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Production planning is the most important part of the production process in Tempe Babe. The material consideration in the production planning in this research is the optimizing of the amount of production in fulfilling the number of tempe demand, optimizing of the amount of profit Tempe obtained and the minimization of the amount of raw materials used for Tempe production. The implementation of the goal programming method can provide solutions for optimizing production planning on Tempe Babe, where the deviational variables in goal programming serve to demonstrate the possibility of negative and positive deviations from right side value of the destination function. The results of calculation analysis with goal programming, indicating the excess amount of product production will be added to the product that has the biggest advantage and the excess amount of production will be added to the product that has the number of requests Optimal profit from each product resulting in the amount of prediction of Tempe production. The results of this research provide the optimum solution for production planning on Tempe Babe every month. In addition, this study also resulted in a new mindset to find production planning models in the IoT environment as a continuation of this research.

The Integrated Population Decision Support Model in the village needs to be developed according to the rules of Law number 6 of 2014 with a decision information system model that can assist one in making accurate and targeted decisions in choosing a university. Many problems can be solved using a model, one of which is the Decision Making System, for the Determination of Human Resources in an area. There are several models that have been built including Analytical Hierarchy Process (AHP). which is the most widely used research method in solving multi-criteria problems, such as in the Determination of Human Resource Selection. This research model uses Analytical Hierarchy Process (AHP) in determining the University for a superior place of learning for human resources. In determining the University, there are several basic decision-making, including the place of the educational model, the model of expertise / skills taught, reputation, quality, teaching and learning process. The final results in this study are the priority results of university criteria, which are sorted from highest to lowest, so that prospective student users who wish to continue their higher education in choosing a regional university (rural) can easily make decisions by determining the university in the village which, and finally this model is almost 80% accurate.

Self-regulation is a process to turn and arrange thoughts, behavior and deep emotion of achieving goal, predict the outcome of student learning achievements with the criteria for assessing which cognitive and affective. This can be seen in the students who has not reached minimum criteria 100 % of the final test which received by students. Research now applied performance and looking for value k best with the nearest distance related the ability self-regulation students to learning achievements. Learning outcomes low is something that should not be left, because bad for the future students. Therefore need to followed up in improving self-regulation learning. So, did analysis by using the method k-nearest neighbor.

Data is the most important thing in a study. The quality of the results of the research will be directly proportional to the quality of the data that will be used in the research is concerned. One of the problems that exist in the data set is the absence of a value in the data for a particular attribute or better known as the missing data. One method that is often used by researchers is the k-nearst Neighbor (KNN). However, this method has several drawbacks, one of which is the selection of appropriate values of k not to degrade the performance of the classification. In the process of calculating the parameters k KNN there that can affect the accuracy of the classification results. To use more than one parameter k then used by majority voting to determine the classification results. If the parameter k in KNN classification used 1 then the result was very tight because it will use the nearest neighbor to the results of the classification. Conversely, if the value of the parameter k used KNN is great then the classification results will blur.This research will optimize the parameters k in the UN tax cluster using the algorithm expectation Maximation(EM). The results of the research in the form of clustering information by using the number of clusters k value optimization and the number of clusters without using the optimization of the value k. Then analysis the results after getting data already clustered. Results from the study showed that k obtained from the optimization algorithm can improve the results of the cluster where the 66% error can be reduced to 64%, yet very close to the best result of the measurement accuracy is tested.

Verification and identification of a person using biometrics have been widely used as the retina of the eye, the face and voice. In this experiment, such as voice biometrics to identify a person who is used to the system presence. Voice recognition is done by pattern matching between training data and test data. In this study used methods Dynamic Time Warping (DTW), K-Nearest neigbors (KNN) and Fast Frequency Transform (FFT) for voice recognition. DTW is used as a method of pattern recognition, while KNN is used for sound classification. Before testing conducted prior extraction using FFT method. This study uses 100 votes out of 10 people with the amount of each 10 people. Presentations were used as training data by 70% and 30% of test data. Results obtained by dividing the recognized voice to the overall sound. From the results 83.33 % voice recognition.

Implementation of Neuron Network model using Perceptron has not given optimal result in real time learning. The large number of inputs expressed in matrix form makes the process slower in pattern recognition. So, it takes characteristic to represent all the input matrices by using the partition method. By partitioning each input and with the best weight and using the activation function will produce an output value. And learning is valid in recognizing patterns only 1 iteration only. Further validation is done on the water mill control module with dissolved oxygen input, water pH, salinity and water temperature. With Perceptron Partition learning algorithm more real-time than perceptron model. Testing on the waterwheel input whether rotating or stopping by Matrix Laboratory software simulation.

In this research, hybridization of Learning Vector Quantization (LVQ) algorithm with Self Organizing Kohonen for face recognition using webcam. Hybrid technique performed is Kohonen algorithm used for initial weighting and the result of weighting inserted into LVQ algorithm to get result of training in the form of final weight used for face recognition. The data used in this study is the face of a digital image of the acquisition with a digital tool make use of camera that will be used for learning (learning data set) and a set of images for testing (testing data set).The first step of the process the face image (preprocessing) used for prepare the input face image to be input into network. The preprocessing step in this research is divided into four step like Image Readings, Grayscaling, Sobel operator edge detection and binaryization. The result of this test is percentage of face recognition success with LVQ algorithm is 57.03%, Kohonen is 52.59% and Hybrid is 68.88%.While the average time of the introduction process is for LVQ of 2.64 seconds, Kohonen of 2.61 seconds and Hybrid 2.59 seconds. From the above results can be concluded that in terms of accuracy Hybrid algorithm slightly superior to the Kohonen is 16.29% and in terms of time Hybrid algorithm faster than LVQ algorithm of 0.05 seconds and Kohonen an average of 0.02 seconds.

