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All Journal Jurnal Teknologi Informasi dan Terapan (J-TIT)
Agus Hariyanto
Politeknik Negeri Jember, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Sistem Monitoring Suhu dan Pengairan Otomatis Pada Tanaman Stroberi Berbasis Website Akhmad Farizi; Bekti Maryuni Susanto; Ery Setiyawan Jullev Atmadji; Agus Hariyanto; Elly Antika
Jurnal Teknologi Informasi dan Terapan Vol 8 No 2 (2021)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v8i2.255

Abstract

Abstract— Strawberry plants need a certain amount of soil moisture to thrive. In the process of watering strawberry plants, farmers have to go to the garden every day to do watering and monitor the condition of the garden manually, the process of watering manually is like using a bucket and a pitcher, this process is a waste of energy and time, if the farmer's house is far from the garden , farmers or cultivators must make observations when the time is right for watering according to the soil conditions of the strawberry plant. This research implements a website-based automatic temperature monitoring and irrigation system where the website can be accessed via the public Internet network, not only on the local network. The results of observations on the growth of strawberry plants showed that plants that were given automatic irrigation based on the Internet of Things (IoT) grew better when compared to plants that were given manual irrigation. Keywords—strawberry; monitoring; temperature; waterring; microcontroller; Internet of Things. Abstrak— Tanaman stroberi membutuhkan kelembapan tanah tertentu agar dapat berkembang dengan baik. Pada proses penyiraman tanaman stroberi, petani harus pergi ke kebun setiap hari untuk melakukan penyiraman dan memonitoring kondisi kebun secara manual, proses penyiraman secara manual seperti menggunakan ember dan teko kocor, proses ini sangatlah membuang tenaga dan juga waktu, apabila rumah petani jauh dari kebun tersebut, petani atau pembudidaya harus melakukan pengamatan kapan waktu yang tempat untuk melakukan penyiraman sesuai dengan kondisi tanah dari tanaman stroberi. Penelitian ini mengimplementasikan sistem monitoring suhu dan pengairan otomatis berbasis website dimana website dapat diakses melalui jaringan publik Internet bukan hanya di jaringan lokal. Hasil pengamatan pertumbuhan tanaman stroberi menunjukkan bahwa tanaman yang diberikan pengairan otomatis berbasis Internet of Things (IoT) tumbuh lebih baik jika dibandingkan dengan tanaman yang diberikan pengairan secara manual. Keywords—stroberi; monitoring; suhu; pengairan; mikrokontroller; Internet of Things.
Efficient Intrusion Detection System Utilizing Ensemble Learning and Statistical Feature Selection in Agricultural IoT Networks Ahmad Fahriyannur Rosyady; Bekti Maryuni Susanto; Agus Hariyanto; Mukhamad Angga Gumilang
Jurnal Teknologi Informasi dan Terapan Vol 12 No 1 (2025): June
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v12i1.448

Abstract

To enhance agricultural processes, smart agriculture combines a variety of devices,protocols, computing paradigms, and technologies. The cloud, edge computing, big data, andartificial intelligence all offer tools and solutions for managing, storing, and analyzing the vastamounts of data produced by various parts. Smart agriculture is still in its infancy and lacks severalsecurity measures, brought in the creation of numerous networks that are vulnerable to cyberattacks.The most well-known cyberattack is called a denial of service (DoS) attack, in which the attackersoverwhelm the network with massive amounts of data or requests, preventing the nodes fromaccessing the various services that are provided in that network. Intrusion Detection Systems (IDS)have shown to be effective defense mechanisms in the event of a cyberattack. The implementationof conventional intrusion detection systems (IDS) approaches in Internet of Things (IoT) deviceswas hindered by resource constraints, such as reduced computing capacity and low powerconsumption. In this paper, we used an ensemble learning and statistical based feature selectionstrategy to create a lightweight intrusion detection solution. The results show that the stackingensemble method is able to improve the performance of single machine learning in the classificationof anomalous events even though the computation time required is quite large compared to thecomputation time of single machine learning
Co-Authors Ahmad Fahriyannur Rosyady Akhmad Farizi Bekti Maryuni Susanto Bekti Maryuni Susanto Elly Antika Ery Setiyawan Jullev Atmadji Mukhamad Angga Gumilang