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Panji Novantara
Universitas Kuningan
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Journal : bit-Tech

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Deteksi Hama Penyakit Daun Padi Dengan Menggunakan Teknik Optimasi Deep Learning Convolutional Neural Network Novantara, Panji; Risteruw Leonardo Firmansyah; Marrilyn Arismawati
bit-Tech Vol. 7 No. 3 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i3.2284

Abstract

Budidaya padi memegang peranan penting dalam ketahanan pangan nasional, namun sering terhambat oleh serangan penyakit daun yang berdampak signifikan terhadap penurunan produksi. Untuk menjawab tantangan tersebut, penelitian ini merancang sebuah aplikasi berbasis algoritma Convolutional Neural Network (CNN) guna mengklasifikasi penyakit daun padi secara otomatis dan akurat. Pengumpulan data dilakukan melalui observasi langsung di Gapoktan (Gabungan Kelompok Tani) Kabupaten Kuningan, wawancara dengan petani, studi literatur, serta pengembangan sistem menggunakan pendekatan Rapid Application Development (RAD) yang memungkinkan pembangunan aplikasi secara cepat dan terstruktur. Model Convolutional Neural Network (CNN) yang dibangun diuji menggunakan 480 gambar sampel dan menghasilkan akurasi tinggi sebesar 97,75%. Nilai F1-Score yang diperoleh yaitu 0,97 untuk Brown Spot, 0,921 untuk Blast, 0,871 untuk Hispa, dan 0,952 untuk daun sehat. Hasil ini menunjukkan bahwa aplikasi mampu mendeteksi penyakit secara dini, sehingga petani dapat segera mengambil tindakan preventif untuk meminimalkan kerugian hasil panen. Untuk meningkatkan performa, disarankan penerapan Model teknik optimasi yang diterapkan dalam proses model CNN (Convolutional Neural Network ) seperti perluasan dataset, variasi teknik augmentasi data set, serta evaluasi terhadap gambar dengan kompleksitas tinggi. Pengembangan ke klasifikasi penyakit lainnya juga sangat potensial. Secara keseluruhan, aplikasi ini berpeluang besar mendukung pertanian digital dan mewujudkan sistem pertanian padi yang lebih berkelanjutan dan modern.
Development of The Software as Services (SaaS) Business Model in The Satusehat Integrated Electronic Medical Record System Novantara, Panji; Trisudarmo, Ragel; Fauziah
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2354

Abstract

Digital transformation in the healthcare sector represents a key strategy to enhance operational efficiency and improve the quality of medical services. This study presents the development of a Software as a Service (SaaS)-based Electronic Medical Record (EMR) information system, integrated with SatuSehat, a national health data platform managed by the Ministry of Health of the Republic of Indonesia. The system is designed to improve the accuracy of clinical data recording and expedite access to patient information for healthcare professionals. The development process adopted the Agile methodology, characterized by iterative and incremental stages including requirements analysis, system design, implementation, testing, and evaluation. Agile was selected for its ability to accommodate dynamic user needs and regulatory requirements through continuous feedback loops and adaptive planning. Compliance with national health regulations and data security standards, including Minister of Health Regulation No. 24 of 2022 concerning EMR implementation, guided the entire process. Evaluation of the system demonstrates enhanced efficiency in medical administrative workflows, improved accuracy of patient records, and accelerated clinical decision-making processes. The integration with SatuSehat enables interoperability at a national level, thereby supporting real-time health data exchange and long-term health monitoring systems. From a societal standpoint, the system improves data accessibility for healthcare personnel and elevates the overall quality of care delivered to patients. Economically, the SaaS-based approach reduces operational costs, promotes efficient budgeting, and contributes to the broader digital transformation of healthcare services, particularly in strengthening primary care infrastructure.
Co-Authors Alman Muhammad Anggun Apriani Aria Mariany Asih Awalia Cecep Juliansyah Abbas, M.Kom. Dadan Nugraha Damasus Sandi Setiadi Danu Pradana Deni Supriadi Elpan Januar Fauziah Fitri Susanti Jajang Mutiara Marrilyn Marrilyn Arismawati Nunu Nugraha Pratama, Agum Rio Priantama Risteruw Leonardo Firman Risteruw Leonardo Firmansyah Roni Nursyamsu Roni Nursyamsu Tata Sutabri Tito Sugiharto Trisudarmo, Ragel Usep Sapari Septiana