UF - Computer Engineering Tehcnology

Implementasi Sistem Monitoring Berbasis IoT untuk Analisis Korelasi Suhu Udara dan Kelembapan Media Tanam pada Budidaya Melon di Greenhouse

Thu, 01 Jan 2026 00:00:00 GMT

Implementasi Sistem Monitoring Berbasis IoT untuk Analisis Korelasi Suhu Udara dan Kelembapan Media Tanam pada Budidaya Melon di Greenhouse Septino, Arizal Penelitian ini mengimplementasikan sistem monitoring berbasis Internet of Things (IoT) pada greenhouse Sekolah Vokasi IPB menggunakan mikrokontroler ESP32, sensor DHT22, dan Capacitive Soil Moisture Sensor v2.0 yang dilengkapi MicroSD, Mini UPS, dan dashboard berbasis Laravel. Data dikumpulkan selama 14 hari (14-28 April 2026) dengan interval 5 menit, menghasilkan 3.794 rekaman. Setelah pembersihan dan agregasi rata-rata per jam, diperoleh 311 titik data untuk analisis. Sensor DHT22 mencapai MAPE 1,07% untuk suhu dan 8,33% untuk kelembapan udara, sedangkan sensor kelembapan media tanam mencapai MAPE 17,25% setelah kalibrasi. Mini UPS mampu mempertahankan operasional sistem selama 13 jam 42 menit. Analisis korelasi Pearson menghasilkan r = -0,1129 (Sangat Rendah, Signifikan). Analisis regresi linear sederhana menghasilkan persamaan Y = 62,1254 - 0,3165X, dengan R² = 1,27%, t-hitung = -1,9975, dan p-value = 0,0466 < a = 0,05. Rendahnya korelasi dipengaruhi oleh penyiraman manual terjadwal sebagai faktor dominan pengendali kelembapan media tanam.; This study implemented an Internet of Things (IoT)-based monitoring system in the IPB Vocational School greenhouse using an ESP32 microcontroller, a DHT22 sensor, and a Capacitive Soil Moisture Sensor v2.0, supported by MicroSD backup storage, a Mini UPS, and a Laravel-based dashboard. Data were collected over 14 days (April 14–28, 2026) at 5-minute intervals, producing 3,794 records. After data cleaning and hourly averaging, 311 data points were obtained for analysis. The DHT22 sensor achieved MAPE values of 1.07% for temperature and 8.33% for air humidity, while the growing media moisture sensor achieved a MAPE of 17.25% after calibration. The Mini UPS maintained system operation for 13 hours and 42 minutes. Pearson correlation analysis yielded r = -0.1129 (Very Low, Significant). Simple linear regression produced the equation Y = 62.1254 - 0.3165X, with R² = 1.27%, t-statistic = -1.9975, and p-value = 0.0466 < a = 0.05. The weak correlation was mainly influenced by scheduled manual irrigation, which became the dominant factor controlling growing media moisture.

Pembuatan Prototipe Sistem Monitoring Kesuburan Tanah Berbasis Internet Of Things

