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<![CDATA[ANALISIS PENJADWALAN DISTRIBUSI PUPUK BERSUBSIDI MENGGUNAKAN METODE DISTRIBUTION REQUIREMENT PLANNING (DRP) (STUDI KASUS PADA PT. PETROKIMIA GRESIK) ]]>
<![CDATA[Dewi Sukmawati]]>;
<![CDATA[Bambang Irawanto]]>
<![CDATA[ Jurnal Matematika Vol 3, No 2 (2014): JURNAL MATEMATIKA ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[ ABSTRACT. The Distribution of products in PT. Petrokimia Gresik carried out on the demand of consumers of each district in the province. The distribution is run on irregular or random, either in time or quantity distribution. Activity affects the distribution of the total cost of inventory the company issued in the procurement of supplies, therefore the company needs to pay close attention to the application System of distribution’s activity to optimize the distribution of subsidized fertilizer schedule in order to maintain time and cost efficiency. Distribution Requirement Planning (DRP) is a method for handling the procurement of supplies in a multi-level distribution network. DRP method relates to the size of ordering lot and the amount of safety stock. DRP method reduce the total cost of inventory and the frequency distribution of activity by determining the distribution of effective scheduling in consideration that the distribution is done in accordance lot size or multiples thereof and the amount of safety stock required. From the research, the activity of distribution schedule of subsidized fertilizer is obtained in Region DC of Lampung in 2013 with the total stockpile cost 7.875.167.077 IDR of inventory at PT. Petrokimia Gresik within 9 months. Distribution of subsidized fertilizer each product that executed simultaneously on day 22 in each period to the 4 buffer warehouses in Lampung region. Keywords: ]]>
<![CDATA[ECONOMIC PRODUCTION QUANTITY DALAM KASUS PRODUKSI BARANG YANG TIDAK SEMPURNA DAN PENGERJAAN KEMBALI SERTA PENGEMBALIAN BARANG TANPA STOCKOUT ]]>
<![CDATA[Adhie Wijaya Litianko]]>
<![CDATA[ Jurnal Matematika JURNAL MATEMATIKA NO 2 2016 ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[,Abstrak. Model EPQ biasa digunakan dalam masalah pengendalian persediaan untuk menentukan kebijakan dan mengawasi tingkat persediaan. Permasalahan persediaan adalah bagaimana cara menentukan jumlah produksi optimal dengan biaya total persediaan yang minimum. Asumsi umum yang digunakan adalah semua barang yang dihasilkan sempurna. Pada Tugas Akhir ini dibahas mengenai Model Economic Production Quantity dalam kasus produksi barang yang tidak sempurna dan pengerjaan kembali serta pengembalian barang tanpa Stockout, dimana barang yang diproduksi tidak semua sempurna dan kemungkinan adanya barang gagal. Barang yang belum sempurna akan dikerjakan kembali sebelum dapat dijual. Pada model ini juga dipertimbangkan tentang barang yang belum sempurna yang lolos dari pengawasan dan berakhir di tangan konsumen dan mengakibatkan pengembalian barang. ]]>
<![CDATA[PRODUK GRAF FUZZY INTUITIONISTIC ]]>
<![CDATA[Zumiafia Ross Yana Ningrum]]>;
<![CDATA[Lucia Ratnasari]]>
<![CDATA[ Jurnal Matematika Vol 1, No 1 (2012): jurnal matematika ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[An intuitionistic fuzzy graph G:V,E consist of a couples of node sets V and set of edges E which the sum of degree membership and degree non membership each of nodes and each of edges in closed interval [0,1], the degree membership each of edges is less than or equal with the minimum of degree membership each nodes of incident, and degree non membership each of edges is less than or equal with the maximum degree non membership each nodes of incident. Product fuzzy graph was defined by Dr. V. Ramaswamy and Poornima B. Product fuzzy graph is fuzzy graph, where the degree membership each of edges is less than or equal with product of the between degree of membership each nodes of incident. In this paper we study the definitions of product intuitionistic fuzzy graph, product intuitionistic fuzzy graph complete, further discussion about the complement of product intuitionistic fuzzy graph, join of product intuitionistic fuzzy graph and multiplication of product intuitionistic fuzzy graph and their characteristics.]]>
<![CDATA[PELABELAN GRACEFUL SATU MODULO PADA BEBERAPA GRAF EULE ]]>
<![CDATA[Isa Isa]]>;
<![CDATA[Lucia Ratnasari]]>
<![CDATA[ Jurnal Matematika Vol 3, No 4 (2014): JURNAL MATEMATIKA ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[ ABSTRACT. A graph with edges is said to be one modulo graceful graph () if there is a injective function from vertex set of graph to in such a way that induces a function from edge set of graph to defined as is bijective. In this Last Project, the following Euler graphs : n-polygonal snakes, and under certain conditions which admit one modulo graceful labeling () are learned. ]]>
<![CDATA[BILANGAN DOMINASI−LOKASI PERSEKITARAN TERBUKA PADA GRAF TREE ]]>
<![CDATA[Riko Andrian Riko Andrian]]>
<![CDATA[ Jurnal Matematika JURNAL MATEMATIKA NO 4 2016 ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[R ABSTRAK. Himpunan subset dari himpunan titik disebut himpunan dominasi jika setiap titik di adjacent dengan setidaknya satu titik di . Suatu himpunan dominasi didalam graf merupakan himpunan dominasi-lokasi persekitaran terbuka untuk jika untuk setiap dua titik pada himpunan dan tidak kosong dan berbeda. Bilangan dominasi-lokasi persekitaran terbuka dinotasikan dengan merupakan kardinalitas minimum dari suatu himpunan dominasi-lokasi persekitaran terbuka. Pada tugas akhir ini dikaji himpunan dominasi-lokasi persekitaran terbuka pada graf tree. Graf Tree dengan order memiliki bilangan dominasi-lokasi persekitaran terbuka ⌈ ⁄ ⌉ . Kata kunci: Himpunan dominasi-lokasi persekitaran terbuka, bilangan dominasi -lokasi persekitaran terbuka.]]>
