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<![CDATA[PENERAPAN TEORI KENDALI PADA MASALAH INVENTORI ]]>
<![CDATA[Pardi Affandi]]>;
<![CDATA[Faisal Faisal]]>;
<![CDATA[Yuni Yulida]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 6, No 2 (2012): JURNAL EPSILON VOLUME 6 NOMOR 2 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v6i2.86
<![CDATA[This paper will examine the application of Control Theory to the problem Inventory, will be developed the first model in which dynamic demand and inventory available all the time. The discussion focused on inventory system analysis nonlinear-shaped production and production costs are treated as a function each inventory level and production level. Then expanded the model first to the next model where the decline in goods is taken into account. Level damage is calculated as a function of time with the amount already available. For both models, optimal control theory will be used to obtain policy optimal control, to obtain optimal results.]]>
<![CDATA[MODEL MATEMATIKA KOMENSALISME ANTARA DUA SPESIES DENGAN SUMBER TERBATAS ]]>
<![CDATA[Friska Erlina]]>;
<![CDATA[Yuni Yulida]]>;
<![CDATA[Faisal Faisal]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 8, No 1 (2014): JURNAL EPSILON VOLUME 8 NOMOR 1 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v8i1.102
<![CDATA[MODEL MATEMATIKA KOMENSALISME ANTARA DUA SPESIES DENGAN SUMBER TERBATAS]]>
<![CDATA[MODEL MATEMATIKA PADA PENYEBARAN MALARIA DI KALIMANTAN SELATAN ]]>
<![CDATA[Rahmi Hidayati]]>;
<![CDATA[Faisal Faisal]]>;
<![CDATA[Yuni Yulida]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 11, No 2 (2017): JURNAL EPSILON VOLUME 11 NOMOR 2 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v11i2.119
<![CDATA[Malaria adalah penyakit menular yang disebabkan plasmodium melalui gigitan nyamuk Anopheles betina. Tujuan dari penelitian ini adalah untuk menjelaskan terbentuknya model penyebaran malaria di Kalimantan Selatan, menganalisis dan menginterpretasi tingkat infeksinya. Penelitian ini dilaksanakan dengan mencari data kasus malaria kemudian mengkaji model SIR, menentukan asumsi yang diperlukan, membentuk model SIR, menentukan kestabilan model dan menganalisis tingkat infeksi malaria dengan model matematika. Model penyebaran malaria di Kalimantan Selatan merupakan sistem persamaan diferensial nonlinier. Pada model ini diperoleh dua titik ekuilibrium yaitu bebas penyakit dan titik ekulibrium endemik. Titik ekuilibrium bebas penyakit stabil asimtotik. Setelah dianalisis tingkat infeksi di Kalimantan Selatan untuk setiap kabupaten menggunakan model tersebut, diperoleh tingkat infeksi malaria paling rendah terjadi di Banjarmasin dan paling tinggi terjadi di Kabupaten Balangan. Infeksi malaria mengalami penurunan setiap tahunnya sehingga infeksinya akan hilang seiring berjalannya waktu hal ini menjelaskan bahwa Kalimantan Selatan akan bebas dari infeksi malaria.Kata Kunci : malaria, model SIR, titik ekuibrium, kestabilan, bilangan reproduksi dasar]]>
<![CDATA[BILANGAN RAINBOW CONNECTION BERDASARKAN DERAJAT MINIMUM PADA GRAF ]]>
<![CDATA[Widya Anggraini]]>;
<![CDATA[Muhammad Mahfuzh Shiddiq]]>;
<![CDATA[Pardi Affandi]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 12, No 2 (2018): JURNAL EPSILON VOLUME 12 NOMOR 2 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v12i2.318
<![CDATA[Graf ????????=(????????,????????) terdiri dari 2 himpunan yaitu himpunan tak kosong ???????? dan himpunan ???????? yang mana elemen ???????? disebut titik dan elemen ???????? disebut sisi. Banyaknya sisi yang berhubungan dengan titik ???????? disebut derajat dan minimum dari banyaknya sisi yang berhubungan dengan titik ???????? pada graf ???????? disebut derajat minimum (????????(????????)). Salah satu topik yang dipelajari dalam pewarnaan pada graf adalah rainbow connection. Pewarnaan sisi di ???????? dikatakan rainbow connected jika setiap dua titik yang berbeda dihubungkan oleh lintasan rainbow. Bilangan rainbow connection dari graf terhubung ???????? ditulis ????????????????(????????) yaitu minimum dari banyaknya warna yang diperlukan untuk membuat ???????? bersifat rainbow connected. Tujuan dari penelitian ini adalah untuk menentukan bilangan rainbow connection dalam graf berdasarkan derajat minimumnya. Penelitian dilakukan dengan cara mencari bilangan rainbow connected untuk graf 2-terhubung. Langkah berikutnya dicari juga untuk kasus graf 2-terhubung yang tidak memuat jembatan. Tahap terakhir dari dua dua graf tersebut dilakukan pencarian bilangan rainbow connected untuk graf dengan derajat minimum 3. Hasil dari penelitian ini adalah untuk graf terhubung ????????, jika memiliki ????????≥3 maka memiliki bilangan rainbow connection lebih dari 5????????/6.Kata Kunci :graf, derajat, bilangan rainbow connection.]]>
