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Epsilon: Jurnal Matematika Murni dan Terapan

epsilon
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Published by Universitas Lambung Mangkurat

ISSN : 19784422 EISSN : 26567660 DOI : http://dx.doi.org/10.20527

Core Subject : Science, Engineering,

Decision Sciences, Operations Research & Management Transportation

Jurnal Matematika Murni dan Terapan Epsilon is a mathematics journal which is devoted to research articles from all fields of pure and applied mathematics including 1. Mathematical Analysis 2. Applied Mathematics 3. Algebra 4. Statistics 5. Computational Mathematics

Arjuna Subject : Matematika - Matematika Terapan

Articles 220 Documents

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BIFURKASI DARI HASIL MODIFIKASI SISTEM PERSAMAAN LORENZ Faisal Faisal
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 6, No 1 (2012): JURNAL EPSILON VOLUME 6 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

The Lorenz equation system is the family of Chen's system of equations and systems equation Lu. The system of equations of Lorenz, the system of Chen equations and the system of equations Lu they have three positive parameters. Differences modify the system of equations of Lorenz with the three systems of equations which (Lorenz equation system, Chen equation system, Lu equation system) respectively lies in the second equation. Modification of the system of equations Lorenz has two parameters with one parameter may be negative. In this paper will be analyzed whether or not there is bifurcation. The results of this paper shows the system having subcritical Hopf bifurcation.

UKURAN RISIKO BERDASARKAN PRINSIP PENENTUAN PREMI : PROPORTIONAL HAZARD TRANSFORM Aprida Siska Lestia
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 8, No 2 (2014): JURNAL EPSILON VOLUME 8 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

The problem that will be discussed in this paper is an analysis of one type of risk measure that determines it based on the principle of premium determination (premium-based risk measures), namely Proportional Hazard (PH) transform, both in the form of basic concepts and their properties. It will then assess the size of the risk for some of the total data distribution models of insurance claims that are generally heavy tailed. Where the assessment process is done simulated using Monte Carlo method and recursive method. The discussions made for the distribution of total claims will only be limited to the claims of distributed gamma, Weibull, Pareto, lognormal, and loglogistic and distribution of many claims used in the form of binomial, binomial negative and Poisson.

PEMODELAN PENYAKIT DIFTERI DI SUMATERA BARAT MENGGUNAKAN REGRESI ZERO INFLATED DAN REGRESI HURDLE Fitri Mudia Sari; Pardomuan Robinson Sihombing
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol. 15(1), 2021
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Data that states the number of events in a certain period of time is called count data. Poisson regression is one of the regression models included in the application of GLM that can be used to model the count data. In Poisson regression, there are assumptions that must be met, namely the mean and variance of the response variables must be the same (equidispersion). Several models that are able to overcome overdispersion due to excess zero are the Zero Inflated model and the Hurdle model. This study examines the characteristics of parameter estimation in the modeling of quantified data that is overdispersed due to excess zero using the Zero Inflated Poisson (ZIP), Zero Inflated Negative Binomial (ZINB), Hurdle Poisson (HP) model and the Hurdle Negative Binomial (HNB) model in cases of diphtheria. in West Sumatra in 2018. Based on individual parameter testing and AIC values, the HP model provides better performance than the ZIP, ZINB, and HNB models. So the Hurdle Poisson model is better used in this case than other models

PREDIKSI BEBAN LISTRIK DI KOTA BANJARBARU MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION Muhammad Nazmi Fadilah; Akhmad Yusuf; Nurul Huda
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 14, No 2 (2020): JURNAL EPSILON VOLUME 14 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Kecukupan pasokan energi listrik diukur dengan melihat kemampuan pasokan daya listrik saat beban puncak. Karena sifat tenaga listrik tidak dapat disimpan dalam skala besar, sehingga kebutuhan suatu saat harus dipasok saat itu juga. Pelanggan listrik tercatat pada PT.PLN Rayon Banjarbaru pada tahun 2019 sebanyak 133.726 pelanggan, sedangkan pada tahun 2018 sebanyak 126.747. Jaringan Syaraf Tiruan Backpropagation adalah salah satu cabang kecerdasan buatan yang digunakan mengidentifikasi pola data menggunakan algoritma pembelajaran dalam menyelesaikan permasalahan yang berhubungan dengan prediksi. Algoritma Jaringan Syaraf Tiruan Backpropagation terdiri tiga tahap, yaitu tahap perambatan maju, tahap perambatan-balik, serta tahap perubahan bobot dan bias. Tujuan penelitian ini adalah untuk melakukan prediksi dan mengetahui tingkat akurasi dengan Jaringan Syaraf Tiruan Backpropagation. Data yang digunakan adalah data jumlah beban listrik yang dibangkitkan di kota Banjarbaru dalam kurun waktu 9 tahun dengan 12 unit masukan. Hasil dari penelitian ini adalah tahap pelatihan Jaringan Syaraf Tiruan dengan empat simulasi lapisan sembunyi mendapatkan arsitektur jaringan yang cukup baik yakni arsitektur 12-12-1 dengan nilai MAPE adalah 6,597% dan RMSE adalah 0,032222. Untuk tahap pengujian diperoleh nilai MAPE adalah 7,918% dan RMSE adalah 0,070479 yang dapat digunakan untuk memprediksi jumlah beban listrik dengan cukup baik. Serta tahap prediksi diperoleh nilai MAPE adalah 12,366% dan RMSE adalah 0,113272 yang menunjukkan hasil prediksi kurang baik dikarenakan terjadi penurunan jumlah beban listrik yang dibangkitkan secara signifikan pada bulan Desember 2018 dengan bulan Januari 2019.