Thu, 01 Jan 2026 00:00:00 GMT

Pembuatan Prototipe Sistem Monitoring Kesuburan Tanah Berbasis Internet Of Things GAIO, JAMES BRANDO Perubahan iklim dan fluktuasi mikroklimat pada lahan pertanian terbuka menuntut adanya pengelolaan kualitas tanah yang presisi, khususnya pada komoditas rentan seperti tanaman tomat yang membutuhkan kelembaban dan nutrisi spesifik agar terhindar dari kecacatan fisik. Untuk mengatasi masalah tersebut, penelitian ini merancang prototipe sistem monitoring kesuburan tanah berbasis Internet of Things (IoT) menggunakan mikrokontroler ESP32 dan metodologi SDLC Waterfall. Secara teknis, sistem ini mengakuisisi metrik unsur hara (NPK) menggunakan sensor Modbus RS485, serta derajat keasaman (pH), kelembaban, suhu, dan intensitas cahaya. Seluruh data dikonversi ke format JSON dan ditransmisikan via protokol MQTT secara asinkron setiap 5 detik untuk divisualisasikan secara real-time melalui website monitoring smart farming berbasis React.js dan Node.js. Keandalan instrumen divalidasi melalui perhitungan Mean Absolute Percentage Error (MAPE) dengan rata-rata tingkat akurasi kumulatif mencapai 94,93%, mengonfirmasi presisi akuisisi data. Selanjutnya, analisis regresi linear berganda membuktikan secara empiris bahwa parameter iklim mikro dan sifat fisik tanah memiliki intervensi signifikan terhadap ketersediaan hara. Secara spesifik, Uji T menunjukkan bahwa kadar Nitrogen sangat dipengaruhi oleh Suhu Udara (nilai Sig. < 0,001), sementara ketersediaan Fosfor dan Kalium sangat dipengaruhi oleh Kelembaban Tanah dan Intensitas Cahaya (nilai Sig. < 0,001). Melalui integrasi perangkat keras dan analisis data tervalidasi ini, prototipe berhasil menyajikan data empiris untuk mencegah stres pada tanaman tomat dan memberikan justifikasi objektif guna mendukung efisiensi otomasi sistem irigasi presisi.; Climate change and microclimate fluctuations in open agricultural fields require precise soil quality management, particularly for vulnerable crops such as tomatoes, which require specific moisture levels and nutrients to avoid physical defects. To address these issues, this study designed a prototype Internet of Things (IoT)-based soil fertility monitoring system using an ESP32 microcontroller and the Waterfall SDLC methodology. Technically, the system acquires nutrient (NPK) metrics using an RS485 Modbus sensor, as well as pH, moisture, temperature, and light intensity. All data is converted to JSON format and transmitted asynchronously via the MQTT protocol every 5 seconds for real-time visualization through a smart farming monitoring website built with React.js and Node.js. Instrument reliability was validated through Mean Absolute Percentage Error (MAPE) calculations, with an average cumulative accuracy rate of 94.93%, confirming the precision of data acquisition. Furthermore, multiple linear regression analysis empirically demonstrated that microclimate parameters and soil physical properties have a significant impact on nutrient availability. Specifically, the t-test showed that nitrogen levels are strongly influenced by air temperature (Sig. value < 0.001), while phosphorus and potassium availability are strongly influenced by soil moisture and light intensity (Sig. value < 0.001). Through the integration of hardware and this validated data analysis, the prototype successfully provided empirical data to prevent stress in tomato plants and offered objective justification to support the efficiency of precision irrigation system automation.

Rancang Bangun Sistem Pemantauan Cuaca Hiperlokal Berbasis Sensor GY-BME280 untuk Prediksi Jangka Pendek

Thu, 01 Jan 2026 00:00:00 GMT

Rancang Bangun Sistem Pemantauan Cuaca Hiperlokal Berbasis Sensor GY-BME280 untuk Prediksi Jangka Pendek BAIHAKI, RAIHAN ABRAR Dinamika cuaca di Indonesia yang bersifat hiperlokal seringkali tidak tertangkap presisi oleh sistem pemantauan makro. Penelitian ini bertujuan merancang sistem pemantauan dan prediksi cuaca jangka pendek berskala hiperlokal terintegrasi sebagai peringatan dini presipitasi. Sistem dikembangkan menggunakan ESP32, sensor GY-BME280, dan GPS NEO-6M, dengan data yang divisualisasikan melalui aplikasi Flutter. Server menjalankan prediksi cuaca otomatis menggunakan algoritma empirical decision tree berdasarkan anomali parameter iklim permukaan bumi. Validasi sensor terhadap data Open-Meteo menunjukkan korelasi Pearson linier positif yang sangat kuat dengan tekanan bernilai 0,9138, suhu bernilai 0,8941, dan kelembapan bernilai 0,8476. Algoritma prediksi mencapai akurasi 93,91%, spesifisitas 95,55%, dan nilai F1 76,03%. Pengujian membuktikan sistem beroperasi optimal pada jendela pengamatan (lookback window) 60 menit, mencatat tingkat keberhasilan deteksi hujan 66,7% dengan rata-rata lead time 24,5 menit sebelum presipitasi.; Hyperlocal weather dynamics in Indonesia are often imprecisely captured by macro-level monitoring systems. This study aims to design an integrated hyperlocal weather monitoring and short-term prediction system as an early warning for precipitation. The system was developed utilizing an ESP32, a GY-BME280 sensor, and a GPS NEO-6M module, with real-time data visualization via a Flutter application. The server executes automated weather predictions using an empirical decision tree algorithm based on surface climate parameter anomalies. Sensor validation against Open-Meteo data demonstrated very strong positive linear Pearson correlations with pressure on 0.9138, temperature on 0.8941, and humidity on 0.8476. The prediction algorithm achieved 93.91% accuracy, 95.55% specificity, and a 76.03% F1 score. Testing proved the system operates optimally with a 60-minute lookback window, recording a 66.7% rain detection success rate and an average lead time of 24.5 minutes prior to precipitation.

