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All Journal Journal of Robotics and Control (JRC) J-Icon : Jurnal Komputer dan Informatika
Husni Iskandar Pohan
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield Mochammad Haldi Widianto; Mochamad Iqbal Ardimansyah; Husni Iskandar Pohan; Davy Ronald Hermanus
Journal of Robotics and Control (JRC) Vol 3, No 3 (2022): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i3.13760

Abstract

Current technology has been widely applied for development, one of which has an Artificial Intelligence (AI) applied to Smart Farming. AI can give special capabilities to be programmed as needed. In cooperation with agricultural systems, AI is part of improving the quality of agriculture. This technology is no stranger to being applied in basic fields such as agriculture. This smart technology is needed to increase crop yields for various regions by utilizing the current trends paper. This is necessary because less land is available for agriculture, and there is a greater need for food sources. Therefore, this systematic review aims to collect the current trends in AI studies for Smart Farming papers using the latest year features from 2018-2022. This paper is handy for researchers and industry in looking for the latest papers on research to enhance crop yields. The authors utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of 534 articles from IEEE, ACM, MDPI, IAES, and ScienceDirect. After going through a careful process, 67 papers were found that were judged according to the criteria. After the authors got some of the current trends, the author has discussed several factors regarding the results obtained to enhance crop yields, such as Weather, Soil, Irrigation, Unmanned Aerial Vehicle (UAV), Pest Control, Weed Control, and Disease Control.
PENERAPAN ASSOCIATION RULE MINING PADA REKOMENDASI BUNDLING PRODUK MINIMARKET MENGGUNAKAN ORACLE DATA MINER Husni Iskandar Pohan; Boby Siswanto
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 2 (2021): Oktober 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i2.5145

Abstract

Buying and selling is a process that involves sellers and buyers or consumers where transactions occur that result in the exchange of goods for money. The seller will try to sell the goods by getting the maximum profit possible, while the buyer will get the goods at the minimum possible cost. One of the places where buying and selling transactions are potential is a minimarket. Minimarkets provide a variety of goods that buyers need, but there are times when there are goods that are not in demand by buyers, causing losses to the minimarket. There is an association rule mining technique that can find links between one item and another. The purpose of this study is to provide product bundling recommendations in the form of combining two products with one price to optimize minimarket sales. The results of this study are a list of product recommendations that are included in product bundling.
Co-Authors Boby Siswanto Davy Ronald Hermanus Mochamad Iqbal Ardimansyah Mochammad Haldi Widianto