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salsi kirana sya'bani
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Computer Science & IT Decision Sciences, Operations Research & Management

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Perancangan Sistem Informasi Website COPIA (Corn Utopia) Salman Al-Farisi; salsi kirana sya'bani; Ika Septia Anggraeni; Muhammad Alif Vidi; Annisa Aulia Rohim; Gema Prasasti Mindara
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2121

Abstract

Unequal and efficient distribution of crop yields is a challenge that is often faced in the corn farming industry. This can be detrimental to farmers because it results in a buildup of unsold corn crops in several areas. To overcome this challenge, a technology-based solution is needed so that it can reach customers easily by creating a website that aims to help equalize the distribution of corn harvests, with a more efficient system for managing corn supply and demand. By using an Agile approach in website development, It is hoped that it can produce a system that suits user needs in a short time. The design stage will be carried out using the Unified Modelling Language (UML) approach. In black box testing, it was proven that the use of websites to equalize agricultural products has been proven to be able to build a more efficient system for managing corn supply and demand. In addition, the services provided through the website can reduce product distribution costs and speed up the buying and selling process with customers. 
Pengaruh Efektivitas Robot AI Berbasis Images Preprocessing Terhadap Kepuasan Pengguna Dalam Mendeteksi Kematangan Buah Tomat salsi kirana sya'bani; Nur Aziezah; Hikmah Rahmah; Ridwan Siskandar; Aep Setiawan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 1 (2024): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i1.2315

Abstract

This research aims to demonstrate the influence of the effectiveness of image preprocessing-based artificial intelligence technology in detecting the ripeness level of tomatoes on user satisfaction and to discover correlations between them. The applied research method is quantitative, with data collected through the distribution of questionnaires to attendees of the IT Festival 2023 Expo held on Sunday, August 27, 2023, at the Baranangsiang Campus, IPB. The data analysis methods used include Pearson correlation test, simple linear regression, coefficient of determination test, and T-test using SPSS 25.0 software. The test results indicate that the effectiveness of image preprocessing-based artificial intelligence technology has a positive and significant impact on detecting the ripeness level of tomatoes
Co-Authors Aep Setiawan Annisa Aulia Rohim Gema Prasasti Mindara Hikmah Rahmah Ika Septia Anggraeni Muhammad Alif Vidi Nur Aziezah Ridwan Siskandar Salman Al-Farisi