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Yuni Yulida
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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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Kota banjarmasin,
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INDONESIA
Epsilon: Jurnal Matematika Murni dan Terapan
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 210 Documents
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TITIK TETAP PERSEKUTUAN EMPAT PEMETAAN KONTRAKTIF PADA RUANG METRIK CONE Mawaddah, Ainal; Shiddiq, Muhammad Mahfuzh; Huda, Nurul
JURNAL MATEMATIKA MURNI DAN TERAPAN EPSILON Vol 13, No 2 (2019): JURNAL EPSILON VOLUME 13 NOMOR 2
Publisher : Mathematics Department, Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v13i2.2049

Abstract

Huang Long Guang dan Zhang Xian pada tahun 2006 telah memperkenalkan metrik yang lebih baru yang disebut metrik cone. Suatu himpunan tak kosong X yang dilengkapi metrik cone d disebut ruang metrik cone. Suatu pemetaan memiliki titik tetap yang tunggal jika pemetaan tersebut merupakan pemetaan kontraktif. Konsep titik tetap persekutuan di ruang metrik cone juga harus memenuhi beberapa kondisi pemetaan yang bersifat coincidence point, point of coincidence, dan kompatibel lemah. Penelitian ini mengkaji titik tetap persekutuan untuk empat pemetaan yang kontraktif pada ruang metrik cone. Hasil penelitian ini menunjukkan bahwa empat pemetaan S, T, I dan J memiliki titik tetap persekutuan yang tunggal pada ruang metrik cone.Kata Kunci: ruang metrik cone, titik tetap persekutuan, pemetan kontraktif, coincidence point, point of coincidence, kompatibel lemah
REDUKSI DIMENSI INPUT PADA JARINGAN SYARAF PCA-RBF DENGAN SINGULAR VALUE DECOMPOSITION Abdul Hakim Maulana; Oni Soesanto; Thresye Thresye
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (240.444 KB) | DOI: 10.20527/epsilon.v9i2.13

Abstract

Artificial neural network is an information processing system that has characteristics similar to biological neural networks. Artificial neural networks are divided into single layers and multiple layers. One of the multiple layer neural networks is Radial Basis Function (RBF). RBF is known to have high computing speed. However, the performance of RBF decreases when it involves the input space with high dimension so it requires simplification of the network. One method of simplifying RBF with respect to the dimension of input space is to use Principal Component Analysis (PCA). When the number of data variables is greater than the number of observations, the ability of PCA to be less effective then required Singular Value Decomposition (SVD) to solve the problem. The purpose of this research is to apply Singular Value Decomposition (SVD) process on PCA-RBF neural network. This study discusses the neural network PCA-RBF. PCA serves to reduce the input dimension of RBF. This dimension of input is known as the principal component (PC). PC determination process is done using PCA method combined with SVD. Furthermore, the PC is used as a new input to the RBF and a clustering process is performed on the PC using the K-means method for the initialization of the RBF center. Inisisalisasi center is the first step RBF in classification. The classification process in RBF consists of two processes namely training and testing. The result of this research is the SVD process on PCA to reduce the dimension of input data consisting of the process of determining the right singular matrix (V) ie calculating the ATA matrix, finding the eigenvalues (λ) and eigenvectors of the ATA matrix, conducting Gram-Schmidt and normalization , and the process of forming Principal Component (PC) is by multiplying the matrix of training data with right singular matrix (V), so that PC is used as new input to RBF. In this research is given example of classification data that is Landsat satellite data. After repeating 30 times the average success of classification in Landsat training data is 79,889% with mean error 20,111%, while for data testing Landsat obtained average success equal to 93,333% with error percentage is 6,667%.
MODEL ARIMA (p, d, q) PADA DATA KEMATIAN IBU HAMIL (STUDI KASUS DI RSUD ULIN BANJARMASIN) Dewi Anggraini; Faisal Faisal
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (222.179 KB) | DOI: 10.20527/epsilon.v3i2.39

