Evaluasi Kinerja Sensor FC-28 Untuk Monitoring Kelembapan Tanah Tanaman Indoor Menggunakan Confusion Matrix

Herva Emilda Sari

doi:10.47065/bits.v8i1.9932

Herva Emilda Sari * Universitas Ichsan Satya, Tengerang Selatan, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/bits.v8i1.9932

Keywords: FC-28 Sensor; Soil Moisture; Indoor Plant Monitoring; Confusion Matrix; Sensor Evaluation

Abstract

Technology plays an important role in transforming complex challenges into simpler and more practical processes, including soil moisture monitoring for indoor plants. Soil moisture is one of the most critical factors affecting the survival and growth of indoor plants. However, indoor plant owners often face difficulties in determining the moisture condition of the soil, creating the need for a simple and easy-to-use tool for monitoring soil moisture. The FC-28 soil moisture sensor is designed as a simple drought detection device equipped with an LED indicator to provide information regarding soil moisture conditions. The sensor operates by comparing the detected moisture level with a predefined comparator threshold. When the soil moisture falls below the threshold, the LED indicator turns on, indicating that the soil is dry. Conversely, when the moisture level remains above the threshold, the LED stays off, indicating that the soil is sufficiently moist. This study aims to evaluate the performance of the FC-28 sensor in detecting soil moisture conditions in indoor plants. An experimental approach was employed by conducting tests under dry and wet soil conditions. The sensor detection results were compared with the actual soil conditions (ground truth) using the Confusion Matrix method to obtain accuracy, sensitivity, specificity, and error rate values. The results indicate that the FC-28 sensor can consistently distinguish between dry and wet soil conditions in accordance with the actual conditions observed during the testing scenarios. This study contributes by providing a quantitative performance evaluation of the FC-28 sensor using the Confusion Matrix approach through accuracy, sensitivity, specificity, and error rate parameters for indoor soil moisture monitoring applications. The evaluation results demonstrate a high level of agreement between the sensor outputs and the actual soil conditions within the limited testing scope. These findings suggest that the FC-28 sensor can be utilized as a simple and cost-effective soil moisture monitoring tool for indoor plants under controlled environmental conditions.

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References

O. S. Tian, G. E. Giap, Rudiyanto, M. F. Ahmad, dan R. A. Aziz, “Estimating Unsaturated Hydraulic Conductivity in Unsaturated Soil Using Soil Moisture Sensors,” International Journal of Integrated Engineering, vol. 15, no. 1, hlm. 265–272, 2023, doi: https://doi.org/10.30880/ijie.2023.15.01.024.

R. J. Smythe, Arduino Measurements in Science. Berkeley, CA: Apress, 2022. doi: https://doi.org/10.1007/978-1-4842-6781-3.

P. Raeth dan P. Branch, “Lora Flood Messaging Applied To Remote Soil-Moisture Monitoring,” Journal of Engineering and Computer Engineering, vol. 7, no. 2, pp. 17–25, doi: https://doi.org/10.5897/JECE2022.0205.

G. M. Berruti, M. Leone, P. Vaiano, G. V. Persiano, M. Consales, dan A. Cusano, “All-optical active sensing platform for continuous and sustainable soil water content monitoring,” Opt. Lasers Eng., vol. 178, hlm. 108209, Jul 2024, doi: https://doi.org/10.1016/j.optlaseng.2024.108209.

S. Chowdhury, S. Sen, dan S. Janardhanan, “Comparative Analysis and Calibration of Low Cost Resistive and Capacitive Soil Moisture Sensor,” Okt 2022, [Daring]. Tersedia pada: http://arxiv.org/abs/2210.03019.

Y. Kojima, M. Matsuoka, T. Ariki, dan T. Yoshioka, “Time Domain Transmissiometry-Based Sensor for Simultaneously Measuring Soil Water Content, Electrical Conductivity, Temperature, and Matric Potential,” Sensors, vol. 23, no. 4, hlm. 2340, Feb 2023, doi: https://doi.org/10.3390/s23042340.

K. Iriyanta, B. P. D. Putranto, dan W. Andriyani, “Iot Based Soil Moisture Monitoring And Soil Moisture Prediction Using Linear Regression (Case Study Of Vinca Plants),” Journal of Intelligent Software Systems, vol. 2, no. 1, hlm. 1, Jul 2023, doi: https://doi.org/10.26798/jiss.v2i1.929.

