Prediksi Hasil Produksi Tanaman Tomat di Indonesia Menurut Provinsi Menggunakan Algoritma Fletcher-Reeves
-
Surya Fajri
*
Universitas Asahan, Kisaran,
Indonesia
- Heru Gunawan Universitas Asahan, Kisaran, Indonesia
- Lokot Ridwan Batubara Universitas Asahan, Kisaran, Indonesia
- Zunaida Sitorus Universitas Asahan, Kisaran, Indonesia (*) Corresponding Author
Abstract
Tomatoes are essential for Indonesians because they have high economic and nutritional value. In addition, as population growth increases, the demand for tomatoes also increases. Based on this, it is essential to research to predict the future development of tomato crop production. The research in this paper uses a dataset of tomato plant production in Indonesia, which is spread across 34 provinces in the last seven years, namely from 2015 to 2021), which is sourced from the Indonesian Central Bureau of Statistics and the District/City Agriculture Service of each Province. The algorithm proposed in this study is the Fletcher-Reeves Conjugate Gradient Algorithm which will be processed with the help of Matlab2011b. Research analysis with three network architectural models: 5-7-1, 5-13-1, and 5-17-1. Based on a network comparison of the three architectural models, the best result is the 5-17-1 model because the MSE value is the smallest compared to the other two models, namely 0.0009915 compared to 0.0010851 and 0.0049764, as well as the highest level of accuracy, namely by 94% versus 91% and 88%. Therefore the 5-17-1 model is used to predict the yield of tomato production in Indonesia for the future (2022 and 2023). Based on the prediction results at the end of 2022 and 2023, there are 18 provinces where tomato crop production has the potential to increase, although not too significantly. The prediction of tomato production using the Fletcher-Reeves algorithm is quite good because it produces a small error rate and high accuracy.
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References
P. O. Nurak and Y. Y. Da Rato, “Prospek Pengembangan Usahatani Tomat (Solanum Lycopersicum L.) di Kebun Fakultas Pertanian Universitas Nusa Nipa Maumere,” Jurnal Ilmiah Wahana Pendidikan, vol. 8, no. 1, pp. 480–491, 2021.
Chitra Anggriani Salingkat, A. Noviyanty, and Syamsiar, “Pengaruh Jenis Bahan Pengemas, Suhu dan Lama Penyimpanan terhadap Karakteristik Mutu Buah Tomat,” Agroland: Jurnal Ilmu-ilmu Pertanian, vol. 27, no. 3, pp. 274–286, 2020.
S. A. Assagaf, “Pengaruh Pemberian Mulsa Alang-Alang dan Pupuk NPK Phonska Terhadap Pertumbuhan dan Produksi Tanaman Tomat (Solanum lycopersicum),” Jurnal Biosainstek, vol. 2, no. 1, pp. 40–46, 2020.
D. Septiadi and A. I. Mundiyah, “Karakteristik dan Analisis Finansial Usaha Tani Tomat di Kabupaten Lombok Timur,” Agroteksos, vol. 31, no. 3, pp. 180–188, 2021.
M. Situmorang, A. Wanto, and Z. M. Nasution, “Architectural Model of Backpropagation ANN for Prediction of Population-Based on Sub-Districts in Pematangsiantar City,” International Journal of Information System & Technology, vol. 3, no. 1, pp. 98–106, 2019.
J. R. Saragih, D. Hartama, and A. Wanto, “Prediksi Produksi Susu Segar Di Indonesia Menggunakan Algoritma Backpropagation,” Jurnal Ilmiah Informatika, vol. 08, no. 01, pp. 58–65, 2020.
Y. Andriani, H. Silitonga, and A. Wanto, “Analisis Jaringan Syaraf Tiruan untuk prediksi volume ekspor dan impor migas di Indonesia,” Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 4, no. 1, pp. 30–40, 2018.
S. P. Siregar, A. Wanto, and Z. M. Nasution, “Analisis Akurasi Arsitektur JST Berdasarkan Jumlah Penduduk Pada Kabupaten / Kota di Sumatera Utara,” in Seminar Nasional Sains & Teknologi Informasi (SENSASI), 2018, pp. 526–536.
A. Wanto, “Prediksi Angka Partisipasi Sekolah dengan Fungsi Pelatihan Gradient Descent With Momentum & Adaptive LR,” Jurnal Ilmu Komputer dan Informatika (ALGORITMA), vol. 3, no. 1, pp. 9–20, 2019.
