Analysis of Water Quality Parameters on the Survival Rate of Vannamei Shrimp using the Random Forest Method
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Jan 2, 2025
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Abstract
This study developed a predictive model based on Random Forest algorithm to predict survival rate of Vannamei shrimp using five water quality parameters: dissolved oxygen (DO), temperature, pH, salinity, and Total Dissolved Solids (TDS). The model was trained on this data and evaluated using Mean Squared Error (MSE) and R² Score, with an MSE of 0.71 and R² Score of 1.00. Endpoint testing was conducted using Postman to verify the model response, with output parameters including anomaly_detected, recommendation, and survival rate. The model successfully detected anomalous conditions and provided recommendations according to the detected water quality parameters. Test results showed that DO and salinity had the greatest influence on survival rate, while pH, TDS, and temperature made moderate contributions.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Prih Diantono Abda’u, Ratih Hafsarah Maharrani, Zaenurrohman, & Adrian Putra Ramadhan. (2025). Analysis of Water Quality Parameters on the Survival Rate of Vannamei Shrimp using the Random Forest Method. Jurnal E-Komtek (Elektro-Komputer-Teknik), 8(2), 551-565. https://doi.org/10.37339/e-komtek.v8i2.2215
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[4] A. Fahrurozi, P. Informatika, T. Industri, U. Gunadarma, and J. Barat, “IMPLEMENTASI INTERNET OF THINGS ( IOT ) UNTUK SISTEM MONITORING KUALITAS AIR SHRIMP FARMING VANAME,” J. Ilm. Teknol. dan Rekayasa Vol., vol. 29, no. 1, pp. 71–85, 2024.
[5] R. Arridha, “Desain dan implementasi iot-big data analytic pada smart environment monitoring system,” 2017.
[6] R. P. Tulodo, N. T. Ujianto, E. Budiraharjo, and Y. Hapsari, “Pengembangan Sistem Pendeteksi Hujan Berbasis Internet of Things ( IoT ) dengan Simulasi Wokwi,” Engineering, vol. 14, no. 2, pp. 93–99, 2023.
[7] M. Marzuki et al., “TINGKAT KELULUSAN HIDUP POST LARVA UDANG VANAME ( Litopenaeus vannamei ) YANG DIPELIHARA PADA SALINITAS RENDAH DENGAN MENGGUNAKAN METODE AKLIMATISASI BERTINGKAT,” J. Perikan., vol. 11, no. 1, pp. 129–140, 2021.
[8] Y. Sugianti, D. A. N. Lismining, and P. Astuti, “Respon Oksigen Terlarut Terhadap Pencemaran dan Pengaruhnya Terhadap Keberadaan Sumber Daya Ikan di Sungai Citarum Dissolved Oxygen Response Againts Pollution and The Influence of Fish Resources Existence in Citarum River,” J. Teknol. Lingkung., vol. 19, no. 2, pp. 203–212, 2018.
[9] A. N. Se, P. Santoso, and F. C. Liufeto, “Pengaruh Perbedaan Suhu dan Salinitas Terhadap Pertumbuhan Post Larva Udang Vaname ( Litopenaeus vannamei ),” J. VOKASI ILMU-ILMU Perikan., vol. 3, no. April, pp. 84–89, 2023.
[10] P. E. Jelinda, Y. Jasmanidar, and A. Tjendanawangi, “Pengaruh pH Berbeda Terhadap Pertumbuhan dan Kelangsungan Hidup Udang Vanname ( Litopenaeus vannamei ),” J. VOKASI ILMU-ILMU Perikan., vol. 4, no. April, pp. 209–214, 2024.
[11] E. Gusman and D. Wiharyanto, “Studi Hubungan Parameter Kualitas Air dengan Kelimpahan Bakteri di Tambak Tradisonal Udang Windu ( Penaeus monodon ) di Pulau Tibi , Kalimantan Utara Study of Water Quality Parameters and Their Association with Bacterial Abundance in,” Samakia J. Ilmu Perikan., vol. 15, no. 2, pp. 198–206, 2024.
[12] R. S. Utami, A. Mufti, and M. Rizki, “Sistem Kendali dan Pemantau Kualitas Air Tambak Udang Berbasis Salinitas , Suhu , dan pH Air,” KITEKTRO J. Komputer, Inf. Teknol. dan Elektro, vol. 8, no. 1, pp. 43–48, 2023.
[13] R. Meenal, P. A. Michael, D. Pamela, and E. Rajasekaran, “Weather prediction using random forest machine learning model,” Indones. J. Electr. Eng. Comput. Sci., vol. 22, no. 2, pp. 1208–1215, 2021, doi: 10.11591/ijeecs.v22.i2.pp1208-1215.
[14] I. Hakim, T. Afriliansyah, and U. M. Makassar, “Implementasi Algoritma Komputasi Linear Regression untuk Optimasi Prediksi Hasil Pertanian Universitas Bumi Persada Lhokseumawe , Aceh , Indonesia Abstrak,” KESATRIA J. Penerapan Sist. Inf. (Komputer Manajemen), vol. 5, no. 3, pp. 1423–1434, 2024.