T. M, P. Subbiah, J. M. J, dan R. Theobard, “Optimizing Agricultural Irrigation through Real-Time Data Prediction,” dalam 2024 2nd International Conference on Networking and Communications (ICNWC), IEEE, Apr 2024, hlm. 1–5. doi: https://doi.org/10.1109/ICNWC60771.2024.10537511.

A. P. Nanda, J. Jeprianto, dan M. I. Mahdi, “Sistem Otomatis Penyiraman Tanaman Berbasis Sensor Kelembapan Tanah Untuk Peningkatan Produktivitas Pertanian,” Technologia : Jurnal Ilmiah, vol. 15, no. 4, hlm. 764, Okt 2024, doi: https://doi.org/10.31602/tji.v15i4.16300.

Bavitra, Leo Anaris Sakti, Dimas Saputra, Zaki Ihwan, Baharudin, dan Muhammad Abiyyu Alharits, “Studi Komparasi Sensor Kelembapan Tanah Menggunakan ESP32,” Jural Riset Rumpun Ilmu Teknik, vol. 4, no. 1, hlm. 685–691, Jun 2025, doi: https://doi.org/10.55606/jurritek.v4i1.5292.

G. Deshpande dkk., “IoT-Based Low-Cost Soil Moisture and Soil Temperature Monitoring System.” SSRG International Journal of Electrical and Electronics Engineering, Vol. 10, no. 10, 2023, doi : https://doi.org/10.14445/23488379/IJEEE-V10I10P108.

I. D. Dinov, Data Science and Predictive Analytics. Cham: Springer International Publishing, 2023. doi: https://doi.org/10.1007/978-3-031-17483-4.

P. Vandôme dkk., “Making technological innovations accessible to agricultural water management: Design of a low-cost wireless sensor network for drip irrigation monitoring in Tunisia,” Smart Agricultural Technology, vol. 4, hlm. 100227, Agu 2023, doi: https://doi.org/10.1016/j.atech.2023.100227.

B. Sener, M. U. Gudelek, A. M. Ozbayoglu, dan H. O. Unver, “A novel chatter detection method for milling using deep convolution neural networks,” Measurement, vol. 182, hlm. 109689, Sep 2021, doi: https://doi.org/10.1016/j.measurement.2021.109689.

B. Hodges, M. L. Tagert, J. O. Paz, dan Q. Meng, “Assessing in-field soil moisture variability in the active root zone using granular matrix sensors,” Agric. Water Manag., vol. 282, hlm. 108268, Mei 2023, doi: https://doi.org/10.1016/j.agwat.2023.108268.

X. Zhang, G. Feng, dan X. Sun, “Advanced technologies of soil moisture monitoring in precision agriculture: A Review,” J. Agric. Food Res., vol. 18, hlm. 101473, Des 2024, doi: https://doi.org/10.1016/j.jafr.2024.101473.

A. J. Larner, The 2x2 Matrix. Cham: Springer International Publishing, 2024. doi: https://doi.org/10.1007/978-3-031-47194-0.

N. Effendi, W. Ramadhani, dan F. Farida, “Perancangan Sistem Penyiraman Tanaman Otomatis Menggunakan Sensor Kelembapan Tanah Berbasis IoT,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 3, no. 2, hlm. 91–98, Agu 2022, doi: https://doi.org/10.37859/coscitech.v3i2.3923.

N. Kalbuana dan B. Kurnianto, “Desain Sistem Deteksi Asap Berbasis Sensor Mikrokontroler Sebagai Upaya Pencegahan Kebakaran,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 4, no. 1, hlm. 266–272, Jan 2024, doi: https://doi.org/10.57152/malcom.v4i1.1158.

F. Nieberding, J. A. Huisman, C. Huebner, B. Schilling, A. Weuthen, dan H. R. Bogena, “Evaluation of Three Soil Moisture Profile Sensors Using Laboratory and Field Experiments,” Sensors, vol. 23, no. 14, hlm. 6581, Jul 2023, doi: https://doi.org/10.3390/s23146581.

A. Zancanaro, G. Cisotto, dan L. Badia, “Challenges of the Age of Information Paradigm for Metrology in Cyberphysical Ecosystems,” dalam 2022 IEEE International Workshop on Metrology for Living Environment (MetroLivEn), IEEE, Mei 2022, hlm. 127–131. doi: https://doi.org/10.1109/MetroLivEnv54405.2022.9826967.

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