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All Journal Prosiding Semnastek Jurnal Ilmiah Pangabdhi Journal of Technology and Informatics (JoTI)
Vivi Tri Widyaningrum
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Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences Other

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Menggambar Teknik dengan Teknologi 3 Dimensi Bagi Guru dan Siswa SMKN di Bangkalan Vivi Tri Widyaningrum; Yonathan Ferry Hendrawan; Sri Wahyuni
Jurnal Ilmiah Pangabdhi Vol 4, No 2: Oktober 2018
Publisher : LPPM Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1067.816 KB) | DOI: 10.21107/pangabdhi.v4i2.4928

Abstract

PENGARUH PEMBERIAN MOMENTUM PADA ARTIFICIAL NEURAL NETWORK BACKPROPAGATION Vivi Tri Widyaningrum; Ahmad Sahru Romadhon
Prosiding Semnastek PROSIDING SEMNASTEK 2014
Publisher : Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Salah  satu  algoritma Artificial  Neural  Network (ANN)  yang  biasa  digunakan  adalah  algoritmabackpropagation dengan pola model gradient descent pada proses pembelajarannya. Akan tetapi,gradient  descent memiliki  kelemahan  yaitu tidak  mudah  digunakan  dan terkadang  lambat  dalampengkonvergenan solusinya. Untuk mengatasi kelemahan tersebut dilakukan suatu modifikasi yaitudengan memberikan momentum pada perubahan bobotnya. Pada proses prediksi surface roughnesspada CNC Milling menggunakan ANN Backpropagation dengan momentum pada perubahan bobotini,  nilai  rata-rata  persentase error yang  dihasilkan  pada  masing-masing  nilai  momentum  yangdiberikan adalah tidak banyak mengalami perubahan. Namun jika nilai momentum yang diberikanmendekati  nilai  maksimal  momentum  yaitu  mendekati  nilai  satu maka akan  menyebabkanterjadinya overshoot. Pemberian momentum pada perubahan bobot menyebabkan perubahan yangcukup  besar yaitu pada  waktu  prosesnya,  semakin  besar  nilai  momentum  yang  diberikan  makasemakin  cepat  pula  waktu  proses  yang  dibutuhkan.  Hal  ini  berarti  jika  ingin  waktu  prosesprediksinya  menjadi  cepat  maka  gunakan  nilai  momentum  yang  besar,  namun  sebaiknya  kurangdari 0.9.
Brush-shaped Motion Gesture of UGV Using Hand Gesture Recognition Agus, Agus Murdiono; Muhammad Fuad; Hairil Budiarto; Faikul Umam; Vivi Tri Widyaningrum; Achmad Imam Sudianto
Journal of Technology and Informatics (JoTI) Vol. 8 No. 1 (2026): Vol. 8 N. 1 (2026)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v8i1.1315

Abstract

Manual observation of corn leaf diseases in agricultural fields often faces challenges related to time, effort, and accuracy. To address these challenges, brush-shaped motion patterns, such as zig-zag and boustrophedon trajectories, provide an effective solution by enabling uniform area coverage while reducing redundant traversal, energy consumption, and sensing gaps, making them well-suited for precision agriculture applications. Building on this approach, the system utilizes the MediaPipe framework for hand landmark tracking and the K-Nearest Neighbors (KNN) algorithm to recognize six navigation commands: forward, backward, stop, turn_right, turn_left, and capture. These commands are transmitted via Wi-Fi with an average latency of 0.001964 s. To ensure navigation accuracy during pattern execution, corrections are made using rotary encoders. Gesture classification experiments on 6,000 samples achieved a maximum accuracy of 99.46% across two participants, with stable KNN performance under both indoor and outdoor lighting variations, as well as hand distances ranging from 50 cm. Furthermore, the capture gesture produced an average image acquisition latency of 0.3037 s at various UGV observation positions. In summary, these results demonstrate that integrating real-time gesture control with UGV maneuvers enables systematic field surveys for maize leaf disease monitoring and supports Sustainable Development Goal (SDG) 2 through precision agriculture technology.
Co-Authors Achmad Imam Sudianto Agus, Agus Murdiono Ahmad Sahru Romadhon Faikul Umam Hairil Budiarto Muhammad Fuad Sri Wahyuni Yonathan Ferry Hendrawan