, and MLP has 97.055838% accuracy. The best method for predicting the number of COVID-19 positive cases in Semarang City is Multilayer Perceptron (MLP).
Penentuan Premi Tahunan Dan Cadangan Premi Dengan Metode New Jersey Asuransi Endowment Status Joint Life Menggunakan Suku Bunga Stokastik Miasary, Seftina Diyah; Umami, Riza Lathifatul; Siswanah, Emy
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 9 No 2 (2023): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v9i2.5953

Abstract

Joint life endowment status insurance is insurance that pays out if the participant dies during the policy participant's first death or survives until the conclusion of the insurance period. The purpose of this study is to calculate the amount of joint life endowment status life insurance premium reserves using the New Jersey technique in the CIR model with stochastic interest rates. The CIR model's stochastic interest rate value based on Bank Indonesia interest rates from 2018 to 2022 is 0,075. According to the calculations, the resulting annual premium is lower since the number of individuals who survive is greater than the number of persons who die over the insurance period. Furthermore, the size of the New Jersey premium reserve is zero in the first year and becomes closer to the compensation value as the insurance period proceeds.
Comparative Study of Multilayer Perceptron and Recurrent Neural Network in Predicting Population Growth Rate in Brebes Regency Yazidah, Izzatul; Siswanah, Emy
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.v7i1.30199

Abstract

Due to its ever-growing population, Brebes had the biggest population in Central Java from 2020 to 2022. The government of Brebes has to predict the growth rate of the population and prepare the resources and employment opportunities to anticipate this population growth rate. This research aims to analyze the result of growth rate prediction in Brebes using Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN). These two methods are applied to determine the most suitable one to predict the population growth rate. This is determined by comparing the smallest MAPE value of these two methods. The analyzed data of the total population from 1991-2022 is taken from Badan Pusat Statistik (BPS) of Brebes. The percentage of division between training and testing data is 80%:20%. According to the research results, the recurrent neural network is the most suitable method, with the smallest MAPE being 1.9973%.
Application of The Fackler and Full Preliminary Term Methods In Calculating n-Year Term Life Insurance Premium Reserves Miasary, Seftina Diyah; Ulna, Jihan Ramadhani Ar-Raafi’; Siswanah, Emy
Journal Focus Action of Research Mathematic (Factor M) Vol. 7 No. 1 (2024): Vol. 7 No. 1 (2024)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v7i11973