Abstract

Time series analysis is a sequence of quantitative observation at a certain timeinterval, such as daily, monthly, yearly, etc. This analysis has been used foridentifying the characteristic, pattern, and model of observed data in the specifiedpast period that leads to predict the future observation values. Applications oftime series analysis include all aspects such as, meteorology, economy, andmedical area. The deaths prevalence of pregnancy women at delivering process isstill very high. This leads to a significant medical problem in Indonesia. In 2003,this case has been reported 20 women, including 3 cases due to blooding, 3 casesdue to eclampsy, and 14 cases due to other factors. This research is conducted togive an appropriate model to predict the deaths of pregnancy women in the future.The method of this research is using purposive sampling technique, which isgathering 72 secondary data of monthly deaths pregnancy women from2003 - 2008 in the midwife room of Ulin Hospital, Banjarmasin. The experimentprocedures are identifying the appropriate ARIMA model to give the trendmonthly deaths description of pregnancy women, and evaluating the fitted ARIMAmodel to forecast monthly deaths of pregnancy women in the future 10 yearsbased on the given historical data.Based on the conducted analysis, it is found that monthly deaths of pregnancywomen between 2003 and 2008 in Ulin Hospital, Banjarmasin has experienceda slightly increase. The data are discrete with monthly expected value equal to0.625, where the smallest and biggest deaths are 0 and 3 people, respectively.Beside this, it has been investigated that ARIMA (0, 0, 0) or ARMA (0, 0) is thebest ARIMA model for this case because it results the minimum value of AICC.
PCA-RBPNN UNTUK KLASIFIKASI DATA MULTIVARIAT DENGAN ORTHOGONAL LEAST SQUARE (OLS) Oni Soesanto
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 4, No 2 (2010): JURNAL EPSILON VOLUME 4 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.318 KB) | DOI: 10.20527/epsilon.v4i2.64

Abstract

This study will examine the PCA-RBPNN (Principal Component Analysis-Radial Basis) Probabilistic Neural Network) for the classification of multivariate data. The Main Component Analysis (PCA) has widely known in statistics as a method used to reduce the input dimension of the data multivariate by minimizing information loss. In this case, PCA is used to reduce dimensional input on the RBPNN neural network. The clustering process and initialization center is done with Self-Organizing Map (SOM). For the determination of weights during the learning process on the RBPNN network, using the Orthogonal Least Square (OLS) algorithm. Furthermore, PCA-RBPNN method is used for the classification of multivariate data. Accuracy of PCA-RBPNN classification is simulated and compared with the usual RBPNN model.
PENERAPAN TEORI KENDALI PADA MASALAH PROGRAM DINAMIK Pardi Affandi; Dewi Anggraini; Nur Salam
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.036 KB) | DOI: 10.20527/epsilon.v6i1.81

Abstract

This study examines the application of Control Theory to the problem of Dynamic Program. Dynamic program is a design analysis in math to determine a series decisions relating to the decision-making process are gradually double to optimize problem solving effectively. Classic problems in dynamic programming is the concept of phase, state and acquisition. Problem solving will use Control Theory.
ESTIMASI PARAMETER UNTUK DISTRIBUSI HALF LOGISTIK Rizqi Elmuna Hidayah; Nur Salam; Dewi Sri Susanti
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 7, No 1 (2013): JURNAL EPSILON VOLUME 7 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (254.502 KB) | DOI: 10.20527/epsilon.v7i1.92

Abstract

Point estimation is a value obtained from the samples and used as anestimator of the parameter whose value is unknown. To determine the point estimatorcan be used several methods, such as Maximum Likelihood Estimator (MLE) and Methodof Moments Estimator (MME). Half logistic distribution is used for lifetime data such asthe survival data of a unit or individual of a particular situation in terms of failure time.In this journal, several methods for estimating the location and scale parameters of thehalf-logistic distribution.
PEMBENTUKAN FUNGSI PELUANG BIRTH-DEATH PROCESS MELALUI SISTEM PERSAMAAN DIFERENSIAL LINIER HOMOGEN Etza Budiarti; Karim Karim; Dewi Sri Susanti
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (187.716 KB) | DOI: 10.20527/epsilon.v8i2.108

Abstract

PEMBENTUKAN FUNGSI PELUANG BIRTH-DEATH PROCESS MELALUI SISTEM PERSAMAAN DIFERENSIAL LINIER HOMOGEN
APLIKASI MODEL ANTRIAN PADA OPTIMALISASI PELAYANAN PT KAI STASIUN LEMPUYANGAN YOGYAKARTA Kris Suryowati; Maria Titah JP; Etika Permata Sari
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 12, No 1 (2018): JURNAL EPSILON VOLUME 12 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.083 KB) | DOI: 10.20527/epsilon.v12i1.201

