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All Journal Jurnal Sistim Informasi dan Teknologi Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat
Teddy Winanda
Politeknik Negeri Padang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Klasifikasi Kualitas Mutu Daun Gambir Ladang Rakyat Menggunakan Metode Convolutional Neural Network Teddy Winanda; Y Yuhandri; H Hendrick
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (814.536 KB) | DOI: 10.37034/jsisfotek.v3i3.51

Abstract

Indonesia is one of the countries which have the best Gambier quality in the world. Those are a few areas in Indonesia which have best gambier quality such as Aceh, Riau, North Sumatera, Bengkulu, South Sumatera and West Sumatra. Kabupaten 50 Kota is one of the regencies in west Sumatra that supplies gambier in Indonesia. The gambier leaf selection is mostly done by manual inspection or conventional method. The leaf color, thickness and structure are the important parameters in selecting gambier leaf quality. Farmers usually classify the quality of gambier leaves into good and bad. Computer Vision can help farmers to classify gambier leaves automatically. To realize this proposed method, gambier leaves are collected to create a dataset for training and testing processes. The gambier image leaves is captured by using DLSR camera at Kabupaten 50 Koto manually. 60 images were collected in this research which separated into 30 images with good and 30 images with bad quality. Furthermore, the gambier leaves image is processed by using digital image processing and coded by using python programming language. Both TensorFlow and Keras were implemented as frameworks in this research. To get a faster processing time, Ubuntu 18.04 Linux is selected as an operating system. Convolutional Neural Network (CNN) is the basis of image classification and object detection. In this research, the miniVGGNet architecture was used to perform the model creation. A quantity of dataset images was increased by applying data augmentation methods. The result of image augmentation for good quality gambier produced 3000 images. The same method was applied to poor quality images, the same results were obtained as many as 3000 images, with a total of 6000 images. The classification of gambier leaves produced by the Convolutional Neural Network method using miniVGGNet architecture obtained an accuracy rate of 0.979 or 98%. This method can be used to classify the quality of Gambier leaves very well.
Pelatihan “Food Photography” untuk Meningkatkan Laba Akuntansi pada Sistem Penjualan Online dalam Menyongsong Era New Normal Covid 19 Reno Fithri Meuthia; Eka Siskawati; Hendrick -; Teddy Winanda
Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat Vol 4 No 1 (2022)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.94 KB) | DOI: 10.30630/jppm.v4i1.704

Abstract

Era new normal membuka kesempatan baru bagi UMKM, terutama industri makanan, untuk meningkatkan penjualan mereka melalui sistem penjualan online di media sosial. Kebiasaan berbelanja online telah terbentuk dalam masyarakat sebagai dampak dari social distancing yang diterapkan selama pandemi covid-19. Promosi sangat dibutuhkan oleh bisnis dengan sistem penjualan online. Dengan semakin meningkatnya meningkat dan berkembangnya usaha makanan dan minuman yang memanfaatkan sistem penjualan online, maka kompetisi antara pemain dalam bisnis ini juga semakin meningkat. Foto atau gambar dalam dunia visual marketing memiliki kekuatan untuk menarik pembeli. Sebagian besar pebisnis produk makanan dan minuman menggunakan jasa fotografer profesional dalam menghasilkan foto yang menarik. Namun, tidak semua pebisnis memiliki modal untuk menyewa jasa profesional tersebut, terutama pebisnis yang baru saja merintis usaha mereka. Food Photography dipilih sebagai salah satu metode untuk meningkatkan laba akuntansi adalah karena; (1) skill fotografi makanan dapat menghasilkan gambar – gambar makanan yang menarik bagi pelanggan. (2) food photography dapat memperkuat brand bisnis kuliner. (3) Food photography dapat mempermudah dan mempercepat promosi bisnis kuliner, terutama bagi pebisnis yang sangat mengandalkan media sosial sebagai media promosi mereka.
Co-Authors - Hendrick Eka Siskawati Hendrick - Reno Fithri Meuthia Yuhandri Yuhandri