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All Journal Computatio : Journal of Computer Science and Information Systems Seminar Nasional Lahan Suboptimal CCIT (Creative Communication and Innovative Technology) Journal
Widodo Budiharto
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Agriculture, Biological Sciences & Forestry Computer Science & IT Other

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EDGE DETECTION USING CELLULAR NEURAL NETWORK AND TEMPLATE OPTIMIZATION Widodo Budiharto; Djoko Purwanto; Mauridhi Hery Purnomo
CCIT Journal Vol 4 No 1 (2010): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (562.878 KB) | DOI: 10.33050/ccit.v4i1.358

Abstract

Result of edge detection using CNN could be not optimal, because the optimal result is based on template applied to the images. During the first years after the introduction of the CNN, many templates were designed by cut and try techniques. Today, several methods are available for generating CNN templates or algorithms. In this paper, we presented a method to make the optimal result of edge detection by using TEMPO (Template Optimization). Result shown that template optimization improves the image quality of the edges and noise are reduced. Simulation for edge detection uses CANDY Simulator, then we implementing the program and optimized template using MATLAB. Comparing to Canny and Sobel operators, image shapes result from CNN edge detector also show more realistic and effective to user.
PENGEMBANGAN SISTEM KLASIFIKASI UKURAN PAKAIAN MENGGUNAKAN METODE BODY MEASUREMENT DAN FUZZY LOGIC BERBASIS SENSOR KINECT Alexander A. S. Gunawan; Erwin Erwin; Widodo Budiharto
Computatio : Journal of Computer Science and Information Systems Vol 1, No 1 (2017): Computatio : Journal of Computer Science and Information Systems
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v1i1.231

Abstract

Di dalam kehidupan sehari-hari, penentuan klasifikasi ukuran pakaian biasanya dilakukan dengan mencoba-coba pakaian terlebih dahulu sehingga membutuhkan waktu yang lebih lama. Dalam makalah ini, kita ingin membangun sistem untuk mengidentifikasi ukuran tubuh manusia dengan kamera. Selanjutnya dilakukan klasifikasi ukuran pakaian secara otomatis berdasarkan ukuran tubuh tersebut. Pendekatan yang diajukan untuk memecahkan hal ini adalah dengan metode body measurement dan Fuzzy Logic dengan menggunakan Kinect sebagai sensor. Metode body measurement digunakan untuk mengukur ukuran anggota tubuh manusia berdasarkan citra yang berasal dari sensor Kinect. Fuzzy Logic digunakan untuk menentukan klasifikasi ukuran pakaian berdasarkan hasil pengukuran yang diperoleh. Sistem pengukuran dak klasifikasi ini dapat mempermudah penentuan klasifikasi ukuran pakaian yang pas. Hasil dari penelitian ini menunjukkan bahwa sistem klasifikasi yang dibangun dapat menentukan ukuran pakaian dengan False Match Rate (FMR) sekitar 2.69%.
Inovasi Digital di Industri Smart Farming: Konsep dan Implementasi Widodo Budiharto
Seminar Nasional Lahan Suboptimal 2019: Prosiding Seminar Nasional Lahan Suboptimal “Smart Farming yang Berwawasan Lingkungan untuk Ke
Publisher : Pusat Unggulan Riset Pengembangan Lahan Suboptimal (PUR-PLSO) Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1237.107 KB)

Abstract

Budiharto W.  2019. Digital innovation in the smart farming industry: concept and implementation. In: Herlinda S et al. (Eds.), Prosiding Seminar Nasional Lahan Suboptimal 2019, Palembang 4-5 September 2019. pp. 31-37. Palembang: Unsri Press.Agriculture is one of the oldest industrial sectors ever created by humans. The FAO predicts that by 2050 the world population will be 9.6 billion. That means agricultural production must increase by 70% in that year in order to meet the needs of the population with this amount. Yet as we know that there is a classic problem of food namely the population increases but the amount of agricultural land is getting narrower. Therefore, increasing agricultural technology-based productivity is very urgent, one of which is based on the Internet of Things (IoT). IoT is the latest technology where devices around us can communicate with each other through the internet network. Wireless Sensor Network (WSN) technology was applied more broadly to IoT-based agriculture which came to be known as Smart Farming. The sensors used in agricultural land are used to determine the chemical condition of the soil, the quality of plant health and other useful information. Smart farming, which was originally called Precision Agriculture, is predicted to become a compulsory concept of agriculture in the future because of limited land. Smart farming utilizes technologies such as big data, machine learning, robotics and IoT to improve the quality and quantity of production in the agricultural industry. This paper gradually explains the concept of smart farming and its implementation in Indonesia.Keywords: concept, implementation, smart farming
Co-Authors Alexander A. S. Gunawan Djoko Purwanto Erwin Erwin Mauridhi Hery Purnomo