Perancangan Sistem Pengkabutan Otomatis Berbasis Sensor SHT85 dan VEML7700 Menggunakan Logika Fuzzy pada Tanaman Tomat

Thu, 01 Jan 2026 00:00:00 GMT

Perancangan Sistem Pengkabutan Otomatis Berbasis Sensor SHT85 dan VEML7700 Menggunakan Logika Fuzzy pada Tanaman Tomat Ramadhan, Alfikri Fluctuating weather in open fields frequently triggers stress in tomato plants due to unstable temperature and humidity. An ESP32-based automated misting system was designed as a solution to execute the Mamdani fuzzy logic algorithm in real-time. The data acquisition process relies on SHT85 and VEML7700 sensors with a constant reading interval of 10 seconds. This specific interval was selected to ensure the system remains responsive in mitigating heat without compromising hardware memory stability. The control validation phase was conducted by comparing the ESP32 actuation duration against a Python simulation and mathematical calculations as the ground truth. The test results revealed a contrasting phenomenon regarding machine computational resolution. Under minimum and transitional weather conditions, the Python simulation aligned perfectly at 80 seconds, whereas the ESP32 experienced deviations to 119 and 90 seconds. The limitations of the microcontroller's 32-bit architecture triggered these deviations, as the system was forced to perform value truncation when executing defuzzification on narrow-angled fuzzy sets. The situation reversed during extreme weather conditions, where the ESP32 was highly precise, reaching exactly 510 seconds, while Python experienced a minor 3-second discretization error due to wide trapezoidal calculations. These actuation discrepancies stem purely from differences in machine computational resolution, rather than a control system failure. The actuation time differences remain well within safe agronomic tolerances. Ultimately, the implementation of this system successfully executed fuzzy logic within a temperature range of 16–29°C, 60–90% humidity, and 10,000–30,000 lux light intensity to mitigate the risk of crop failure.; Perubahan cuaca lahan terbuka sering memicu stres tanaman tomat akibat ketidakstabilan suhu dan kelembapan. Sistem pengkabutan otomatis ESP32 dirancang sebagai solusi pengeksekusi algoritma logika Fuzzy Mamdani secara real-time. Proses akuisisi data mengandalkan sensor SHT85 dan VEML7700 dengan interval pembacaan konstan 10 detik. Interval ini dipilih agar sistem responsif meredam panas tanpa mengorbankan stabilitas memori perangkat keras. Tahap validasi kendali dilakukan dengan mengkomparasi durasi aktuasi ESP32 melawan simulasi Python dan perhitungan matematis sebagai ground truth. Hasil pengujian mengungkap fenomena resolusi komputasi mesin yang kontras. Kondisi cuaca minimum dan transisi menunjukkan hasil Python sejalan sempurna di angka 80 detik, sedangkan ESP32 mengalami deviasi menjadi 119 dan 90 detik. Limitasi arsitektur 32-bit mikrokontroler memicu deviasi ini karena sistem terpaksa melakukan pembulatan nilai (truncation) saat mengeksekusi defuzzifikasi pada area himpunan bersudut sempit. Situasi berbalik saat cuaca ekstrem, dimana ESP32 sangat presisi menyentuh 510 detik, sementara Python mengalami discretization error minor 3 detik akibat kalkulasi trapesium lebar. Fluktuasi selisih ini murni perbedaan resolusi komputasi mesin, bukan kegagalan kendali. Selisih aktuasi tersebut masih berada dalam toleransi aman agronomis. Implementasi sistem ini sukses mengeksekusi logika fuzzy pada suhu 16–29°C, kelembapan 60–90%, dan intensitas cahaya 10.000–30.000 lux guna menekan risiko gagal panen.