Laying the position of the access point on the Wi-Fi network in a room is needed to Keyword: WI-FI, converage Area, Signals, Simulate Annealing AbstrakPeletakan posisi access point pada jaringan WI-FI dalam suatu ruangan sangat diperlukan untuk mengoptimalkan kekuatan sinyal yang diterima dari transmitter terhadap receiver. Parameter yang menentukan performa access point adalah nilai kekuatan sinyal. Kuat atau lemahnya sebuah sinyal access point akan dipengaruhi jarak dan penghalang yang ada antara access point dan client yang mengakses access point tersebut. Pada penelitian ini telah dilakukan beberapa simulasi di beberapa ruangan yang diletakan access point terhadap receiver. Parameter yang di gunakan untuk pengukuran kekuatan sinyal menggunakan aplikasi inSSIDer yang menghasilkan nilai RSSI (Received Signal Strength Indication) dari sebuah transmitter terhadap receiver dan penghalang (hambatan) yang dapat mempengarui kekuatan sinyal tersebut. Dari penelitian ini kekuatan sinyal yang di terima oleh receiver tidak hanya di pengaruhui oleh jarak antara accespoint terhadap penerima, melainkan di pengaruhi oleh penghalang(hambatan) yang ada pada suatu ruangan. Dari hasil penelitain ini diharapkan dapat memperoleh
Indonesia is one of the developing countries that have serious problems with poverty. The still many poor people in Indonesia encourage the government to make and determine the right policies so that the problem of poverty can be overcome and not drag on. Therefore, the authors conducted this study to try to help the government conduct an analysis in predicting the level of development of the poor in Indonesia. The prediction method used is the Bayesian Regulation artificial neural network. This method is a development of the backpropagation method that is often used to predict data. The data used are data on poor people in Indonesia in 2012-2018, which are sourced from the Indonesian Central Bureau of Statistics. Based on this data a network architecture model will be formed and determined using the Bayesian Regulation method, including 10-5-10-2, 10-10-10-2, 10-10-15-2, 10-10-20-2, 10-15-10-2, 10-15-15-2, 10-15-20-2, 10-20-20-2, 10-25-25-2 and 10-30-30-2. From these 10 models after training and testing, the results show that the best architectural model is 10-25-25-2. The accuracy of the architectural models is 94.1% and 61.8% with MSE values of 0,00013571 and 0,00005189. The results of this study are the prediction of the poor for the next 5 years.
AbstrakPengangguran merupakan masalah besar yang dihadapi oleh bangsa Indonesia dari tahun ke tahun selain kemiskinan. Oleh sebab itu perlu dilakukan prediksi terhadap tingkat pengangguran terbuka di Indonesia, agar nantinya pihak pemerintah maupun swasta memiliki acuan dan referensi yang tepat untuk saling bahu membahu mengatasi masalah ini. Metode prediksi yang digunakan adalah Resilient Backpropagation yang merupakan salah satu metode Jaringan Saraf Tiruan yang sering digunakan untuk prediksi data. Data penelitian yang digunakan adalah data pengangguran terbuka menurut pendidikan tertinggi yang ditamatkan tahun 2005-2018 berdasarkan semester, yang diperoleh dari website Badan Pusat Statistik Indonesia. Berdasarkan data ini akan dibentuk dan ditentukan model arsitektur jaringan, antara lain 12-6-. Dari 8 model ini setelah dilakukan pelatihan dan pengujian diperoleh hasil bahwa model arsitektur terbaik adalah 12-18-2 (12 adalah input layer, 18 adalah jumlah neuron hiden layer dan 2 adalah output layer). Tingkat akurasi dari model arsitektur untuk semester 1 dan semester 2 ini adalah 75% dengan nilai MSE sebesar 0,00052083 and 0,00105823. AbstractUnemployment is a big problem faced by the Indonesian people from year to year besides poverty. Therefore it is necessary to predict the level of open unemployment in Indonesia so that later the government and private parties have the right references and references to work together to overcome this problem. The prediction method used is Resilient Backpropagation which is one method of Artificial Neural Networks which is often used for data prediction. The research data used is open unemployment data according to the highest education completed in 2005-2018 based on the semester obtained from the website of the Indonesian Central Bureau of Statistics. Based on this data a network architecture model will be formed and determined, including 12-6-. From these 8 models after training and testing, the results show that the best architectural model is 12-18-2 (12 is the input layer, 18 is the number of hidden neurons and 2 is the output layer). The accuracy of the architectural model for semester 1 and semester 2 is 75% with an MSE value of 0,00052083 and 0,00105823.
Selection of the best private schools in embassy cities with the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method. This decision support system is built through 6 stages. The first stage is collecting data and information through interviews and document analysis. The second stage is processing data and information to get the system design to be built. The third stage is system analysis which includes school data input, weighting criteria with the PROMETHEE method, and alternative ranking with the PROMETHEE method. The Fourth stage is designing the system using the concept of Object Oriented Design. The fifih stage is the implementation of a web-based system. The last step is evaluating the system by comparing the level of accuracy between the PROMETHEE method. With the implementation of the PROMETHEE method for the selection of the best private schools that will result in the ranking of the best private schools, it is expected that in the selection of the best schools that are truly recommended in accordance with the wishes and abilities of students
Pesticides are chemicals and organic which are used by farmers to protect rice plants from pests, farmers often experience difficulties in choosing the pesticides to be used. Where pesticide products circulate very much in the market and offer various advantages of each product, but often farmers experience incompatibility with what has been offered by each product Where pesticide products circulate very much in the market and offer various advantages of each product, but often farmers experience incompatibility with what has been offered by each product. The incompatibility of pesticides used by farmers can affect the yields of farmers. The purpose of this study is as knowledge of farmers in determining the best pesticides to eradicate pests in rice plants, especially in the village of Bah Sampuran and apply the MAUT method (Multi Attribute Utility Theory) to calculate each criterion of alternatives and produce cracking in recommending the best pesticides to eradicate pests in plants rice. The criteria used are: the workings of the pesticides, the price of pesticides, many pests, shelf life, the effect on humans, the influence on rice plants, the influence on other animals, climate resistance. This application was built using Vb net programming language and MySql database. From the results of this study it was found that Alternative Plenum had the highest value with a value of 0.79 so that it became the best Pesticide recommendation.Keywords: Decision Support System, Pesticides, FOREIGN, Vb net, MySql
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