Meninjau Kembali Ekonomika Neoklasik

Economic Faculties in Indonesian Universities have been teaching economics in the Neoclassical tradition as in Samuelson\u27s Economics, a combination of Classical liberalism and Marginal Utility theory. But the development experience in the last 32 years which have created extreme inequalities in the distribution of wealth and income have raised the issues of economic and social justice. ”Social economics insist that justice is a basic element of social economic organization – (which is) far more important than allocative efficiency. Inefficient societies abound and endure in the historical record but societies that lack widespread conviction as to their justness are inherently unstable. ” ….. The most fundamental difference between the social-economics perspective and that of mainstream economics is that the latter has for its principal focus the production of good and services while the former focuses on the reproduction of society. (E.K. Hunt, History of Economic Thought A Critical Perspective, 1979). An atmosphere need to be created whereby economists are prepared to take on what is best from the social science; economics is more likely to be changed by its friends than by its critics; in business as well as in theory we prefer not the metaphor of the invisible hand but rather that of the “invisible handshake” the spirit of cooperation and competition. 1

Penggunaan Sifat Pengingat Asosiatif Pada Jaringan Syaraf Tiruan Hopfield Diskret Untuk Pemulihan Data

This research concern with application of discrete Hopfield neural networks for recovering data. Using associative memories properties of discrete Hopfield neural networks we can store a set of data patterns as a memories. The basic concepts of using discrete Hopfield neural networks as associative memories is to interpret the system\u27s neurons evolution as a movement of input pattern toward the one stored pattern most resembling the input pattern. The result shows that the application could recover false data to its origin

Prediksi Data Runtun Waktu Menggunakan Jaringan Syaraf Tiruan

This research concerns about application of artificial neural networks (ANN) for predicting time series data. By modifying perceptron\u27s activation function with linear function, we got linear networks. In order to predict time series data, these linear networks combine with adaptive LMS algorithm. And then we had completed this model with time delay function to accommodate past data in time series. The data that used in the test had varied in frequency and sampling time. Results of the test had shown that the networks work properly to predict the data series

Peningkatan Efisiensi Penggunaan Bahan Bakar Kendaraan Bermotor Dengan Melakukan Pencarian Jarak Terdekat Menggunakan Jaringan Syaraf Tiruan Hopfield Di Wilayah Purwokerto

This proposed research concern with application of continuous Hopfield neural networks for shortest path routing in a given map, in this case Purwokerto city's map had choosen as an example. The method that was used in this research based on the ability of continuous Hopfield neural networks for representing their neuron as choosen vertices in the given map. The result shows that the networks can produce optimal route for such source and destination node pairs. As the product of this research, we have knowledge about the shortest way from one to another location at Purwokerto, so we can increase the efficiency on fuel use by using this rout