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All Journal Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Unram Journal of Community Service (UJCS) Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Computer Science and Information Technology Journal of Data Analytics, Information, and Computer Science (JDAICS) Jurnal Computer and Technology
Akbar, Ardiyallah
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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PERANCANGAN SMART FARMER PADA TANAMAN PADI MENGGUNAKAN ESP8266 BERBASIS INTERNET OF THINGS (IOT) Juniyardi, Lalu; Suryadi, Emi; Akbar, Ardiyallah; Samsumar, Lalu Delsi
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 4 (2024): Oktober
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jdaics.v1i4.1328

Abstract

Masalah hama burung pada tanaman padi merupakan masalah serius bagi petani, karena dapat mengakibatkan penurunan hasil panen yang signifikan. Penelitian ini bertujuan untuk sistem pengusir hama burung berbasis Internet of Things (IoT) dalam judul Smart Farmer Pada Tanaman Padi Menggunakan ESP8266 Berbasis IoT yang efektif dan efisien untuk melindungi tanaman padi. Sistem ini dirancang untuk mendeteksi kehadiran burung secara real-time dan mengusirnya menggunakan kombinasi suara dan gerakan. Metodologi penelitian meliputi tahap perancangan perangkat keras dan perangkat lunak, pengujian di lapangan, dan analisis data. Sistem ini menggunakan sensor PIR (Passive Infrared) untuk deteksi gerakan dari burung, NodeMCU ESP8266 sebagai pengendali utama, dan DFPlayer Mini yang terhubung dengan speaker untuk memutar suara pengusir burung. Sistem juga dilengkapi dengan dua motor servo yang menggerakkan objek yang menakuti burung. Semua komponen ini diintegrasikan melalui jaringan IoT untuk memungkinkan pemantauan dan pengendalian jarak jauh. Hasil pengujian di lapangan menunjukkan bahwa sistem pengusir hama burung berbasis IoT ini mampu mendeteksi kehadiran burung dengan akurasi yang tinggi dan mengusirnya secara efektif. Penggunaan kombinasi suara dan gerakan terbukti lebih efektif dibandingkan dengan metode konvensional. Sistem ini juga dapat dipantau dan dikendalikan secara real-time melalui aplikasi berbasis web, memberikan kemudahan bagi petani dalam mengelola dan mengawasi perangkat pengusir hama.
IoT Innovation and Entrepreneurship Education: Sustainable Tilapia Cultivation Optimization Strategy Samsumar, Lalu Delsi; Kembang, Lale Puspita; Akbar, Ardiyallah; Sriasih, Sriasih; Zaenudin, Zaenudin; Kalbuadi, Amiruddin
Unram Journal of Community Service Vol. 5 No. 4 (2024): December
Publisher : Pascasarjana Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ujcs.v5i4.781

Abstract

Tilapia cultivation in Teratak Village, Central Lombok, faces problems in feed efficiency and limited market access. Lack of automation technology causes feed waste, while limited marketing knowledge limits farmers' competitiveness. This community service activity aims to overcome these problems through the application of Internet of Things (IoT) technology in the form of automatic feeders (smart feeders) and entrepreneurship training focused on digital marketing. The methods applied include the manufacture and installation of smart fish feeders that are controlled via an application to regulate the amount and frequency of feed. In addition, entrepreneurship training focuses on digital marketing strategies through social media and e-commerce platforms to expand market reach. The results of the activity show that smart feeders increase feed efficiency by up to 20%, reduce waste, and support more optimal fish growth. Digital marketing training helps farmers improve their online promotion skills, expand market networks, and significantly increase sales. In conclusion, the application of IoT technology and digital marketing-based entrepreneurship training has proven effective in increasing the efficiency of cultivation and market competitiveness of tilapia farmers in Teratak Village
Implementation of Conditional WGAN-GP, ResNet50V2, and HDBSCAN for Generating and Recommending Traditional Lombok Songket Motifs Akbar, Ardiyallah; Karim, Muh Nasirudin; Imran, Bahtiar
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10894

Abstract

Songket is a traditional Indonesian woven textile with profound cultural and aesthetic value, particularly in Lombok, where artisans continue to preserve its distinctive motifs. However, the creation of new designs is still carried out manually, requiring considerable time and relying heavily on the artisans’ creativity. This study proposes an integrated system that combines Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (CWGAN-GP), ResNet50V2, and HDBSCAN to automatically generate and recommend Lombok’s traditional songket motifs. The dataset consists of primary data collected directly from local artisans and secondary data from the BatikNitik public repository, thereby providing authentic yet diverse motif samples for training. CWGAN-GP is employed to synthesize motifs with stable and realistic structures across multiple epochs. Subsequently, ResNet50V2 is utilized for deep visual feature extraction, HDBSCAN for density-based clustering, and UMAP for two-dimensional visualization of motif distribution. The system successfully groups motifs into meaningful clusters, with the largest cluster containing consistent patterns of high aesthetic value. A recommendation mechanism is also developed to suggest up to five similar motifs from the original dataset within the same cluster, ensuring cultural relevance while fostering design innovation. Despite these promising outcomes, several limitations remain, such as the relatively small number of songket motif samples, variations in motif quality, and challenges during data collection including inconsistent lighting and non-uniform patterns. These factors affect both dataset consistency and generative performance. Nevertheless, this approach demonstrates the potential of artificial intelligence to support the preservation and innovation of cultural heritage by assisting artisans in creating and exploring new motifs more efficiently without losing their traditional identity.
Co-Authors ahmad yani Amiruddin Kalbuadi Buchtami, Lalu Reza Hambali Hambali Hamim, Lutfi Hamzan Wadi Imran, Bahtiar Jaelani, Lalu Rizki Juniyardi, Lalu Karim, Muh Nasirudin Kembang, Lale Puspita Lalu Darmawan Bakti, Lalu Darmawan Lalu Delsi Samsumar, M.Eng. Rudi Muslim Sriasih, Sriasih Subki, Ahmad Supardianto Supardianto Suryadi, Emi Tony Gunawan Zaeniah Zaeniah Zaenudin Zaenudin Zaenudin Zulpan Hadi