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All Journal INTI Nusa Mandiri Journal of Telecommunication, Electronics and Control Engineering (JTECE)
Muhammad Farhan Mahfuzh
Universitas Tidar
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Penentuan Karakteristik Lahan Tembakau Berdasarkan Retensi Hara Menggunakan Fuzzy Mamdani pada Kecamatan Tlogomulyo Kabupaten Temanggung Muhammad Farhan Mahfuzh; Risky Via Yuliantari
Journal of Telecommunication Electronics and Control Engineering (JTECE) Vol 5 No 2 (2023): Journal of Telecommunication, Electronics, and Control Engineering (JTECE)
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/jtece.v5i2.1056

Abstract

Fuzzy mamdani digunakan untuk menentukan karakteristik lahan tembakau berdasarkan retensi hara terdiri atas KTK Tanah, Ph H2O, dan C-Organik. Retensi hara merupakan salah satu karakteristik lahan tembakau yang dapat menghasilkan kualitas tembakau terbaik di Kecamatan Tlogomulyo Temanggung. Tidak semua di wilayah Kecamatan Tlogomulyo dapat menghasilkan tembakau kualitas terbaik atau srinthil. Srinthil merupakan jenis bentuk tembakau rajangan yang sudah mengering menyerupai rambut gimbal, menyatu dengan lainnya, serta memiliki ketajaman aroma. Berdasarkan pengujian yang telah dilakukan menyatakan bahwa fuzzy mamdani mampu menentukan wilayah yang memiliki kecocokan lahan berdasarkan retensi hara untuk menanam tembakau kualitas srinthil. Lahan tersebut berada pada Desa Losari dengan karakteristik KTK tanah tinggi, Ph H2O sebesar 5.5-6.5 dan C-Organik Tinggi sehingga dihasilkan nilai 0.94 atau sangat cocok untuk dijadikan lahan tanaman tembakau.
DETEKSI RUPIAH EMISI 2022 UNTUK DISABILITAS NETRA MENGGUNAKAN YOLOV5M DENGAN OUTPUT SUARA Muhammad Farhan Mahfuzh; Mokhammad Nurkholis Abdillah; Bagus Fatkhurrozi
INTI Nusa Mandiri Vol. 19 No. 1 (2024): INTI Periode Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i1.5295

Abstract

People with visual disabilities have difficulty recognizing rupiah denominations using blind codes due to differences in paper size for each denomination, wrinkled paper, and variations in blind codes for different emission years.. The proposed method uses the YOLOv5m algorithm as well as Google Text to Speech (GTTS) as voice output. The aim of the research is to find a model with the best precision value from YOLOv5m in detecting the 2022 emission rupiah and integrate it into GTTS to produce nominal rupiah sounds. The model was trained with the main image dataset, namely 700 images of rupiah emissions in 2022 taken at an angle of 1200. Next, the model was tested to recognize seven nominal amounts, namely IDR 1,000, IDR 2,000, IDR 5,000, IDR 10,000, IDR 20,000, IDR 50,000, and IDR 100,000. The test results show that the best YOLOv5m model is the one that has been trained using the main dataset (700 images) and supplemented with a multi-class image dataset (250 images) and background images (30 images). This model has a precision value of 82% when testing in real time. This research succeeded in applying the YOLOv5 algorithm which is integrated with Google Text to Speech to detect the image of 2022 emission rupiah banknotes.
Co-Authors Abdillah, Mokhammad Nurkholis Bagus Fatkhurrozi Risky Via Yuliantari