Jurnal Ilmiah Matematika dan Terapan
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PELABELAN L(d,2,1) PADA OPERASI KOMPLEMEN DAN KORONA GRAF LINTASAN DAN SIKLUS
Full text linkLet be a graph with vertices and edges. An labeling of graph is a function of such that the following condition for where denoted the on distance of two vertices and and for . A number is called the span of labeling, if is the largest label vertex of labeling. Notation states that the smallest span of all labeling on a graph . An injective labeling is called and a minimum span of all labeling denoted by . A graph which has labeling is called the graph. In this paper we study of such labeling by considering complement of path and cycle. The result showed that complement of path has , for and , for and complement of the cycle has for and , for and corona of two paths has . Therefor, the complement of paths the complement of cycle , and corona of two path are graph
MEMBANGUN MODEL PENYEBARAN PENYAKIT AKIBAT ASAP KEBAKARAN HUTAN
Full text linkForest fires impact a very serious problem because it could cause health problem, especially respiratory disease such as (ISPA), Asthma and Bronchitis. The study of the health disorders is conducted by consider mathematicaly the spread of disease due to forest fires smoke. The model is constructed by devide the human population into six subpopulations, that is vulnerable S(t), exposed E(t), Asthma infected A(t), Bronchitis infected B(t) and recovered R(t).The governed model is analyted at every critical points using Routh-Hurwitz method. The results gives two critical points that describe a free disease conditions ( ) and an endemic conditions ( ). A stabil ( ) is occured if and where the threshold point of the stability is expressed as and . Endemic conditions will be asymptotically stable when and with . The condition of free disease of forest fires is occured in a long time period, while the endemic conditions is occurred in a short time period. It could be interpreted that the disease spread due to the forest fires smoke is not easy to overcome
MENGKAJI PERILAKU HARGA KOMODITI PANGAN DI KOTA PALU MENGGUNAKAN METODE BACKPROPAGATION
Full text linkArtificial neural network is an information processing paradigm that is inspired by biological neural cell systems, like the brain, that processes information. The purpose of this research is to develop neural networks to predict the price of food commodities using backpropagation method. The research was conducted by using the rate of monthly price of food commodities in Palu from January 2011 - December 2015. The data is used to predict food commodity prices forduring 2016. The backpropagation networks consists of three layers. The first layer of input is constructedin the form of monthly prices of IR 64, ciherang, membramo, cimandi, superwin, sintanur, cisantana, sticky black, sticky white, yellow corn dry, white corn, soybeans, peanuts, green beans, cassava, sweet potato, onion, garlic, red pepper large, red pepper curls, cayenne pepper, cabbage round, potatoes, tomatoes, carrots, cauliflower, beans, onion, avocado, red apples, green apples, oranges, jackfruit, mango, pineapple, papaya, banana, banana horns, rambutan, bark, olive, durian, watermelon, and mangosteen from January – December that consist of 12 variables. One hidden layer consistof five neurons and the other one is the output, that is the food commodity prices. The training process shows that on a maximum iterations on 500, constant learning rate 0,3 and 0,6 momentum, the predictions have 97.92% of level accuracy. The identification resultof food commodity prices behavior in Palu is predicted as follow: IR 64 Rp7.387, ciherang Rp8.182, membramo Rp8.150, cimandi Rp8.131, superwin Rp8.228, sintanur Rp8.660, cisantana Rp8.122, black sticky rice Rp21.383, white sticky rice Rp16.558, dry yellow corn Rp5.983, white corn Rp9.283, soybeans Rp14.600, peanuts Rp20.008, green beans Rp16.375, cassava Rp8.225, sweet potato Rp8. 542, red onion Rp28.550, garlic Rp21.208, red chili Rp27.308, curly red chili Rp23.650, cayenne Rp36.450, round cabbage Rp6.833, Rp12.067 potatoes, tomatoes Rp6.108, carrots 11.000, cauliflower Rp8.625, beans Rp10.333, scallion Rp25.242, avocado 11.000, red apple Rp29.023, green apple Rp31.067, orange Rp6.083, jackfruit Rp23.483, mango Rp11.187, pineapple Rp8.183, papaya Rp10.600, bananas Rp8.481, horn banana Rp2.683, rambutan Rp8.450, barking Rp5.625, tan Rp8.366, durian Rp19.208, watermelon Rp14.528 and mangosteen Rp18.067. It is predicted that the food commodity prices increased monthly