<![CDATA[PERKIRAAN SELANG KEPERCAYAAN UNTUK NILAI RATA-RATA PADA DISTRIBUSI POISSON ]]>
<![CDATA[Randy Toleka Ririhena]]>;
<![CDATA[Nur Salam]]>;
<![CDATA[Dewi Sri Susanti]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 10, No 1 (2016): JURNAL EPSILON VOLUME 10 NOMOR 1 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v10i1.54
<![CDATA[Confidence interval is an interval between two value, where we believe that the parameter value lay within those interval. To express it, approximate interval were conducted. If the parameter value is unknown, probability will be use rather than exact value. Approximation that conduct express probability that an interval contain parameter value that we estimate. One of parameter value to compute is mean. One of well-known distribution is Poisson ditribution. The purpose of this study is to find approximate interval for the mean of random variable with Poisson distribution. The result of research is confidence interval for poisson distribution by using pivotal quantity method. Based on pivotal quantity method, approximate interval for the mean of poisson distribution with the size of a large sample is???????? ???? ????????????− ????????????????/2 ???????????????? ???????? < ???????? < ???????????? + ????????????????/2 ???????????????? ???????? ???? = 1− ????????]]>
<![CDATA[KOMPUTASI METODE SIMPLEKS PADA PENYELESAIAN PROGRAM LINIER ]]>
<![CDATA[Ahmad Yusuf]]>;
<![CDATA[Dewi Sri Susanti]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 4, No 1 (2010): JURNAL EPSILON VOLUME 4 NOMOR 1 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v4i1.44
<![CDATA[One of the methods that can be used to solve linear program problem is a simplex method. In this study, researchers will try to make a computational algorithm the simplex method that can be used for the completion of the linear program, so obtained a series of efficient completion processes and optimal end results. This research generate program code Computing using Borland Delphi 6.0 programming language which can be used to solve linear program problems by using simplex method.]]>
<![CDATA[KONSTRUKSI SEMIGRUP REGULER DENGAN TRANSVERSAL INVERS IDEAL KUASI ]]>
<![CDATA[Thresye Thresye]]>;
<![CDATA[Na'imah Hijriati]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 5, No 1 (2011): JURNAL EPSILON VOLUME 5 NOMOR 1 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v5i1.70
<![CDATA[A transversal inverse o S of a regular semigrup S is called a quasi ideal transversal inverse or Q-transversal inverse if o o o S SS S where o S is the quasi ideal of S. Let S is a regular semigrup with transversal invers o S which is the quasi ideal of S. For example o o oo R xS: x x x x and eg o oo o L aS: aa a a, then R and L is an orthodox semigrup with transverse inverse o S which is ideal right of R and is the left ideal of L. Can be constructed regular semigrup with transversal inverse ideal quasi-shaped o o R L x, a R L: x a .It is connected with a band, then a regular semigrup with transverse inverse ideal quasi-shaped o o R B x, e R B: x x e]]>
<![CDATA[TEKNIK PERAMALAN MENGGUNAKAN METODE PEMULUSAN EKSPONENSIAL HOLT-WINTERS ]]>
<![CDATA[Siti Nur Hamidah]]>;
<![CDATA[Nur Salam]]>;
<![CDATA[Dewi Sri Susanti]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 7, No 2 (2013): JURNAL EPSILON VOLUME 7 NOMOR 2 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v7i2.97
<![CDATA[Time series forecasting is a method used to determine what might happen in the future based on information obtained in the past. One method used in time series forecasting is a Holt-Winters exponential smoothing method. This method can be used for time series data with trend and seasonality components. This method is based on three smoothing equations: overall smoothing, trend, and seasonal components. Holt-Winters exponential smoothing method consists of multiplicative and additive seasonality models. The method of this research is literature study by collecting and studying references that are relevant to the idea of this research, and then applying the Holt-Winters exponential smoothing method into data. The results of this research show that the multiplicative seasonality model of Holt-Winters exponential smoothing method can be used if data represent an increase in long-term and seasonal fluctuations which is the increasingly bigger with the increasing of observation time