Penerapan Rantai Markov Dalam Peramalan Cuaca (Studi Kasus: Cuaca Harian di Kota Padang)

Information about the weather is needed. Weather is one of the considerations of the community in carrying out various activities. The purpose of this study is to provide information related to weather forecasts by applying Markov chain theory. The Markov chain is a random process in which all information about the future is contained in the present state. The study uses daily weather data that occurs on June 1, 2022 to June 30, 2022 to predict the weather for the next 7 days. The data used is secondary data taken from the website of the Meteorology, Climatology, and Geophysics Agency (BMKG) of Padang City. Based on the results of calculations using Markov chains, a transition matrix is obtained that is used to predict the weather for the next day

A PREDICATION WEATHER PARALLEL WITH FILTER MODEL BASED ON EXTRACT EVENT: CASE STUDY IS MALAYSIAN WEATHER FOR SHORT-TERM

Of all of the challenges predication weather high impact to environment based on estimate time about this sufficing using random method which mean not cover whole data coming from environment. In this care for coverage whole data below filter technique with kept the time elements and analysis with reifications. A center of attention study aim predication via filter model to contribute knows immediate future in Malaysia scope to helpful aircraft and navigation system begin analog to digital by simulate processes. In evaluate by observation will easy determinate the filter model supplementary suitable and clear meaningful likewise the random method request more processes and capacity shortest