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All Journal ILKOM Jurnal Ilmiah Jurnal Tecnoscienza
Marniyati H. Botutihe
Universitas Pohuwato
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Mathematics Other

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Neural Network Method Based on Particle Swarm Optimization for Predicting Satisfaction of Recipients of Internet Data Support from the Ministry of Education and Culture Annahl Riadi; Irvan Muzakkir; Marniyati H. Botutihe
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

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Abstract

The free quota assistance program for students and lecturers is an assistance program carried out by the ministry of education and culture, this program has been implemented since the impact of the covid-19 pandemic in all regions of Indonesia, this assistance is expected to help students and lecturers in carrying out online learning caused by the pandemic covid-19, the purpose of this study is to measure the level of visitor satisfaction through predictions of satisfaction so that it can help the government in advancing the world of education., data processing is carried out using the rapid miner application and using the neural network method with particle swarm optimization, from the results of data processing the results obtained are Values the accuracy for the neural network algorithm model is 42.44% and the accuracy value for the PSO-based neural network algorithm model is 91.86%.
PERBANDINGAN METODE FORECASTING K-NN, NN DAN SVM UNTUK PERAMALAN JUMLAH PRODUKSI COCONUT OIL Ivo Colanus Rally Drajana; Marniyati H. Botutihe
JURNAL TECNOSCIENZA Vol. 7 No. 2 (2023): TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

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Abstrak Tanaman pohon kelapa memiliki banyak bagian yang dimanfaatkan, sehingga tumbuhan ini dianggap tumbuhan serbaguna. Minyak kelapa (coconut oil) dihasilkan oleh buah pohon kelapa salah satunya adalah buah kelapa yang diolah menjadi minyak kelapa (coconut oil). Peramalan sangat diperlukan untuk meramalkan jumlah produksi minyak kelapa (coconut oil) pada sebuah perusahaan untuk mencapai target produksi. Penelitian ini memiliki tujuan untuk membandingkan metode forecasting untuk mendaptkan model terbaik. Dari hasil eksperimen menggunakan data sales order (SO) di peroleh model terbaik untuk peramlan menunjukkan bahwa model yang terbaik dihasilkan oleh algoritma Support Vector Machine (SVM) dilihat dari hasil RMSE terkecil yaitu 0,172 jika di bandingkan dengan model K-Nearest Neighbor (K-NN) dan model Neural Network (NN).
Co-Authors Annahl Riadi Irvan Muzakkir Ivo Colanus Rally Drajana