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All Journal Jurnal Teknik ITS IPTEK Journal of Proceedings Series Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JUTI: Jurnal Ilmiah Teknologi Informasi Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi International Journal of Artificial Intelligence Research JURNAL ILMIAH GEOMATIKA Journal of Sustainable Technology and Applied Science International Journal of Organizational Behavior and Policy Sewagati
Ginardi, R.V. Hari
Institut Teknologi Sepuluh Nopember
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Internet of Things (IoT) Smartfarming untuk Pertanian Bawang Merah di Desa Kare, Kabupaten Madiun Ciptaningtyas, Henning; Ginardi, Raden Venantius Hari; Aunurohim, Aunurohim; Hariadi, Ridho Rahman; Hisyam, Achmad Aushaf Amrega; Fauzi, Haffif Rasya; Pasya, Muhammad Naufal; Syafa, Ilhan Ahmad; Wicaksono, M. Januar Eko; Salsabilla, Rehana Putri; Syahputra, Muhammad Harvian Dito; Fraditya, Awang
Sewagati Vol 9 No 2 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i2.2339

Abstract

Indonesia merupakan salah satu negara penghasil bawang merah terbesar di dunia, namun proses pemeliharaan tanaman bawang merah masih mengalami kendala, terutama dalam hal efisiensi sistem pengairan. Penerapan teknologi Internet of Things (IoT) menawarkan solusi yang dapat meningkatkan efisiensi pemeliharaan melalui sistem pemantauan dan pengendalian otomatis. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem IoT yang terintegrasi dengan aplikasi mobile untuk membantu petani di Desa Kare, Kabupaten Madiun dalam mengelola kebutuhan air tanaman bawang merah secara lebih efektif. Sistem ini menggunakan sensor BME280 yang terhubung ke ESP32 melalui jaringan Wi-Fi untuk memantau suhu dan kelembapan lingkungan, yang selanjutnya digunakan untuk mengendalikan katup solenoid guna mengatur pengairan secara otomatis sesuai kebutuhan tanaman. Aplikasi mobile dibangun menggunakan Flutter dan menyediakan fitur dashboard yang memungkinkan petani memantau data secara real-time. Pengujian sistem dilakukan melalui user acceptance testing dan device compatibility testing untuk memastikan integrasi dan kinerja sistem. Hasil penelitian menunjukkan bahwa sistem ini mampu membantu petani dalam pengelolaan irigasi yang efisien dan menjaga kualitas tanaman, sehingga dapat mendukung peningkatan produktivitas serta hasil panen. Temuan ini penting sebagai langkah awal dalam pengembangan pertanian cerdas yang lebih berkelanjutan di Indonesia.
Enhancing Electricity Consumption Prediction with Deep Learning through Advanced Data Splitting Techniques Pratiwi, Adinda Putri; Ginardi, Raden Venantius Hari; Saikhu, Ahmad
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i2.1204

Abstract

Energy consumption is increasing due to population growth and industrial activity, making electricity essential in human life. With limited natural resources, effective management of electrical resources is crucial to reduce energy usage amidst rising demand. The current trends on using deep learning as prediction can enhance the performances. To have good performance it needs correct preprocessing data, so it will produce a model with less overfitting. This research proposes a model using time-series cross-validation as the splitting data and correlation to choose the best features set for the prediction of electricity consumption. Experiments will compare time-series cross-validation and holdout methods to see the performances of splitting data and enhancing the multi-horizon data.  The experiment used 8 sets of feature lists, which are paired in combination based on correlation to ensure the best features that are related. The result is splitting data using time-series cross-validation can maintain good perfomances on mode and holdout can maintain a good evaluation performance across the horizon. Feature sets that include temporal features have excellent results, especially when combined with features that have the strongest correlation relationship with electricity consumption, leading to an enhanced R2. Among all the models tested, CNN-GRU had the best model for multistep prediction across various every horizons and feature sets.
Smart City Maturity Analysis Based on COBIT 2019 and SNI ISO 37122:2019 Ahkam, Syuaib; Ginardi, R. V. Hari
International Journal of Organizational Behavior and Policy Vol 4 No 2 (2025): JULY 2025
Publisher : Accounting Department, School of Business and Management - Universitas Kristen Petra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/ijobp.4.2.53-64

Abstract

In the current era of digital transformation, the development of Smart City is crucial for regions that want to improve public services, stimulate economic growth, and improve the quality of life of their citizens. West Sumbawa Regency, with its tourism and creative economy potential, has adopted the Smart City initiative. However, its effectiveness is hampered by suboptimal IT governance, limited digital infrastructure, and a lack of standardized integrated evaluation models. This study aims to analyze and assess the maturity of Smart City in West Sumbawa Regency by combining the COBIT 2019 framework for IT governance and SNI ISO 37122:2019 for smart city performance indicators. Using a mixed-methods approach—including a survey of 150 stakeholders for quantitative analysis and in-depth interviews with 50 key informants for qualitative analysis—as well as PLS-SEM analysis, capability maturity assessment, and GAP analysis, the results show that most IT governance processes are at maturity levels 2–3. This indicates a significant gap between existing IT governance practices and the achievement of Smart City indicators, particularly in aligning corporate objectives and risk management. The main contribution of this research is the development of an integrated evaluation model that provides a holistic evidence-based roadmap for local governments to formulate more effective Smart City policies to achieve sustainable smart city transformation.
Co-Authors Ahkam, Syuaib Ahmad Saikhu Ahmad Yusuf Ali Sofyan Kholimi Aprilio, Adrianus Yoza Arifiani, Siska Aunurohim Aunurohim Bilqis Amaliah Briantoro, Hendi Chastine Fatichah Ciptaningtyas, Henning Dewi, Ratih Kartika Eka Sari Oktarina Evy Kamilah Ratnasari Fahmi Akbar Saputra Fauzi, Haffif Rasya Fraditya, Awang Hanifah, Asiyah hidayat, dwi taufik Hisyam, Achmad Aushaf Amrega indrawanti, annisaa sri Isye Arieshanti Kusuma, Zulfa Hafizh Luqmanulhakim, Naufan Zaki Manurung, Miranda Maranatha Wijayaningtyas Mohammad Yanuar Hariyawan Mohammad, Iki Adfi Nur Muchammad Husni Mustika Mentari Nanik Suciati Noor Fitria Azzahra Parulian, Boy Pasya, Muhammad Naufal Pradigdya, Christian Andrean Pratiwi, Adinda Putri Putri, Rachmah Agus Ratih Kartika Dewi Ridho Rahman Hariadi Rizka Wakhidatus Sholikah, Rizka Wakhidatus Sabilla, Irzal Ahmad Salsabilla, Rehana Putri Santosa, Hafis Akmaldi Santoso, Dian Septiani Suastika Yulia Riska Surya, Maulidina Rahmawati Susijanto Tri Rasmana Syafa, Ilhan Ahmad Syahputra, Muhammad Harvian Dito Wicaksono, M. Januar Eko Wicaksono, Rahmad Aji Wijaya, Agas Ananta