periods. These patterns identify the non-stationary of mean and variance. While, the additive seasonality model can be used if data show an increase in long-term and seasonal fluctuations that are relatively constant with the increasing of observation time. Time series forecasting is a method used to determine what might happen in the future based on information obtained in the past. One method used in time series forecasting is a Holt-Winters exponential smoothing method. This method can be used for time series data with trend and seasonality components. This method is based on three smoothing equations: overall smoothing, trend, and seasonal components. Holt-Winters exponential smoothing method consists of multiplicative and additive seasonality models. The method of this research is literature study by collecting and studying references that are relevant to the idea of this research, and then applying the Holt-Winters exponential smoothing method into data. The results of this research show that the multiplicative seasonality model of Holt-Winters exponential smoothing method can be used if data represent an increase in long-term and seasonal fluctuations which is the increasingly bigger with the increasing of observation time periods. These patterns identify the non-stationary of mean and variance. While, the additive seasonality model can be used if data show an increase in long-term and seasonal fluctuations that are relatively constant with the increasing of observation time]]>
<![CDATA[MEMETRIKKAN RUANG MERIK CONE DENGAN MENORMKAN RUANG BANACH ]]>
<![CDATA[Ahmad Maulidi]]>;
<![CDATA[Mohammad Mahfuzh Shiddiq]]>;
<![CDATA[Nurul Huda]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 11, No 1 (2017): JURNAL EPSILON VOLUME 11 NOMOR 1 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v11i1.113
<![CDATA[Huang and Zhang introduced the cone metric space, by replacing codomain from the set of real numbers into an ordered Banach space on a cone, where the cone is a non empty subset of real Banach space that satisfy certain other properties. In this study also explained about the norm space which is a pair of a vector space with a norm that satisfy some specific properties. Furthermore, Banach space is a complete norm space and space norm says completed if every Chaucy sequence in norm space is convergent.In this paper, the researcher want to study how to metrizability of metric spaces via renorming the Banach spaces. This research was conducted by explaining and proving how to metrizability of cone metric spaces via renorming the Banach spaces. The result is a metric space cone can be made into an ordinary metric space with a metric defined by ????????(????????,????????)=‖|????????(????????,????????)|‖]]>
<![CDATA[METODE PUC DAN ILP UNTUK PERHITUNGAN AKTUARIA DAN ASET PASAR PROGRAM PENSIUN ]]>
<![CDATA[Noor Baitirahmah]]>;
<![CDATA[Dewi Sri Susanti]]>;
<![CDATA[Aprida Siska Lestia]]>
<![CDATA[ EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 12, No 2 (2018): JURNAL EPSILON VOLUME 12 NOMOR 2 ]]>
Publisher : <![CDATA[Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat ]]>
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DOI: 10.20527/epsilon.v12i2.313
<![CDATA[Program dana pensiun merupakan badan hukum yang mengelola dan menjalankan program yang menjanjikan manfaat pensiun bagi pesertanya. Manfaat pensiun merupakan pembayaran berkala yang dibayarkan kepada peserta di waktu pensiun. Besar dan cara pendanaan suatu program pensiun dapat ditentukan dengan menggunakan metode perhitungan aktuaria dengan tujuan menentukan iuran normal (????????????????????????) dan kewajiban aktuaria (????????????????????????). Penelitian ini bertujuan menjelaskan rumus dan perhitungan aktuaria, serta proses perhitungan aset pasar dengan metode PUC dan ILP. Formula perhitungan aktuaria metode ???????????????????? dan ???????????? , untuk iuran normal didapatkan dari penjabaran definisi dalam metodenya, sedangkan formula kewajiban aktuarianya didapatkan dari persamaan awal kerajiban aktuaria. Aset pasar merupakan total aset yang dimiliki suatu program pensiun. Proses perhitungan aset pada waktu t dilakukan dengan menghitung unfunded liability, supplementary contribution, dan contribution pada waktu ????????−1. Dari nilai aset pasar didapatkan loss, dimana nilai loss mengindikasikan pendanaan program pensiun mengalami kerugian atau tidak. Jika ???????????????????????????????? bernilai positif maka program pensiun mengalami kerugianKata kunci : Program Dana Pensiun, Santunan Definit, Perhitungan Aktuaria, Aset Pasar, PCU dan ILP]]>
