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All Journal Jurnal Teknologi Informasi dan Multimedia Insand Comtech : Information Science and Computer Technology Journal JURNAL PENGABDIAN MASYARAKAT AKADEMISI
MUHAMMAD HAFIDH FIRMANSYAH
Politeknik Negeri Jember
Religion Humanities Computer Science & IT Electrical & Electronics Engineering Social Sciences

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Node-RED dan Robotik pada Sistem Penyiraman Otomatis berbasis IoT Wahyu Kurnia Dewanto; Aji seto Arifianto; Hariyono Rakhmad; Hermawan Arief Putranto; Muhammad Hafidh Firmansyah
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 3 (2024): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i3.609

Abstract

The Internet of Things (IoT) technology offers great potential in the agricultural sector, especially in the automation of plant irrigation systems. Many farmers face challenges with water use efficiency and real-time land condition monitoring. Manual irrigation systems often lead to water wastage. Currently, many centralized irrigation systems use a one-by-one watering approach, requiring multiple sensors to monitor each plant's condition, making them less efficient. To address this issue, this research developed an automated irrigation system controlled by Node-RED and robotic technology. The system is designed to require only one sensor to monitor the entire agricultural area, while still efficiently distributing water to many plants. Node-RED manages data from soil moisture and environmental temperature sensors, then activates the watering robot to distribute water according to the plants' needs. The system was tested by comparing manual and automatic methods using polybags. The soil moisture sensor sends data to Node-RED, which activates the watering robot when soil moisture falls below a set threshold. Test results show that the automated system can save up to 20% of water usage compared to manual methods, while keeping soil moisture within the optimal range. This system also enables real-time monitoring and control, providing a more efficient, timely, and resource-saving solution.
Implementasi Dompet Digital Polije Berbasis IoT dan Blockchain MUHAMMAD HAFIDH FIRMANSYAH; Wahyu Kurnia Dewanto; Hariyono Rakhmad
JURNAL PENGABDIAN MASYARAKAT AKADEMISI Vol. 2 No. 1 (2024): Januari : JURNAL PENGABDIAN MASYARAKAT AKADEMISI
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jpma.v2i1.504

Abstract

urrently, the implementation of IoT devices has been widely utilized by various parties in supporting the increasingly complex aspects of human life. IoT devices have become a favorite among hardware and software developers due to their ease of use and flexibility in adapting to the evolving systems of today. One of the uses of IoT is in the realm of digital economics, where digital economy represents a new way of prioritizing technology and ease in the buying and selling transaction process between sellers and buyers. In the past, payment processes for goods or services used to involve paper money and coins, but nowadays, payments are made using digital media. However, the current digital payment methods still rely on centralized storage technology. Therefore, if the data held at the center is damaged or compromised, it can disrupt the flow of financial transactions, and user data privacy becomes a subsequent concern.
Implementasi Artificial Intelligence untuk Prediksi Penyakit Jantung dengan Pendekatan Explainable AI Bima Wahyu Maulana; Agung Muliawan; Muhammad Hafidh Firmansyah; Angga Dwinanda; Difari Afreyna Fauziah
Insand Comtech : Information Science and Computer Technology Journal Vol. 11 No. 1 (2026): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v11i1.2972

Abstract

Fokus utama penelitian ini adalah rancang bangun sistem prediksi penyakit kardiovaskular dengan mengimplementasikan algoritma Random Forest. Guna mengatasi masalah "kotak hitam" pada kecerdasan buatan, studi ini mengintegrasikan pendekatan Explainable Artificial Intelligence (XAI) melalui metode SHAP (SHapley Additive exPlanations) untuk memperkuat aspek transparansi model. Analisis dilakukan menggunakan data sekunder dari Heart Disease UCI Dataset, yang mencakup variabel klinis esensial seperti usia, gender, tekanan darah, hingga kadar kolesterol. Siklus riset dimulai dari tahap pra-pemrosesan data, distribusi data latih dan uji, hingga fase konstruksi model. Evaluasi efektivitas sistem diukur menggunakan metrik akurasi, precision, recall, dan F1-score. Temuan empiris menunjukkan bahwa model mampu menghasilkan tingkat akurasi sebesar 83%, dengan kapabilitas klasifikasi yang stabil baik pada pasien positif maupun negatif penyakit jantung. Lebih lanjut, penerapan SHAP mengungkap bahwa variabel oldpeak, thalach, dan ca menjadi determinan paling krusial dalam pembentukan prediksi. Menariknya, fitur seperti kolesterol tidak selalu memberikan dampak linier langsung, melainkan bekerja melalui interaksi kompleks dengan atribut lainnya. Secara keseluruhan, integrasi XAI dalam studi ini terbukti meningkatkan interpretabilitas model machine learning. Hal ini diharapkan dapat memberikan landasan klinis yang lebih kuat bagi tenaga medis dalam proses pengambilan keputusan serta mempertebal kepercayaan terhadap sistem diagnostik berbasis AI.
Co-Authors Agung Muliawan Aji Seto Arifianto Angga Dwinanda Bima Wahyu Maulana Fauziah, Difari Afreyna Hariyono Rakhmad Hermawan Arief Putranto Wahyu Kurnia Dewanto