PELABELAN SELIMUT AJAIB SUPER PADA GRAF LINTASAN
Full text linkLet = (, ) be a simple graph. An edge covering of is a family of subgraphs 1 , … , such that each edge of () belongs to at least one of the subgraphs , 1 ≤ ≤ . If every is isomorphic to a given graph , then the graph admits an − covering. Let be a containing a covering , and the bijectif function : ( ∪ ) → {1,2,3, … , || + ||} is said an −magic labeling of if for every subgraph ′ = ( ′ , ′ ) of isomorphic to , is obtained that ∑ () + ∑ () ∈(′ ∈( ) ′ ) is constant. is said to be −super magic if () = {1, 2, 3, … , ||}. In this case, the graph which can be labeled with -magic is called the covering graph −magic. The sum of all vertex labels and all edge labels on the covering − super magic then obtained constant magic is denoted by ∑ (). The duplication graph 2 of graph 2 () is a graph obtained from two copies of graph , called and ′ , with connecting each respectively vertex in with the vertexs immediate neighboring of ′ in ′ . The purpose of this study is to obtain a covering super magic labeling for of 2 () on (2 ( )) for ≥ 4 and 3 ≤ ≤ − 1. In this paper, we have showed that duplication path graph (2 ( )) has 2 () covering super magic labeling for ≥ 4 and 3 ≤ ≤ − 1 with constant magic for all covering is ∑ (2 () () ) = ∑ (2 () (+1)
ANALISIS KESTABILAN MODEL MATEMATIKA PENYEBARAN PENYAKIT SIFILIS PADA MANUSIA
Full text linkSyphilis is a sexually transmitted infection caused by the bacterium Treponema pallidum spiroset subspecies pallidum. Transmitted through sexual contact, the infection can also be transfered from mother to fetus during pregnancy or at birth, that causes congenital syphilis. The mathematical model that represents the spread of the disease was adapted from a mathematical model SEI. The model classifiles human population into vulnerable suscepted women and men, Exposed , and Infected , sub-populations of women vulnerable , sub-populations women incubation period , sub-populations of women infected and a sub-population of men vulnerable , sub-populations incubation period male , sub-populations laki- infected men considered in the model. The derived models gives two critical point that is free disease and endemic critical point. The existence of a critical point must satisfye and . The model was analyzed by the linierized method and Routh-Hurwitz criteria to determine the system stability. The simulation shows that, in case of free-disease syphilis spread condition, the population of women and men has increased. The growth of women population is higher than the men population. it means that the spread of syphilis occurs faster in the men sub-population. In endemic condition of syphilis disease spread, the women population will growth rapidly than the men population
OPTIMALISASI KEBUTUHAN GIZI PADA MENU MAKANAN IBU HAMIL ANEMIA MENGGUNAKAN METODE BRACH AND BOUND (Studi Kasus di Kecamatan Ampana Tete Kabupaten Tojo Una-Una Provinsi Sulawesi Tengah)
Full text linkAnemia in pregnancy is a common problem because it reflects the value of socio-economic welfare of society and has had enormous influence on the quality of human resources. Settings menu maternal anemia is an effort to maintain the condition of pregnant women with anemia. This study aims to obtain optimal value nutritional needs of pregnant women anemia in Ampana Tete District of Tojo Una-Una Central Sulawesi province by using the branch and bound method. The parameters used in this study are the type of staple foods (1 ), the type of vegetable(2 ), types of fruit(3 ), types of side dishes(4 ), green beans(5 ), and milk(6 ), Results show 1st, 2 nd, and 3 rd of 36 combinations known to the most optimal combination for all trimester is a combination of 14. For the first trimester are as many as rice, 348 g spinach were 116 g,chicken eggs as 482 gmuch,and green beans 138 g, at a cost of . 15680,00, 2nd trimester is as much as rice, 381 g spinach amount to 167 g, chicken 690 g eggs, and green beans as much as 154 g and of milk 3 g at a cost of 20498,50, and the third trimester is rice, 345 g spinach, 127 g, chicken 914 g eggs, and green beans 176 g, at a cost of . 24086.00 per day. The analysis has not been as expected because one of the drawbacks is the use of linear programming linearity as sumption that sometimes does not correspond to reality
