Open AccessPENERAPAN METODE DOUBLE EXPONENTIAL SMOOTHING UNTUK PERAMALAN TINGKAT INDEKS PEMBANGUNAN MANUSIA BERBASIS SISTEM INFORMASI GOEGRAFIS DI PROVINSI JAWA TENGAH
Author(s) -
Roni Yoga Irawan,
Wawan Laksito Yuly Saptomo,
Setiyowati Setiyowati
Publication year - 2019
Publication title -
jurnal teknologi informasi dan komunikasi sinar nusantara
Language(s) - English
Resource type - Journals
eISSN - 2620-7532
pISSN - 2338-4018
DOI - 10.30646/tikomsin.v7i2.437
Subject(s) - exponential smoothing , statistics , index (typography) , geography , computer science , mathematics , world wide web
The basic goal in quality human development is to overcome problems in society are poverty, unemployment, illiteracy, food security and democracy enforcement. But in its achievements there are several aspects of development that failed. To measure the success of a region's performance in the field of human development can be done by calculating the Human Development Index. The Human Development Index is an index that includes three indicators, which are health indicators, education level, and economic indicators. The Province of Central Java is divided into 29 districts and 6 cities, so it has a varied picture of development. Provinsi Jawa Tengah belum memiliki media informasi peramalan yang berbasis peta untuk indeks pembangunan manusia. Dari permasalahan tersebut diperlukan metode untuk meramalkan Indeks Pembangunan Manusia yang berbasis sistem informasi geografis.Data indikator penyusun Indeks Pembangunan Manusia yang mengalami kenaikan pada periode-periode tertentu, dari pola data indikator penyusun Indeks Pembangunan Manusia merupakan pola data yang memiliki unsur trend. Maka pada penelitian ini menggunakan metode double exponential smoothing.The application forecasting the Human Development Index indicator is created using the PHP programming language and the MySQL Server database. Application of Human Development Index forecasting produces forecasting calculations with the value α = 0.9 produces forecasting the following year: 69.3612 with the smallest MSE error: 0.1578 and MAPE value: 0.4894. This study produces accurate forecasting because of low error values.