PRODUK KARTESIAN IDEAL FUZZY PADA RING Sapuah Sapuah; Saman Abdurrahman; Nurul Huda
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 11, No 1 (2017): JURNAL EPSILON VOLUME 11 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

The concept of algebra fuzzy was initially introduced by Rosenfeld in 1971. In 1991, Malik and Moderson explained if cartesian product of two fuzzy subgroup from same group, then it was fuzzy subgroup too and if cartesian product of two fuzzy ideal from same ring, then it was fuzzy ideal too. We discuss the cartesian product of two or more fuzzy subgroups from different group, then it was fuzzy subgroup too and cartesian product of two or more fuzzy ideal from different ring, then it was fuzzy ideal too.

PENGINTEGRALAN MENGGUNAKAN ATURAN SIMPSON UNTUK INTERVAL TITIK YANG TIDAK SAMA Fitriani Fitriani; Akhmad Yusuf; Yuni Yulida
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 13, No 2 (2019): JURNAL EPSILON VOLUME 13 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

In general, numerical integration is carried out at the same point intervals. But in reality, it is sometimes faced with the problem of integrating a function with unequal point intervals. One method to calculating integrals at unequal interval points is the Simpson rule. Based on it, the research aims to form a general formula of numerical integration for unequal interval points and Simpson rule equation by using the Newton interpolation formula with divided differences, also an errors for unequal interval points by integrating the Taylor’s series. The results of this research were obtained a general formula of numerical integration for unequal interval points, general formula of Simpson's 1/3-rule, general formula of the Simpson's 3/8-rule, and an error for each other’s Simpson’s rules.Keywords : Numerical Integration, Simpson's 1/3-Rule, Simpson's 3/8-Rule, Error.

APLIKASI PERKONGRUENAN DALAM MENYELESAIKAN SISTEM PERSAMAAN LINEAR DUA PEUBAH Yuni Yulida; Muhammad Ahsar Karim
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 3, No 2 (2009): JURNAL EPSILON VOLUME 3 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

This paper discusses the determination of existention and solution of linearequation system with two variables written as:a x b y ca x b y ca x b y c    2 2 21 1 where x, y are integers, and n n n a ,a ,,a ,b ,b ,,b ,c ,c ,,c 1 2 1 2 1 2 are non-negativeintegers, using the application of linear congruency

ESTIMASI MODEL LINEAR PARSIAL DENGAN PENDEKATAN KUADRAT TERKECIL DAN SIMULASINYA MENGGUNAKAN PROGRAM S-PLUS Nur Salam; Dewi Sri Susanti; Dewi Anggraini
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 6, No 2 (2012): JURNAL EPSILON VOLUME 6 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Partial linear model (model semiparametric) is a new approach in the regressionmodels between the two regression models are already popular parametric regression andnonparametric regression. Partial linear model is a model that includes both thecombination of parametric components and nonparametric components. This study usesliterature by studying semiparametric regression analysis, finding and determining theestimated parameters. Partial linear model has the form: : ???????? = ???????????????? + g(????????)+ ???????? with???????? and ???????? are explanatory variables, g (.) is an unknown function (smooth function), β isthe parameter of unknown function, ???????? response variable and ???????? is an error with the mean(????????) = 0 and variance ????????2 = ????(????????2).The results showed that the partial linear model parameter estimation canbe performed using the least squares method in which part of the linear model usingnonparametric kernel approach and subsequent estimation results are substituted into thepartial linear model to estimate the parametric part of the model by using the linear leastsquares method. Results obtained partial linear estimation is ???? ???? (t) = ????????????????????=1 (Yi - ???????????? +???????? ) dengan ???????? = (???? ???? ???? )−???? ???? ???? ???? .Based on the simulation results obtained output values and graphs are for theparametric, graphical display and qqline qqnorm estimator beta (β) is (????) yaitu ????0, ????1and ????2 can be seen clearly, where if n is greater (n → ∞) and the greater replicationiteration r , then the points are spread around the more straight line and a straight line.This indicates the greater n and r, the beta (β) closer to the normal distribution.Nonparametric estimator simulation results in this section are taken as an example of anormal kernel function values approaching g (T). So it can be concluded briefly that if thelarger n (n → ∞), the estimator of the nonparametric part closer to the partial linearmodel g (T).