Abstract

Cadangan premi harus diperhitungkan dengan baik untuk meminimalisir kerugian bagi perusahaan asuransi. Metode yang digunakan dalam menentukan cadangan premi dari asuransi jiwa berjangka pada penelitian ini adalah metode Fackler dan metode Full Preliminary Term. Penelitian ini bertujuan untuk membandingkan perhitungan cadangan premi dengan kedua metode pada asuransi jiwa berjangka. Sebelum diperhitungkannya nilai cadangan, terlebih dahulu akan ditentukan besarnya nilai premi tunggal, anuitas awal, dan premi tahunan dari asuransi jiwa berjangka. Asumsi yang digunakan dalam penelitian meliputi tertanggung seorang laki-laki dan perempuan berusia 30 tahun, jangka pertanggungan 30 tahun, suku bunga sebesar 5,75%, dan santunan yang akan diberikan oleh perusahaan asuransi kepada tertanggung adalah sebesar Rp. 200.000.000. Berdasarkan hasil yang diperoleh, dengan didasarkan pada Tabel Mortalita Indonesia (TMI) 2019 diketahui bahwa nilai cadangan Fackler dan cadangan Full Preliminary Term pada produk asuransi jiwa berjangka n-tahun memberikan nilai yang tidak sama. Diperoleh bahwa cadangan Fackler memiliki nilai yang lebih besar dibandingkan dengan cadangan Full Preliminary Term. Cadangan Fackler untuk tertanggung laki-laki pada tahun pertama sebesar Rp.369.635 sedangkan cadangan Full Preliminary Term sebesar Rp.0. Sedangkan untuk peserta perempuan, cadangan Fackler diperoleh Rp. 226.182 dan untuk cadangan Full Preliminary Term diperoleh Rp.0. Hal ini dikarenakan pada cadangan Full Preliminary Term memperhitungkan biaya operasional dari perusahaan asuransi seperti biaya administrasi, komisi agen, dan biaya-biaya lain yang dibutuhkan oleh perusahaan asuransi. Sedangkan pada cadangan Fackler tidak memperhitungkan sejumlah biaya seperti yang disebutkan pada cadangan Full Preliminary Term. Premium reserves must be calculated correctly in order to minimise losses for the insurance business. The Fackler method and the Full Preliminary Term approach were used in this study to calculate premium reserves for term life insurance. The aim of this research is to compare the approaches for calculating premium reserves for term life insurance. Before determining the reserve value, the single premium, initial annuity, and yearly premium of term life insurance will be established. The research assumptions include that the insured is a man and a woman aged 30 years, that the insurance duration is 30 years, that the interest rate is 5.75%, and that the insurance firm will pay the insured IDR. 200,000,000. According to the results, based on the 2019 Indonesian Mortality Table (TMI), the value of Fackler reserves and Full Preliminary Term reserves in n-year term life insurance contracts provide distinct values. It is discovered that Fackler reserves are more valuable than Full Preliminary Term reserves. The Fackler reserve for male insureds in the first year is IDR 369,635 while the Full Preliminary Term reserve is IDR 0. Meanwhile, Fackler's reserve for female participants was IDR. 226,182, and the Full Preliminary Term reserve was Rp. 0. This is because the Full Preliminary Term reserve accounts for the insurance company's operations expenditures, such as administration fees, agent commissions, and other expenses. Meanwhile, the Fackler reserve excludes a number of charges from the Full Preliminary Term reserve
PRICING OF THE ASIAN OPTION WITH THE KAMRAD-RITCHKEN’S TRINOMIAL MODEL Nabila Wafa’, Jihan; Siswanah, Emy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1457-1468

Abstract

Asian Option determines its payoff option value by the average stock during the option period. This research aims to determine the price of Asian Option by average arithmetic using Kamrad-Ritchken’s Trinomial method. The Kamrad-Ritchken trinomial model is one of the models in the trinomial method used to determine the option value that provides a procedure for determining the barrier parameter or stock price tendency ( ). The stock price tendency makes the trinomial model right on the dotted line of possible stock prices. This study is different from previous studies because the focus of this study is to determine the price of Asian options, both call options and put options with different maturity time variables. The data used for this research are taken from the NVIDIA Corporation (NVDA) data from August 2nd, 2021 – September 29th, 2023. Next, several parameters of option value are determined, which are the initial stock price ( ), contract price ( ), risk-free interest rate ( ), period ( ), stock return ( ), variance ( ), volatility ( ), stock price trend ( ), stock price increase ( ), stock price decrease ( ), stock price increase opportunity ( ), fixed stock price opportunity ( ), stock price decrease opportunity ( ), and barrier ( ). These parameters are used to calculate the price of Asian Option. According to the calculation result by average arithmetic using Kamrad Ritchken’s Trinomial method, the longer the maturity date of an option, the more expensive the option price will be.
OPTIMAL PORTFOLIO FORMATION USING MEAN VARIANCE EFFICIENT PORTFOLIO AND CAPITAL ASSET PRICING MODEL WITH ARTIFICIAL NEURAL NETWORK AS STOCK SELECTION METHOD Siswanah, Emy; Maslihah, Siti; Anggraini, Agustina; Hakim, Muhammad Malik
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2097-2110

