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All Journal Jurnal ELTEK Indonesian Journal of Aerospace
Hanafi, Nofria
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Aerospace Engineering Astronomy Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Rancang bangun bobot kartesian tiga axis untuk penyiraman tanaman yang akurat dan efisien Tamami, Niam; Hermawan, Hendhi; Hanafi, Nofria; Madyono, Madyono; Perdana, Galang; Ramadhan, Farhan
JURNAL ELTEK Vol. 20 No. 2 (2022): Oktober 2022
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/eltek.v20i2.351

Abstract

Untuk menunjang lahan pertanian yang subur, diperlukan proses penyiraman agar kadar air dalam tanah tetap terjaga. Kegiatan penyiraman yang dilakukan secara manual membutuhkan banyak energi. Selain itu kadar air yang diberikan dengan penyiraman manual tidak dapat terukur secara akurat. Dalam makalah ini, kami mengusulkan penyiraman otomatis dengan robot kartesian tiga aksis untuk lahan dengan ukuran 3 meter x 1.5 meter dengan 171 titik tanam. Kontrol penyiraman berbasis fuzzy agar kadar air yang diberikan bisa akurat. Sebelum penyiraman, rata-rata kelembapan tanah pada lahan tersebut adalah 45.28% dengan nilai minimal 40%, nilai maksimal 50%. Target kelembapan tanah untuk setiap titik adalah 60%. Robot dapat menyiram seluruh titik tanam tanpa campur tangan manusia. Nilai kadar air rata-rata setelah penyiraman adalah 62.10%, dengan nilai minimal 60%, nilai maksimal 65%. Selain itu, juga telah dibandingkan mekanisme penyiraman dengan metode fuzzy dengan metode on-off, metode fuzzy mampu menghasilkan penyiraman yang lebih akurat dengan tingkat kesalahan rata-rata 2.10%, sedangkan metode on-off memiliki tingkat kesalahan rata-rata 5.32% terhadap target nilai kelembapan tanah. Metode fuzzy juga lebih efisien waktu dalam penyiraman yaitu 7 detik hingga 8 detik, sedangkan metode onoff membutuhkan waktu penyiraman 10 detik hingga 15 detik.   ABSTRACT To support fertile agricultural land, a watering process is needed so that the water content in the soil is maintained. Watering activities carried out manually require a lot of energy. In addition, the water content given by manual watering cannot be measured accurately. In this paper, we propose automatic watering with a three-axis Cartesian robot for land with a size of 3 meters x 1.5 meters with 171 planting points. Fuzzy based watering control so that the water content given can be accurate. Before watering, the average soil moisture on the land was 45.28% with a minimum value of 40%, a maximum value of 50%. The target soil moisture for each point is 60%. The robot can water the entire planting point without human intervention. The average water content value of watering is 62.10%, with a minimum value of 60%, a maximum value of 65%. In addition, also compared with the application error with the fuzzy method with the on-offmethod, the fuzzy method is able to produce more accurate watering with an average error rate of 2.10%, while the on-off method has an average error of 5.32% against the soil moisture target. The fuzzy method is also more time efficient in watering, which is 7 seconds to 8 seconds, while the on-off method requires a watering time of 10 seconds to 15 seconds.
Implementation of Kalman Filter for Accuracy Improvement and Angular Stability as a Control Reference Parallel Manipulator for Camera Pointing on CAN Satellite Fahrizal, Muhammad; Hanafi, Nofria
Indonesian Journal of Aerospace Vol. 23 No. 2 (2025): Indonesian Journal Of Aerospace
Publisher : BRIN Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/ijoa.2025.8981

Abstract

This study focuses on the application of the Kalman Filter to improve the accuracy and stability of angular data obtained from Inertial Measurement Unit sensors, which are often affected by noise and bias. The refined angular data serves as a control reference for the parallel manipulator used in the camera pointing system on CAN satellites. Accurate and stable reading angles are essential to ensure precise camera alignment, especially in dynamic environments with disturbances. This study integrates the Kalman Filter into the IMU data processing pipeline to filter the raw roll, pitch, and yaw. We tested the yaw stability improvement by 5.29% and filter performance improvement with 29.25% accuracy, pitch stability improved by 4.63% with 31.12% filter accuracy improvement, and roll stability improved by 1.71% with 28.99% filter accuracy improvement. These filtered angles are then used to control the parallel manipulator, allowing for precise orientation adjustment. The system performance is evaluated in terms of angular accuracy, stability, and manipulator responsibility. The results show a significant improvement in the angular quality of the data, with reduced noise and bias, leading to improved manipulator control. This implementation supports the development of high-precision camera systems for CAN satellites, which require robust and reliable orientation mechanisms. The proposed approach contributes to advancing control systems in small-scale satellite technology, where accuracy and stability are of critical importance. This study highlights the potential of the Kalman Filter in enhancing sensor accuracy for CAN satellite camera pointing systems. However, further research is needed to address dynamic environmental variations that may affect sensor performance. Future studies could explore integrating complementary filtering techniques or machine learning models to optimize data fusion and improve overall system resilience.
Co-Authors Hendhi Hermawan Madyono, Madyono Muhammad Fahrizal, Muhammad Niam Tamami Perdana, Galang Ramadhan, Farhan