<![CDATA[OPTIMASI ALIRAN PADA JARINGAN DENGAN ALGORITMA SUCCESSIVE SHORTEST PATH ]]>
<![CDATA[Khoirum muslimah]]>;
<![CDATA[Siti Khabibah]]>
<![CDATA[ Jurnal Matematika Vol 1, No 1 (2012): jurnal matematika ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[Optimization is a process flow to achieve the ideal (the effective value can be achieved) of an object traveling from one place to another within a network. Transportation problems are part of the linear program is usually completed by the usual simplex method. While the transport network is a visualization of the transportation problem into a graph problem. At this final project method or algorithm used in obtaining optimal flow is the successive shortest path algorithm. The first is to find the shortest path of the transport network. The second is to choose a node with a value of supply (before supply is applied to some demand) and the node with the demand . The third is to calculate , with arc on shortest path to . Then send units of flow from node to node along the shortest path in the residual network. At the end of the optimal flow will be obtained, if the condition residual value does not negative of all the arcs in the residual network and value for all . Key words: successive shortest path, the optimization of flow, transport networks]]>
<![CDATA[KUS-ALJABAR DAN ASPEK ALJABAR TERKAIT ]]>
<![CDATA[Melly Nur Aziz]]>;
<![CDATA[Suryoto Suryoto]]>
<![CDATA[ Jurnal Matematika Vol 3, No 2 (2014): JURNAL MATEMATIKA ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[A KUS-algebra is a nonempty set with a binary operation and has special element and satisfy the axioms of KUS-algebra. KUS-algebra structure has simialarities with other algebraic structures that KU-algebra. Every KUS-algebra on where then is not a KU-algebra. That the other algebraic structures, KUS-algebra also has substructure called KUS-subalgebra, ideal of KUS-algebra called KUS-ideal and homomorphism of KUS-algebra called KUS-homomorphism.]]>
<![CDATA[ANALISIS KEPADATAN ARUS LALU LINTAS DUA LAJUR SEARAH DENGAN MENGGUNAKAN MODEL KONTINUM SEDERHANA ]]>
<![CDATA[Liza Alifiana]]>
<![CDATA[ Jurnal Matematika JURNAL MATEMATIKA NO 4 2016 ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[ ABSTRACT.Jalan Gombel Lama, Semarang is a two-lane road in the same direction. Theroadwas relatively dense even jammed at certain hours. In this thesis analyzed the value of density onthese roads by using a simple continuum model. Simple continuum model is one model of the flowof traffic lanes. This model explains the relationship speed, density, and traffic flow. This modelalso explains the interaction between the two lanes, where vehicles are driven on a lane can moveto the other lane that is more tenuous. Density values obtained by finding the numerical solution ofthe model using the finite difference method Lax Friedrichs. The solution is used to determine thevalue of the density on the road. From the data simulation density values obtained on both lanesalmost the same so that the value of the level of small displacement vehicles.Keywords:simple continuum model, Lax Friedrichs]]>
<![CDATA[PENYELESAIAN MASALAH LINTASAN TERPENDEK FUZZY DENGAN MENGGUNAKAN ALGORITMA CHUANG – KUNG DAN ALGORITMA FLOYD ]]>
<![CDATA[Anik Musfiroh]]>;
<![CDATA[Lucia Ratnasari]]>
<![CDATA[ Jurnal Matematika Vol 1, No 1 (2012): jurnal matematika ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[Abstract : In the classic graph, shortest path problem is related problem with determination of the which are connected in a graph that form the shortest distance between source node and the destination node. This idea is extended to solve the fuzzy shortest path problem. In this paper, will be discussed about Chuang - Kung algorithm and Floyd algorithm to solve shortest path problem. Chuang - Kung algorithm’s steps is to determine all pass possible path from source node to destination node, then compute value of similarity degree SLmin, Li with Lmin is the fuzzy shortest length and Li is length of possible path. While for Floyd algorithm, the first step is to determine the initial distance matrix D0 and the matrix of the initial order S0 , then check this elements. If in matrix Dk element is dik+dkj<dij so dij replaced with Lmin dij, dik+dkj . Then replace elements matrix Sk with k . Changes sij in matrix Sk following to changes dij on matrix Dk .]]>
<![CDATA[FUNGTOR KOVARIAN PADA KATEGORI ]]>
<![CDATA[Soleh Munawir]]>;
<![CDATA[Y.D Sumanto]]>
<![CDATA[ Jurnal Matematika Vol 2, No 1 (2013): JURNAL MATEMATIKA ]]>
Publisher : <![CDATA[MATEMATIKA FSM, UNDIP ]]>
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<![CDATA[Fungtor kovarian merupakan pemetaan dari kategori ke kategori. Akibat dari kategori yang memuat kelas dari obyek-obyek dan morfisma, fungtor kovarian akan memetakan obyek ke obyek dan morfisma ke morfisma. Di sisi lain, fungtor kovarian juga merupakan pemetaan sehingga mempunyai sifat-sifat seperti pada pemetaan yakni injektif, surjektif dan bijektif. Untuk fungtor kovarian dengan pemetaan morfisma bersifat injektif, surjektif dan bijektif secara berturut-turut disebut dengan fungtor kovarian yang faithful, full, fully faithful.]]>
