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Journal : JOMLAI: Journal of Machine Learning and Artificial Intelligence

Analysis of the Fletcher-Reeves Algorithm in Determining the Best Model for Predicting School Life Expectancy in North Sumatra Jaya Tata Hardinata; Christa Voni Roulina Sinaga; Ferri Ojak Immanuel Pardede; Juli Antasari Sinaga
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1819

Abstract

Expected Length of School is the length of school (in years) that is expected to be felt by children at a certain age in the future. It is assumed that the probability that the child will remain in school at the following ages is the same as the probability of the population attending school per total population for the current age. Length of School is also a benchmark for evaluating government programs in improving Human Resources who excel in the competition of technological advances. This writing is done to implement and prove that the Fletcher-Reeves Algorithm can be used to predict Old School Expectations in North Sumatra. The research data is School Expectancy in North Sumatra which consists of 10 districts/cities, which was obtained from the Central Statistics Agency of North Sumatra from 2010 to 2020. This study uses 5 architectural models, namely 9-10-1, 9-15-1, 9-20-1, 9-25-1 and 9-30-1. From the five architectural models used, the best architectural model is 9-10-1 with an MSE of 0.0130650400. Based on this best architectural model, it will be used to predict the Expectation of Long Schools in North Sumatra for the next 5 years, from 2021 to 2025.