Abstract

There are two main things in forming an optimal stock portfolio: stock selection and stock weight determination. This study aims to determine the performance of an optimal portfolio formed using ANN as a stock selection method and MVEP (Mean-Variance Efficient Portfolio) and CAPM (Capital Asset Pricing Model) to determine stock weights. In addition, it is also necessary to determine the characteristics of the stocks formed in the portfolio. The criteria for stock selection are choosing stocks predicted to have maximum mean returns with minimal risk. This research uses data from 10 stocks listed on the Indonesian Stock Exchange. The forecasting results state that ANN can be used to predict stock prices to get a picture of stock prices in the future. Based on the calculation results, BMRI, TLKM, ASII, TPIA, and BBNI stocks were selected to form a stock portfolio. The MVEP and CAPM methods produce stock weights with different characteristics. The MVEP method gives the most significant weight to stocks that have the largest predicted mean return but experience changes in accuracy categories. The CAPM method gives the most significant weight to stocks with less risk than other stocks and has the smallest MAPE value. Empirically, ANN can be used to select stocks to form a portfolio. Stock price predictions with the most significant mean return and small risk can be used as a reference when forming a portfolio using the MVEP and CAPM methods.
Perbandingan Kriteria Kataoka Safety First dan Mean Varians dalam Pembentukan Portofolio Saham Optimal Siswanah, Emy; Abdurakhman, Abdurakhman; Maruddani, Di Asih I
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 2 August 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i2.32846

Abstract

The Markowitz Mean-Variance Portfolio and the Kataoka Safety-First criterion share similarities, as both serve as risk-control methods and suitable for risk-averse investors. This study compares these two approaches in constructing an optimal portfolio and evaluates their respective performances. The findings indicate that the portfolio weights derived from both methods are positive. Empirical evidence suggests that the expected return of the Kataoka Safety-First portfolio is consistently higher than that of the Mean-Variance method. However, this greater return is accompanied by a higher level of risk. Furthermore, the Sharpe and Treynor indices for the Kataoka Safety-First portfolio surpass those of the Mean-Variance method across both portfolio variations analyzed. These results confirm that the Kataoka Safety-First portfolio demonstrates superior performance compared to the Mean-Variance approach. Therefore, the Kataoka Safety-First criterion presents itself as a viable strategy for constructing an optimal portfolio tailored to risk-averse investors.
MODELING OF BOND YIELD CURVE USING CUBIC BEZIER CURVE Siswanah, Emy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (684.49 KB) | DOI: 10.30598/barekengvol16iss4pp1505-1514

Abstract

Investors attracted to Bond have to analyze the Bond yield curve. In this study, the bond yield curve is modeled using a cubic bezier curve. The cubic bezier curve is flexible, precise, and simple to use and evaluate. The bonds used in this study are Surat Berharga Negara (Government Paper) Fix Rate type dated August, 2nd–6th 2021. Bond data is obtained from the Indonesia Stock Exchange https://www.idx.co.id. The results show that the bond yield curve that is formed varies because bond yields change every time following market developments. The cubic bezier curve is able to model the bond yield curve well. Cubic bezier curves have 4 control values ​​that help guide the curve well. The MSE value obtained by the bezier curve is small in general. The MSE values of the cubic bezier curve for the Bond yield data, sequentially from the least to the greatest, are 0,098 on August 4th, 2021; 0,1719 on August 5th, 2021; 0,2161 on August 3rd, 2021; 0,2498 on August 6th, 2021; and 0,2906 on August 2nd, 2021.
Kemampuan Literasi Matematika Peserta Didik Kelas IX berdasarkan Gaya Belajar menurut David Kolb Furqon, Syifa'ul; Siswanah, Emy; Tsani, Dyan Falasifa
Edumatica : Jurnal Pendidikan Matematika Vol 11 No 1 (2021): Edumatica: Jurnal Pendidikan Matematika (April 2021)
Publisher : Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1227.918 KB) | DOI: 10.22437/edumatica.v11i01.11438

