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All Journal ILKOM Jurnal Ilmiah Jurnal Nasional Komputasi dan Teknologi Informasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Tecnoscienza
Ivo Colanus Rally Drajana
Universitas Pohuwato
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

 1 
SUPPORT VECTOR MACHINE BERBASIS CHI SQUARE UNTUK PREDIKSI HARGA BERAS ECER KABUPATEN POHUWATO Sunarto Taliki; Ivo Colanus Rally Drajana; Andi Bode
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 2 (2022): June 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i2.899

Abstract

One of the staple foods for most Indonesians is rice. Rice is one of the staple foods most consumed by the people of Indonesia, the need for rice is also increasing, considering the very large and scattered population of Indonesia. The ups and downs of rice prices also have an impact on farmers because of their large production. The solution to dealing with uncertain changes in the retail price of rice is to predict prices. One way to find out the estimated retail price of rice is to make predictions using the Support Vector Machine algorithm using Chi Square. The results of the experiments that have been carried out, the prediction of rice prices has been successfully carried out. The smallest error rate in the Support Vector Machine algorithm model is RMSE 733,061. Then the proposed model approaches the value of perfection, because the comparison of the experimental results of rice price predictions produces an average accuracy value of 95.82%. Thus, the proposed method is declared successful.
COMPARASI ALGORITMA FORECASTING SVM, K-NN DAN NN UNTUK PREDIKSI HARGA CABAI KOTA GORONTALO Abdul Yunus Labolo; Andi Bode; Ivo Colanus Rally Drajana; Jorry Karim
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 6, No 2 (2023): June 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i2.1112

Abstract

The high demand for chilies, especially in Gorontalo, is a driving force for chilli cultivating farmers. The price of chili which is uncertain every day can fluctuate. The Gorontalo City Food Service cannot make predictions to estimate prices in the following month. Prediction is defined as the use of statistical techniques in the form of a picture of the future based on the processing of historical figures. Due to the many algorithms that can be used in predictions, this study will compare forecasting algorithms namely Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) and Neural Network (NN). Experiments that have been carried out, on chili price prediction with forecasting algorithms have been successfully carried out. The root mean square error (RMSE) result of the SVM algorithm is 0.233, the K-NN algorithm is 0.223 and the NN algorithm is 0.206. Of the three forecasting algorithms used, the best results are produced by the Neural Network algorithm with the smallest RMSE value of 0.206. So it can be concluded that the proposed model is close to perfection, because a comparison of the results of implementing chili price predictions for the next three months produces an accuracy value of 99.25% on average
Co-Authors Abdul Yunus Labolo Andi Bode Andi Bode Betrisandi Betrisandi Farhan Karim Jorry Karim Marniyati H. Botutihe Merin Nurlaisa Abbas Muh Jabal Nur Ruhmi Sulaehani Sarlis Mooduto Serwin Sri Fransiska Pantatu Sunarto Taliki Zulfrianto Yusrin Lamasigi