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All Journal Tensor: Pure and Applied Mathematics Journal
Jefri Radjabaycolle
Science Computation
Computer Science & IT Mathematics

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Prediksi Indeks Harga Konsumen (IHK) Kota Ambon Menggunakan Elman Recurrent Neural Network (ERNN) Jefri Radjabaycolle
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss2pp65-75

Abstract

Indeks Harga Konsumen (IHK) is an economic indicator that can provide information on developments and changes in the prices of goods and services that are predominantly consumed by the public within a certain period of time. In this study the method to be used is the Elman Recurrent Neural Network (ERNN). The research data uses Ambon City IHK data from 2016 to 2019. The data used as research objects are: Food, Beverages, Cigarettes and Tobacco, Housing, Water, Electricity, Gas and Fuel, Clothing, Health, Education, Recreation, and Sport, Transportation, Communication and Financial Services as input variables. The results of training with 5 hidden layers at a maximum epoch of 100,000 obtained the smallest MAPE value of 1.1773. Then the results of testing using the parameters in the experiment on the number of hidden layer neurons 20 obtained the smallest MAPE value of 0.461823.
Analisis Pendapatan Menggunakan Metode Weighted Least Square (Wls) dengan Fungsi Pembobot Huber Jefri Radjabaycolle; Abraham Z Wattimena; Indriana Umul Mu'minin; Gabriela Haumahu
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol3iss2pp101-110

Abstract

The Weighted Least Square (WLS) method is a development of the OLS method which will provide a more accurate solution than the OLS method when outliers are identified in the data. It is possible that the model generated by the OLS method still contains outliers, while the WLS method minimizes outliers in the data. The income result determined using the OLS method is less than the income result using the WLS method, which means that if a fixed value is given (according to the standard) for each result of the factors that affect the income result in the OLS method, the average fisherman income is IDR 2,225 .220. While the average income of fishermen using the WLS method is Rp. 1,015,840. There were two outliers identified using the OLS method and after using the WLS method there were no outliers.
Co-Authors Abraham Z Wattimena Gabriela Haumahu Indriana Umul Mu'minin