N. Nasution, A. Zamsuri, L. Lisnawita, and A. Wanto, “Polak-Ribiere updates analysis with binary and linear function in determining coffee exports in Indonesia,” IOP Conference Series: Materials Science and Engineering, vol. 420, no. 012089, pp. 1–9, 2018.
A. Wanto, “Penerapan Jaringan Saraf Tiruan Dalam Memprediksi Jumlah Kemiskinan Pada Kabupaten/Kota Di Provinsi Riau,” Kumpulan JurnaL Ilmu Komputer (KLIK), vol. 05, no. 01, pp. 61–74, 2018.
A. Wanto, “Optimasi Prediksi Dengan Algoritma Backpropagation Dan Conjugate Gradient Beale-Powell Restarts,” Jurnal Teknologi dan Sistem Informasi, vol. 3, no. 3, pp. 370–380, Jan. 2017.
I. A. R. Simbolon, F. Yatussa’ada, and A. Wanto, “Penerapan Algoritma Backpropagation dalam Memprediksi Persentase Penduduk Buta Huruf di Indonesia,” Jurnal Informatika Upgris, vol. 4, no. 2, pp. 163–169, 2018.
A. Wanto, “Prediksi Produktivitas Jagung Indonesia Tahun 2019-2020 Sebagai Upaya Antisipasi Impor Menggunakan Jaringan Saraf Tiruan Backpropagation,” SINTECH (Science and Information Technology), vol. 1, no. 1, pp. 53–62, 2019.
A. Rahmat and K. Haba, “Penerapan Metode Moving Averange dalam Memprediksi Produksi Tomat,” vol. 5, no. 1, pp. 33–36, 2021.
D. Hutabarat, Solikhun, M. Fauzan, A. P. Windarto, and F. Rizki, “Penerapan Algoritma Backpropagation dalam Memprediksi Hasil Panen Tanaman Sayuran,” BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer, vol. 2, no. 1, pp. 21–29, 2021.
Nurhayati, M. B. Sibuea, D. Kusbiantoro, M. Silaban, and A. Wanto, “Implementasi Algoritma Resilient untuk Prediksi Potensi Produksi Bawang Merah di Indonesia,” Building of Informatics, Technology and Science (BITS), vol. 4, no. 2, pp. 1051–1060, 2022.
N. L. W. S. R. Ginantra, A. D. GS, S. Andini, and A. Wanto, “Pemanfaatan Algoritma Fletcher-Reeves untuk Penentuan Model Prediksi Harga Nilai Ekspor Menurut Golongan SITC,” Building of Informatics, Technology and Science (BITS), vol. 3, no. 4, pp. 679–685, 2022.
P. Parulian et al., “Analysis of Sequential Order Incremental Methods in Predicting the Number of Victims Affected by Disasters,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.
A. Wanto et al., “Forecasting the Export and Import Volume of Crude Oil, Oil Products and Gas Using ANN,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.
E. Hartato, D. Sitorus, and A. Wanto, “Analisis Jaringan Saraf Tiruan Untuk Prediksi Luas Panen Biofarmaka di Indonesia,” Jurnal semanTIK, vol. 4, no. 1, pp. 49–56, 2018.
T. Afriliansyah et al., “Implementation of Bayesian Regulation Algorithm for Estimation of Production Index Level Micro and Small Industry,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.
A. Wanto et al., “Epoch Analysis and Accuracy 3 ANN Algorithm using Consumer Price Index Data in Indonesia,” in Proceedings of the 3rd International Conference of Computer, Environment, Agriculture, Social Science, Health Science, Engineering and Technology (ICEST), 2021, no. 1, pp. 35–41.
N. L. W. S. R. Ginantra et al., “Performance One-step secant Training Method for Forecasting Cases,” Journal of Physics: Conference Series, vol. 1933, no. 1, pp. 1–8, 2021.
J. Wahyuni, Y. W. Paranthy, and A. Wanto, “Analisis Jaringan Saraf Dalam Estimasi Tingkat Pengangguran Terbuka Penduduk Sumatera Utara,” Jurnal Infomedia, vol. 3, no. 1, pp. 18–24, 2018.
