Implementasi Algoritma Resilient untuk Prediksi Potensi Produksi Bawang Merah di Indonesia

Abstract

Shallots are seasonal horticultural crops with high economic value. They are one of the horticultural commodities prioritized by the Director General of Horticulture and the Ministry of Agriculture in their development and handling. Therefore, it is necessary to predict the potential of shallot production in Indonesia so that the government has benchmarks and information in determining the right economic policy so that shallot production can continue to be increased or at least be unstable every year. In this study, the prediction algorithm used is the Resilient algorithm. The research data used are shallot production data obtained from the Indonesian Central Statistics Agency. This research will be analyzed using four network architecture models: 6-5-1, 6-10-1, 6-17-1 and 6-29-1. Based on the analysis of the four models used, the results show that the 6-17-1 model is the best because it has a lower Mean Square Error (MSE) value than the other three models, which is 0.0337792, and the accuracy level is quite good. Of 79% with an error rate of 0.04 used. This architectural model will be used to predict the potential for shallot production in Indonesia. Based on the overall prediction results from each province, the potential for Indonesian shallot production at the end of 2022 tends to decrease compared to 2021. The conclusion can be drawn that the application of the Resilient algorithm to the problem of red onion production data in Indonesia is quite good, but the accuracy is not too high, so a more profound study is needed

Prediksi Hasil Produksi Tanaman Tomat di Indonesia Menurut Provinsi Menggunakan Algoritma Fletcher-Reeves

“…Berdasarkan analisis diperoleh hasil bahwa model 6-17-1 merupakan model terbaik, karena memiliki nilai Mean Square Error (MSE) pengujian yang lebih rendah dibandingkan tiga model yang lain, yaitu sebesar 0,0337792 dan tingkat akurasi yang cukup baik sebesar 79% dengan tingkat error yang digunakan 0,04. Berdasarkan hasil prediksi, potensi produksi hasil bawang merah Indonesia pada Akhir tahun 2022 cenderung menurun dibandingkan tahun 2021 [17]. Selanjutnya penelitian dengan memanfaatkan algoritma Fletcher-Reeves untuk menentukan model prediksi harga nilai ekspor menurut golongan Standard International Trade Classification (SITC).…”

Implementasi Metode Back-Propagation Dalam Memprediksi Jumlah Produksi Daging Ayam Ras Pedaging Di Indonesia

“…Hal tersebut dibuktikan pada penelitian sebelumnya, telah dilakukan penelitian untuk memprediksi hasil produksi pada jagung menggunakan metode back-propagation dengan hasil tingkat akurasi mencapai 88,14% [9]. Kemudian penelitian yang dilakukan untuk memprediksi jumlah produksi telur ayam petelur berdasarkan provinsi di Indonesia dengan algoritma back-propagation dengan model arsitektur terbaik 7-32-1 dengan MSE 0,0082336 dan hasil tingkat akurasi 96,88% [10], dan masih banyak lagi penelitian-penelitian lain nya [11]- [19].…”

Effect of three fungi species application and concentration on production and pest attack on shallot (Allium ascalonicum L.)

“…There is a relatively significant price disparity between producers and consumers, so the shallot business is a source of income for farmers. Therefore, the need for shallots is essential [5].…”