The prediction of gold price aims to find out the gold price in the future on the basis of historical data on gold prices in the past, so it can be used as a consideration by gold investors to investing in gold. Prediction methods that do not require assumptions, one of which is Artificial Neural Networks. In this study, using Artificial Neural Networks, Feed Forward Neural Network with Extreme Learning Machine (ELM). ELM is a non-iterative algorithm so ELM has advantages in process speed. The input weight and bias for this method are determined randomly. After that, to find the final weight using the Moore-Penrose Generalized Inverse calculation on the hidden layer output matrix. The best model selection criteria uses the Mean Absolute Percentage Error (MAPE). This study shows that the results of the training and testing process from the model 1 input neuron and 7 hidden neurons are very good, because it produces MAPE training = 0.6752% and MAPE testing = 0.8065%. Also gives a very good prediction result because it has MAPE = 0.5499% Keywords: gold price, Extreme Learning Machine, MAPE

Public transportation is considered to be able to handle several transportation problems, such as “the ancient” traffic congestion to “the contemporary” environmental impact. Rail transit, or also known as commuter rail, is one of the most important public transportation types since it could reduce effectively the traffic congestion. At this instant, service quality of commuter rail is essential to achieve the customer satisfaction. This research aims to assess the operations of commuter rail by assessing its service quality. The importance-performance and gap analysis (IPGA) based on nine criteria was applied to accomplish the objective. A case study was conducted in KRL commuter line of Jakarta Metropolitan Area which is operated by P.T. Kereta Commuter Indonesia. The result shows that the safety criterion has the highest relative importance score and the fare has the highest relative performance score. The IPGA technique then was employed to build strategies based on the relative importance and performance from the passengers’ point of view.