Dynamic programming is an optimization approach that divides the complex problems into the simple sequences of problems in which they are interrelated leading to decisions. In the dynamic programming, there is no standard formula that can be used to make a certain formulation. In this paper we use forward and backward method to find path which have the minimum cost and to know whether they make the same final decision. Convert the problem into several successive sequential stages starting on from stages 1,2,3 and 4 for forward dynamic programming and the step back from stage 4.3,2,1 for backward dynamic programming and interconnected with a decision rule in each stage. Find the optimal solution with cost principle at next stage. Based on the characteristics of the dynamic programming, the case is divided into several stages and the decision is has to be made (xk) at each stage. The results obtained at a stage are used for the states in the next stage so that at the forward stage 1, f1 (s) is obtained and used as a consideration of the decision in the next stage. In the backward, used firstly stage 4, f4 (s) is obtained and used as a consideration of the decision in the next stage. Cost forward and backward always increase steadily, because the cost in the next stage depends on the cost in the previous stage and formed the decision of each stage by taking the smallest fk value. Therefore the forward and backward approaches have the same result.

In conservation process it is unavoidably that conflict incidents may occur among the people and wild-life in the surrounding of the conservation area. Mitigating conflict between wildlife and people is considered a top conservation priority, particularly in landscapes where high densities of people and wildlife co-occur. This conflict is also happened in Leuser conservation area located in the border of North Sumatra and Aceh province, Indonesia. Easing the conflict problem is very difficult. This paper proposes a conceptual model based on system thinking to explore factors that may have great influence on the conflict and to figure out mitigating the conflict. We show how this conceptual framework can be utilized to analyze the conflict occur and further how it could used to develop a multi- criteria decision model.

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers' demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

In daily activities, hospitals, as one of the important health care unit, generate both medical solid waste and non-medical solid waste. The occurrence of medical solid waste could be from the results of treatment activities, such as, in the treatment room for a hospital inpatient, general clinic, a dental clinic, a mother and child clinic, laboratories and pharmacies. Most of the medical solid waste contains infectious and hazardous materials. Therefore it should be managed properly, otherwise it could be a source of new infectious for the community around the hospital as well as for health workers themselves. Efforts surveillance of various environmental factors need to be applied in accordance with the principles of sanitation focuses on environmental cleanliness. One of the efforts that need to be done in improving the quality of the environment is to undertake waste management activities, because with proper waste management is the most important in order to achieve an optimal degree of human health. Health development in Indonesian aims to achieve a future in which the Indonesian people live in a healthy environment, its people behave clean and healthy, able to reach quality health services, fair and equitable, so as to have optimal health status, health development paradigm anchored to the healthy. The healthy condition of the individual and society can be influenced by the environment. Poor environmental quality is a cause of various health problems. Efforts surveillance of various environmental factors need to be applied in accordance with the principles of sanitation focuses on environmental cleanliness. This paper proposes a model for managing the medical solid waste in hospitals in Medan city, in order to create healthy environment around hospitals.

The burden of pollution due to industrial waste, ports, community activities and marine intrusion further exacerbate environmental quality. This pollution causes drinking water sources polluted. This study aims to analyze Pb contamination in marine, and drinking water from wellbores and measure the magnitude of health risks. This is cross sectional study and quantitative research that analyzes Pb concentrations in marine and drinking water. The sample are 250 people who live in coastal area and drink water from wellbores. Water samples were examined in certified laboratories by using Atomic Absorbstion Spectrophotometer method, health risk was analyzed by the environmental health risk (EHRA) method. Pb concentrations average in marine is 52 μgl-1 . Pb concentration from 92 samples of drinking water average is 4.5 μgl-1 and range 5.4 – 26.2 μgl-1. The amount of health risk RQ

Hospital is a very important institution to provide health care for people. It is not surprising that nowadays the people's demands for hospital is increasing.. However, due to the rising cost of healthcare services, hospitals need to consider efficiencies in order to overcome these two problems. This paper deals with an integrated strategy of staff capacity management and bed allocation planning to tackle these problems. Mathematically, the strategy can be modeled as an integer linear programming problem. We solve the model using a direct neighborhood search approach, based on the notion of superbasic variables.

This paper review a model developed to minimize production costs on bottled water production planning through stochastic optimization. As we know, that planning a management means to achieve the goal that have been applied, since each management level in the organization need a planning activities. The built models is a two-stage stochastic models that aims to minimize the cost on production of bottled water by observing that during the production process, neither interfernce nor vice versa occurs. The models were develop to minimaze production cost, assuming the availability of packing raw materials used considered to meet for each kind of bottles. The minimum cost for each kind production of bottled water are expressed in the expectation of each production with a scenario probability. The probability of uncertainly is a representation of the number of productions and the timing of power supply interruption. This is to ensure that the number of interruption that occur does not exceed the limit of the contract agreement that has been made by the company with power suppliers.

Hazardous and toxic waste resulting from activities at most hospitals contain various elements of medical solid waste ranging from heavy metals that have the nature of accumulative toxic which are harmful to human health.Medical waste in the form of gas, liquid or solid generally include the category or the nature of the hazard and toxicity waste. The operational in activities of the hospital aims to improve the health and well-being, but it also produces waste as an environmental pollutant waters, soil and gas.From the description of the background of the above in mind that the management of solid waste pollution control medical hospital, is one of the fundamental problems in the city of Medan and application supervision is the main business licensing and control alternatives in accordance with applicable regulations.