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Journal : Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)

Implementasi Logika Fuzzy pada Kekuatan Sinyal yang Diterima Antena Viasat X-Band Afif Nuur Hidayat; Bagus Fatkhurrozi; Ibrahim Nawawi
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 2, No 2 (2020): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v2i2.732

Abstract

The data that the antenna receives during satellite data acquisition has a signal strength that is affected by the antenna's movement at an elevation and azimuth angle. Every change in the two angles causes the signal strength received by the antenna to change. Signal strength calculation is important to be able to ensure satellite data is received well. Fuzzy Mamdani's logic as a method that can be used to calculate uncertain variables will be implemented in the calculation of the signal strength received by the Viasat X-Band antenna when the acquisition process of Aqua satellite data takes place. The results of the calculation of fuzzy mamdani logic by testing 6 signal strength data obtained from the Aqua satellite track analysis owned by LAPAN are shown in the percentage of errors, among others: DOY 197 of 1.33%; DOY 213 by 2.89%; DOY 259 of 1.93%; DOY 304 of 1.18%; DOY 320 by 4.73%; and DOY 357 of 2.27% and the average error (overall) of the entire data tested was 2.39%. This shows that the mamdani fuzzy logic is suitable for use in calculating the signal strength received by the Viasat X-Band antenna.
Optimasi Proses Gasifikasi Menggunakan Logika Fuzzy Mamdani Bagus Fatkhurrozi; Sapto Nisworo; Sumardi Sumardi
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 4, No 2 (2022): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v4i2.1261

Abstract

This study aims to test the performance of fuzzy logic in the gasification process. Gasification is the process of converting solids into flammable gases. The gas produced becomes an alternative energy source, namely the Waste Power Plant (PLTSa). The research applies Mamdani's Fuzzy logic. Fuzzy logic was created using Matlab R2018b software. The results obtained indicate that the Mean Absolute Error (MAE) output of H2 on fuzzy logic training data is 6.57. The test results for CO fuzzy output MAE value of 1.12. The test results on CO2 MAE fuzzy are 1.18. In the CH4 test, the MAE fuzzy output is 0,84.
Deteksi Penyakit Daun Durian dengan Algoritma YOLO (You Only Look Once) Mauladany, Muhammad Ibna; Fatkhurrozi, Bagus; Wibowo, Rheza Ari
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 6, No 1 (2024): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v6i1.2067

Abstract

Permasalahan yang dialami petani durian salah satunya adalah serangan penyakit terhadap daun sehingga mengganggu proses produksi buah. Penyakit yang sering menyerang daun durian adalah bercak daun dan hawar daun. Penelitian ini memiliki tujuan untuk menerapkan teknologi kecerdasan buatan yang dapat membantu mengenali, mengamati serta mendeteksi penyakit daun durian secara efektif. Algoritma deteksi objek menggunakan YOLO (You Only Look Once) merupakan bagian dari sistem kecerdasan buatan digunakan dalam penelitian ini. Objek yang dideteksi dalam penelitian ini dibagi menjadi 3 kelas yaitu bercak daun, hawar daun, dan daun sehat. Proses penyusunan sistem memanfaatkan citra daun yang memiliki kelas tersebut dengan jumlah 300 gambar dan 25 gambar sebagai citra uji. Dari hasil training dataset menggunakan Google Colab, nilai mAP tertinggi didapat pada epoch 100 yaitu sebesar 0,815. Model kemudian diuji dan mendapatkan nilai akurasi 85 %, kepresisian 96 %, dan recall 86%.