IMPLEMENTASI METODE EXTREME LEARNING MACHINE (ELM) Untuk Prediksi Indeks Pembangunan Manusia Di Provinsi DKI Jakarta

Bagus Arief Aditiya, . (2020) IMPLEMENTASI METODE EXTREME LEARNING MACHINE (ELM) Untuk Prediksi Indeks Pembangunan Manusia Di Provinsi DKI Jakarta. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The Human Development Index (HDI) is a measurement of the achievement of community development in a particular region. HDI is formed based on 3 basic dimensions namely, knowledge, health and a decent standard of living. This causes the calculation of the HDI by the Central Statistics Agency (BPS) requires quite a long time plus still have to publish the results of the HDI calculation each year. HDI data from previous years can be used as parameters for predictive purposes. Making predictions for HDI can help the DKI Jakarta Provincial Government in making future development policy planning decisions. One method that can be used for HDI predictions is Extreme Learning Machine (ELM). ELM is a form of feedforward artificial neural network (ANN) which has advantages in learning speed and also a high level of accuracy. Furthermore, the best performance of the eight scenarios that have been formulated will be sought, thus in this study it is expected to be able to accurately produce HDI values in the next period. The best results obtained from 8 research scenarios made are the results of scenarioY3. The RMSE obtained is 0,025355 in the testing process.

Item Type: Thesis (Skripsi)
Additional Information: [No Panggil : 1610511026] [Pembimbing 1 : Didit Widiyanto] [Pembimbing 2 : Noor Falih] [Penguji 1 : Jayanta] [Penguji 2 : Ika Nurlaili Isnainiyah]
Uncontrolled Keywords: Human Development Index, Artifical Neural Network, ELM
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Bagus Arief Aditiya
Date Deposited: 13 Jan 2022 02:12
Last Modified: 13 Jan 2022 02:12
URI: http://repository.upnvj.ac.id/id/eprint/6607

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