GRUP FAKTOR YANG DIBANGUN DARI SUBGRUP NORMAL FUZZY Mahfuz Tarmizi; Saman Abdurrahman; Muhammad Mahfuzh Shiddiq
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 13, No 1 (2019): JURNAL EPSILON VOLUME 13 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

A Quotient group is a set which contains coset members and satisfies group definition. These cosets are formed by group and its normal subgroup. A set which contains fuzzy coset members is also called a quotient group. These fuzzy cosets are formed by a group and its fuzzy normal subgroup. The purpose of this research is to explain quotient groups induced by fuzzy normal subgroups and isomorphic between them. This research construct sets which contain fuzzy coset members, define an operation between fuzzy cosets and prove these sets under an operation between fuzzy coset satisfy group definition, and prove theorems relating to qoutient groups and homomorphism. The results of this research are ????????⁄={????????|????∈????} is a qoutient group induced by a fuzzy normal subgroup, where ???? is a fuzzy normal subgroup of a group ????, ???????? is a fuzzy coset, and the binary operation is “∘” where ????????∘????????=???????????? for every ????????,????????∈????????⁄. An epimorphism ???? from a group ???? to a group ????′ and a fuzzy normal subgroup ???? of ???? which is constant on ???????????????? cause quotient goup ????????⁄ and ????′????????⁄ are isomorphic.

PREDIKSI INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN LONG SHORT-TERM MEMORY Akhmad Yusuf
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol. 15(2), 2021
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Pasar modal merupakan tempat bertemunya pihak penjual dan pembeli serta dapat dijadikan sebagai indicator kemajuan suatu negara. Semakin tinggi pergerakan atau aktifitas di pasar modal maka semakin tinggi pula pergerakan ekonomi di suatu Negara tersebut. Bursa Efek Indonesia (BEI) merupakan pasar modal yang terdapat di Indonesia. Index harga saham gabungan (IHSG) merupakan rata-rata harga saham keseluruhan yang berada di Bursa Efek Indonesia (BEI) dan memiliki volatilitas yang tinggi sehingga diperlukan suatu metode untuk memprediksi pergerakan harga IHSG tersebut yang dapat dijadikan sebagai acuan bagi para pembeli (pihak surplus dana). Long Short-Term Memory (LSTM) merupakan sebuah metode forecasting yang dapat digunakan untuk memprediksi data yang bersifat time series. Pada penelitian ini, data yang digunakan berjumlah 1212 data pada interval waktu 16 Februari 2017 sampai 14 Februari 2022 dengan time frame 1D. Data terbagi menjadi 2 bagian, yaitu data training berjumlah dan data testing berjumlah data. Parameter LSTM yang digunakan batch-size 25 dan untuk menguji keberhasilan parameter tersebut digunakan epoch yang berbeda-beda. Epoch sejumlah 50 merupakan model terbaik menghasilkan RMSE lebih kecil yaitu 6.2335 dengan nilai prediksi 6765.5103 dan nilai actual 6807.50

Page 15 of 22 | Total Record : 220

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Mathematics Department, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. Jl. A. Yani KM.35.8 Banjarbaru, Kalimantan Selatan

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Home Page

OAI Link

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Contact Name Yuni Yulida

Contact Email y_yulida@ulm.ac.id

Phone +6281348054202

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Editorial Address Mathematics Department, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. Jl. A. Yani KM.35.8 Banjarbaru, Kalimantan Selatan

Location Kota banjarmasin, Kalimantan selatan INDONESIA

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Abstract

Contact Name
Yuni Yulida

Contact Email
y_yulida@ulm.ac.id

Phone
+6281348054202

Journal Mail Official
epsilon@ulm.ac.id

Editorial Address
Mathematics Department, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. Jl. A. Yani KM.35.8 Banjarbaru, Kalimantan Selatan

Location
Kota banjarmasin,

Kalimantan selatan

INDONESIA