In digital images processing, there are three types of edges based on intensity changes. Namely, step edges, ramp edges and edges noise. An edge is defined as a set of pixels where there is an abrupt change in colour intensity over distance. On-ramp edges where gray levels change slowly, the Gradient Method is able to detect better. On step edges where the intensity or gray levels changes very quickly the Laplace method is able to detect better than the Gradient Method. In this study, three images were used as samples and identified the type of edge of each image. Furthermore, edge detection is performed with the first derivative operator Canny and the second derivative operator Laplacian of Gaussian. The results indicate that for step edges LoG provides better results, whereas for ramp edges Canny detects better. However, by selecting the right threshold that matches the σ (standard deviation), Canny is also capable to provide good edge detection results. The greater the σ value, the threshold was chosen must be small so that the results obtained are good and easily interpreted. The Canny operator produces a thinner edge and a firmer boundary between objects and between objects on the given sigma = 1 value while the LoG operator corrects better, especially on the steep part of the value σ = 2 compared to the value σ = 1.

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This article examines set a prey-predator population model system with structural stages. Development of a mathematical model of a sustainable population of a population of living things. Structure stages are formed in predator populations, namely immature and mature. The predation function that corresponds to the characteristics in the ecosystem is the predation process of Holling I. The interaction in the population model that is carried out analysis is the equilibrium value formed from the population model. There are eight equilibrium values that arise from simple simulations. The equilibrium is E 1(0,0,0,0), E 2(0, k,0,0), E 3(k,0,0,0), E 4(k, k,0,0), E 5(0,0,0, A 1), E 6(A 2,0, A 3, A 4), E 7(0, A 5, A 6, A 7) and E 8(A 8, A 9, A 10, A 11). However, only one equilibrium value is analyzed to obtain stability. Stability is seen by requiring four eigenvalues with the Jacobian matrix. As well as the chosen value is used to find the amount of harvest carried out. The linearization of differential equations is an alternative way in this study to obtain equilibrium values. Each equilibrium value has the characteristics and terms of its stability. The Routh-Hurwitz criterion becomes a condition of its stability characteristics. Meanwhile, exploitation efforts in the population are carried out to see the changes that occur. Harvesting carried out obtained harvesting business W = 0.01313666667. For the maximum benefit obtained π = 4.997259008. This advantage is the stability and sustainability of the ecosystem.

This article develops mathematical models with structural stages from predators, immature and mature predators. The predation function of mature predators follows the Holling II response function. We assume that the immature predator population has the economic value, therefor the harvesting function is included in this model. In this model an analysis of the equilibrium point and stability of the interior equilibrium point is carried out. Analysis of the stability of the interior equilibrium points is done by linearization method and pay attention to the eigenvalues of the characteristics of the Jacobi matrix obtained. Analysis of equilibrium point stability is carried out before and after harvesting. The result is obtained by each of the three equilibrium points. At the equilibrium point of the interior with stable harvesting a local maximum profit analysis is obtained from the exploitation business. Based on the results of the analysis, it is obtained the value of harvesting business which provides a stable equilibrium point and maximum profit.

Modeling of wind speed characterstic in a particular location is often conducted, one of which is to find out the potential of wind energy in the interest of wind power plants. Of the many probability distributions, the following distributions are distributions that are quite commonly used to model the characteristic of wind speed data, namely Gamma Distribution, Weibull Distribution, Normal Distribution, Lognormal Distribution and Rayleigh Distribution. The results of the analysis and test of wind speed data in the Mopah Airport area shows that the Distribution of 3 Parameters-Gamma is the most suitable distribution to model the wind speed characteristic in the region with the shape parameters α = 26,585, scale parameters β = 0,2283 and location parameters ɣ = -0,7061. The average wind speed per month ranges from 5.2 to 5.5 knots.