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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengabdian Masyarakat Indonesia
Rustandi, Dede
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Humanities Computer Science & IT Education Engineering Social Sciences Other

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PENGEMBANGAN DESA WISATA MELALUI PELATIHAN DIGITAL MARKETING DALAM MENINGKATKAN UMKM DESA MADIASARI Febriansyah, Febriansyah; Ramadhanti, Manda; Novyantari, Zahrani Tri; Rustandi, Dede; Hamdan, Ahmad
Jurnal Pengabdian Masyarakat Indonesia Vol 2 No 2 (2024): JPMI Juni 2024
Publisher : CV Bayfa Cendekia Indonesia Bekerjasama dengan Jurusan/Program Studi Pendidikan Masyarakat FKIP Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jpmi.v2i2.109

Abstract

Madiasari Village is a pilot tourism village located in Cineam District, Tasikmalaya Regency where there are several potentials ranging from religious tourism, cultural tourism, to nature tourism, and even local micro, small and medium business centers such as crafts and food. There are several obstacles that cause all these sectors not to be optimized, starting from the lack of public awareness of the local potential owned and not understanding the community about marketing micro, small and medium business products in digital marketing. The purpose of the implementation of this digital marketing training is to help the community, especially micro, small and medium enterprises in marketing their products digitally in order to get a wider market and introduce local products in Madisari Village. In this Digital Marketing Training activity using the social demand approach method and integrative approach. The result of this digital marketing training is that the Madiasari Village community understands the strategies in marketing their products digitally in order to get a wider market.
Anatomy Identification of Bamboo Stems with The Convolutional Neural Networks (CNN) Method Rustandi, Dede; Sony Hartono Wijaya; Mushthofa; Ratih Damayanti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5370

Abstract

It is important to note that some species of bamboo are protected and considered endangered. However, distinguishing between traded and protected bamboo species or differentiating between bamboo species for various purposes remains a challenge. This requires specialized skills to identify the type of bamboo, and currently, the process can only be carried out in the forest for bamboo that is still in clump form by experienced researchers or officers. However, a study has been conducted to develop an easier and faster method of identifying bamboo species. The study aims to create an automatic identification system for bamboo stems based on their anatomical structure (ASINABU). The bamboo identification algorithm was developed using macroscopic images of cross-sectioned bamboo stems and the research method used was the convolutional neural network (CNN). CNN was designed to identify bamboo species with images taken using a cellphone camera equipped with a lens. The final product is an Android automatic identification application that can detect bamboo species with an accuracy of 99.9%.
Co-Authors Febriansyah Febriansyah Hamdan, Ahmad Novyantari, Zahrani Tri Ramadhanti, Manda Ratih Damayanti RR. Ella Evrita Hestiandari Sony Hartono Wijaya