Abstract

Model antrian merupakan pemodelan matematika yang berkaitan dengan masalah mengantri. Pelayanan pada PT Kereta Api Indonesia Stasiun Lempuyangan Yogyakarta pada akhir pekan (week end) biasanya terjadi peningkatan kedatangan pelanggan cukup tinggi sehingga waktu antar kedatangan lebih kecil dari pada waktu pelayanan, dan garis tunggu (waiting line) cukup panjang. Hal ini menunjukkan tingkat pelayanan tidak optimal, sehingga pada penelitian ini dibahas pembentukan model antrian yang tepat dalam rangka peningkatan kualitas sistem pelayanan. Pada pembahasannya diasumsikan tidak ada pelanggan yang saling mendahului ataupun meninggalkan antrian sebelum selesai dilayani. Data survey waktu antar kedatangan, rata-rata jumlah kedatangan pelanggan per waktu, dan rata-rata pelayanan loket pembelian tiket jarak jauh, serta hasil uji hipotesis menunjukan rata-rata tingkat kedatangan pelanggan berdistribusi Poisson, waktu antar kedatangan berdistribusi eksponensial, rata-rata waktu pelayanan berdistribusi eksponensial, sehingga bentuk modelnya (M/M/1): (GD/∞/∞). Hasil simulasi diperoleh model optimal (M/M/2): (GD/∞/∞). Model antrian pada pelayanan check in tiket (M/M/2): (GD/∞/∞) menunjukkan sudah optimal. Pelayanan cetak tiket mandiri menunjukkan model self service dan modelnya berbentuk (M/M/∞): (GD/∞/∞), hal ini perlu ditingkatkan kualitas layanannya dengan mengganti komputer sesuai spesifikasinya dan diberi petugas, sehingga waktu pelayanan lebih efektif.
PEMBAGI NOL PADA MATRIKS ATAS RING KOMUTATIF Nurhayani, Mega; Thresye, Thresye; Huda, Nurul
JURNAL MATEMATIKA MURNI DAN TERAPAN EPSILON Vol 13, No 1 (2019): JURNAL EPSILON VOLUME 13 NOMOR 1
Publisher : Mathematics Department, Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (70.376 KB) | DOI: 10.20527/epsilon.v13i1.1326

Abstract

Matriks atas ring komutatif adalah matriks yang entri-entrinya dibangun dari ring komutatif. Himpunan matriks atas ring komutatif membentuk struktur ring terhadap operasi penjumlahan matriks dan operasi pergandaan matriks. Struktur yang terbentuk atas matriks yang entri-entri dari ring komutatif atau dapat disimbolkan  merupakan ring. Selanjutnya  dikatakan ring dengan pembagi nol jika terdapat dua elemen matriks yang tidak sama dengan nol akan tetapi ketika diberikan operasi pergandaan maka bernilai nol. Tulisan ini membahas sifat-sifat pembagi nol pada matriks atas ring komutatif, yaitu jika , dengan  adalah ring komutatif, maka matriks  merupakan pembagi nol kiri dalam  jika dan hanya jika matriks  merupakan pembagi nol kanan dalam . Kata kunci : Ring komutatif, pembagi nol, matriks, matriks atas ring komutatif.
PERAMALAN CURAH HUJAN DI KALIMATAN SELATAN DENGAN JARINGAN SYARAF TIRUAN Gt.Khiruddin Indra Permana; Ahmad Yusuf; Nur Salam
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 1 (2015): JURNAL EPSILON VOLUME 9 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (274.795 KB) | DOI: 10.20527/epsilon.v9i1.7

Abstract

South Kalimantan is in the area of high rainfall so it is included in the criteria of the rainy season. Artificial Neural Network (ANN) is one method that can identify patterns of data from rainfall forecasting system by conducting training method. One of the model ANN used is Backpropagation (BP). The training of a network using BP consists of 3 steps, namely: feedforward input pattern training, calculation and BP from the set of error and weight adjustment. The purpose of this research is to predict rainfall in South Kalimantan in 2015 using JST BP. The research method used in this research is literature study and case study related to rainfall forecasting, JST and BP. This research procedure will begin by collecting data, analyzing data and training data then predicting the data to be achieved. The results of this research is the highest rainfall in South Kalimantan in 2015 occurred in the area of Martapura Kota Kab. Banjar in January. In this period of the month there is a possibility that the area will experience an increase in water level or flood. While the lowest rainfall occurred in the region Pelaihari Kab. Land of the Sea around August and September. In this period the rainfall is so low that the area is likely to be in dry conditions.

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