Abstract

The purpose of this study was to determine the characteristics of mathematical literacy skills of class IX students based on learning styles according to David Kolb. This study uses an analytical descriptive approach with research subjects of class IX A students of SMP 4 Pemalang in the academic year 2019/2020. The results of the study stated that High, Medium and Lower Diverger Subjects were able to solve math literacy problems level 2, 3 and 5. The Upper Assimilator Subject was able to solve math literacy problems level 2, 3, 4, 5 and 6. The Middle Assimilator was complete at levels 2, 3, 5 and 6. The Lower Assimilator Subject is only completed at levels 2, 3, and 5. The Upper Converger Subject is able to complete level 2, 3, 4, 5, and 6 mathematics literacy. less able at level 3. Lower Converger is complete at level 2 and 3 then less able at level 4. Upper Accomodator subject is able to solve mathematical literacy problems level 3, 4, 5, and 6 then less able at level 2. Middle Accomodator is complete at level 2 and 3. whereas Lower Accommodation is only able to solve level 2 problems and less able to solve level 3 mathematical literacy problems.
Low Welfare Status Modeling Using Mixed Geographically Weighted Regression Method with Fixed Tricube Weighting Function: Pemodelan Status Sejahtera Rendah Menggunakan Metode Mixed Geographically Weighted Regression Dengan Fungsi Pembobot Fixed Tricube Yuliyanti, Tri; Siswanah, Emy; Nisa, Lulu Choirun
Indonesian Journal of Statistics and Applications Vol 6 No 2 (2022)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v6i2p213-227

Abstract

Mixed Geographically Weighted Regression (MGWR) is a method for analyzing spatial data in regression that produces local and global parameters. Parameter estimation using WLS with a fixed tricube weighting function. The object of research in this study is poor population (X1), female household heads (X2), the education (X3), individuals with disabilities (X4), individuals having chronic disease (X5), individuals works (X6), uninhabitable houses (X7), and low welfare status (Y). This reseach applied to the low welfare status (Y) of each district/town in Central Java in 2019, and produced local variables are X1, X3, X5 and global variables are X2, X4, X6, and X7. However, only X1, X4, and X7 have a significant effect on Y in each district/town in Central Java, and X3 has a significant effect on only a few districts/cities, the other, X2, X5, and X6 have no significant effect on the model. The predictor variable has an effect of 98.92% on the model while the remaining 1.18% affected by other factors. The MGWR method divides 2 groups based on significant variables, (a) The first, a district/town whose low welfare status affected by X1, X3, X4, X7 covering Cilacap, Purbalingga, Kendal, Batang, Brebes, Pekalongan Town, and Tegal Town, (b) The second, districts/town whose low welfare status affected by X1, X4, X7 covering Banjarnegara, Purworejo, Temanggung, Kudus, Wonosobo, Pekalongan, Pemalang, Jepara, Wonogiri, Boyolali, Tegal, Magelang, Sukoharjo, Banyumas, Grobogan,  Klaten, Karanganyar,  Kebumen, Blora,  Semarang Town, Pati, Sragen, Demak, Magelang Town, Salatiga Town, Surakarta Town, Semarang, and Rembang.
Co-Authors Abdurakhman Abdurakhman Anggraini, Agustina Di Asih I Maruddani Furqon, Syifa'ul Izzatul Yazidah, Izzatul Lulu Choirun Nisa M. Ismail Maulida, Via Miasary, Seftina Diyah Minhayati Saleh Muhammad Malik Hakim, Muhammad Malik Mukharomah, Rizanatul Multiningsih, Multiningsih Nabila Wafa’, Jihan Nisa, Eva Khoirun Rohman, Ahmad Aunur Rosidah, Zakiyatur Siti Maslihah Tafrikan, Mohamad Tri Yuliyanti Tsani, Dyan Falasifa Ulna, Jihan Ramadhani Ar-Raafi’ Umami, Riza Lathifatul Yustisio, Dheva