PENGATURAN PERSEDIAAN BERAS DI PERUM BULOG DIVRE SULTENG DENGAN METODE ECONOMIC ORDER QUANTITY (EOQ)
Full text linkPerum BULOG of Central Sulawesi Division is a national rice logistic company that its responsibility is to guarantee the sufficiency to meet the rice needs. Perum BULOG also responsible to keep rice price stability. One of the rice price component is the inventory costs that need to be managed. In this research the management is refered to the rice scheme demand of four storages, that are Olaya, Lawanga, Jaya Kencana Toili and Galang. This study uses EOQ (Economic Order Quantity) that consist of five priorities, that are determining the of economical order, determining the amount of safety stock, determining the maximum inventory quantities, determining the reorder point and determining total inventory cost. The results showed that the number of economical order storage of Olaya is 1.817.120,57 kg/message, Lawanga is 1.893.400,78 kg/message, Jaya Kencana Toili is 1.575.543,38 kg/messages and Galang is 1.578.742,75 kg/message. The total Inventory Security for Olaya is 32.371,28 kg, Lawanga is 41.020,07 kg, Jaya Kencana Toili is 30.630,61 kg, and Galang is 57.307,99kg. The maximum inventory for Olaya is 1.849.491,85 kg, Lawanga is 1.934.420,85 kg, Jaya Kencana Toili is 1.606.173,99 kg, and Galang is 1.636.050,74 kg. The reorder point is proposed when rice stock of Olaya reaches 323.664,52 kg, Lawanga reaches 357.282,87 kg, Jaya Kencana Toili reaches 249.620,29 kg and Galang reaches 277.188 kg. The total inventory cost that use Economic Order Quantity is Rp. 2.507.626,39 for Olaya, Rp. 2.612.893,07 for Lawanga, Rp.2.174.249 ,87 for Jaya Kencana Toili, and Rp 2.178.665,00 for Galang. The Efficiency cost of rice supplies BULOG Division is Rp.40.405,29 for Olaya, Rp. 719.256,02 for Lawanga, Rp. 51187.63 for Jaya Kencana Toili, and Rp. 153.528,73 for Galang. These result gives greatest efficiency at the cost of supplies of Perum BULOG Division Central Sulawesi for Lawanga 22% as much
OPTIMALISASI PENDISTRIBUSIAN BARANG MENGGUNAKAN METODE GOAL PROGRAMMING (STUDI KASUS: PT. WULANTIKA UTAMA)
Full text linkPT.Wulantika Utama is one of distributor in Palu who distribute products from factories to retailers. The purpose of this research are to maximize the distribution numbers of trucks and minimize the cost of distribution. Goal Programming is a method that can solve the problem with more than one purpose. Goal Programming model formulation in this study consists of 5 priority and 5 constraint functions. The fifth priority is the storage capacity, the number of trucks used for the distribution of goods to Donggala, Ampana, Poso, and cost targets are minimum distribution. Constraint function consists of inventory in the warehouse, the number of trucks and distribution costs. The results showed that the supply of goods by the warehouse capacity that can fulfiil the necessary distribution product during a month amounted to 14.755 cartons. Optimal distribution for each destination, in Donggala are 8 trucks with a capacity of 250 cartons, Poso are 20 trucks with a capacity of 300 cartons and Ampana are 14 trucks with a capacity of 500 cartons. This result can save distribution costs of Rp.90.993.009 from the previous distribution costs of Rp. 282 602.689
SISTEM PENJADWALAN PERKULIAHAN MENGGUNAKAN ALGORITMA GENETIKA (STUDI KASUS PADA JURUSAN TEKNOLOGI INFORMASI FAKULTAS TEKNIK UNIVERSITAS TADULAKO)
Full text linkSISTEM PENJADWALAN PERKULIAHAN MENGGUNAKAN ALGORITMAGENETIKA (STUDI KASUS PADA JURUSAN TEKNOLOGI INFORMASIFAKULTAS TEKNIK UNIVERSITAS TADULAKO
PREDIKSI KUALITAS AIR BERSIH PDAM KOTA PALU MENGGUNAKAN METODE BACKPROPAGATION
Full text linkPREDIKSI KUALITAS AIR BERSIH PDAM KOTA PALU MENGGUNAKANMETODE BACKPROPAGATIO