I. S. Purba and A. Wanto, “Prediksi Jumlah Nilai Impor Sumatera Utara Menurut Negara Asal Menggunakan Algoritma Backpropagation,” Jurnal Teknologi Informasi Techno, vol. 17, no. 3, pp. 302–311, 2018.
I. S. Purba et al., “Accuracy Level of Backpropagation Algorithm to Predict Livestock Population of Simalungun Regency in Indonesia,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.
A. Wanto, M. Zarlis, Sawaluddin, and D. Hartama, “Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves in the Predicting Process,” Journal of Physics: Conference Series, vol. 930, no. 1, pp. 1–7, 2017.
MathWorks, “traincgf,” The MathWorks, Inc, 1994. [Online]. Available: https://www.mathworks.com/help/deeplearning/ref/traincgf.html. [Accessed: 03-Nov-2022].
BPS, “Produksi Tanaman Sayuran,” Badan Pusat Statistik Indonesia, 2022. [Online]. Available: https://www.bps.go.id/indicator/55/61/1/produksi-tanaman-sayuran.html. [Accessed: 14-Aug-2022].
R. E. Pranata, S. P. Sinaga, and A. Wanto, “Estimasi Wisatawan Mancanegara Yang Datang ke Sumatera Utara Menggunakan Jaringan Saraf,” Jurnal semanTIK, vol. 4, no. 1, pp. 97–102, 2018.
A. A. Fardhani, D. Insani, N. Simanjuntak, and A. Wanto, “Prediksi Harga Eceran Beras Di Pasar Tradisional Di 33 Kota Di Indonesia Menggunakan Algoritma Backpropagation,” Jurnal Infomedia, vol. 3, no. 1, pp. 25–30, 2018.
A. Wanto, M. Zarlis, Sawaluddin, and D. Hartama, “Analysis of Artificial Neural Network Backpropagation Using Conjugate Gradient Fletcher Reeves in the Predicting Process,” in Journal of Physics: Conference Series, 2017, vol. 930, no. 1, pp. 1–7.
M. A. P. Hutabarat, M. Julham, and A. Wanto, “Penerapan Algoritma Backpropagation Dalam Memprediksi Produksi Tanaman Padi Sawah Menurut Kabupaten/Kota di Sumatera Utara,” Jurnal semanTIK, vol. 4, no. 1, pp. 77–86, 2018.
S. Setti and A. Wanto, “Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World,” JOIN (Jurnal Online Informatika), vol. 3, no. 2, pp. 110–115, 2018.
B. Febriadi, Z. Zamzami, Y. Yunefri, and A. Wanto, “Bipolar function in backpropagation algorithm in predicting Indonesia’s coal exports by major destination countries,” IOP Conference Series: Materials Science and Engineering, vol. 420, no. 1, p. 012087, 2018.
B. K. Sihotang and A. Wanto, “Analisis Jaringan Syaraf Tiruan Dalam Memprediksi Jumlah Tamu Pada Hotel Non Bintang,” Jurnal Teknologi Informasi Techno, vol. 17, no. 4, pp. 333–346, 2018.
M. Julham, S. Sumarno, F. Anggraini, A. Wanto, and S. Solikhun, “Penerapan Jaringan Syaraf Tiruan dalam Memprediksi Tingkat Kriminal di Kabupaten Simalungun Menggunakan Algoritma Backpropagation,” BRAHMANA: Jurnal Penerapan Kecerdasan Buatan, vol. 1, no. 1, pp. 64–73, 2019.
N. Z. Purba, A. Wanto, and I. O. Kirana, “Implementation of ANN for Prediction of Unemployment Rate Based on Urban Village in 3 Sub-Districts of Pematangsiantar,” International Journal of Information System & Technology (IJISTECH), vol. 3, no. 1, pp. 107–116, 2019.
I. C. Saragih, D. Hartama, and A. Wanto, “Prediksi Perkembangan Jumlah Pelanggan Listrik Menurut Pelanggan Area Menggunakan Algoritma Backpropagation,” Building of Informatics, Technology and Science (BITS), vol. 2, no. 1, pp. 48–54, 2020.
M. Syafiq, D. Hartama, I. O. Kirana, I. Gunawan, and A. Wanto, “Prediksi Jumlah Penjualan Produk di PT Ramayana Pematangsiantar Menggunakan Metode JST Backpropagation,” JURIKOM (Jurnal Riset Komputer), vol. 7, no. 1, p. 175, 2020.
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