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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian
Faturrahman, Nafis
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Social Sciences Veterinary

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indonesia Pengenalan Pola Ekspresi Wajah Untuk Pengolahan Citra Menggunakan Metode Convolutional Neural Network Nurjihan, Saniyyah Wafa; Nurbadillah, Nurbadillah; Faturrahman, Nafis; Wiguna, Indra Maki; Lasardi, Ekky Mulia; Giri, Endang Purnama; Mindara, Gema Parasti
JATISI Vol 11 No 4 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i4.9585

Abstract

This research focuses on the development of a facial expression recognition system based on image processing that is capable of identifying emotions with high accuracy. Facial recognition is a widely used technology for authentication and security, but it has potential applications in understanding emotional expressions. By utilizing Convolutional Neural Networks (CNN), the system is designed to detect and classify expressions such as happiness, sadness, anger, and neutrality in real time. The research stages include data collection of faces with various expressions, preprocessing, and training of the CNN model. Performance evaluation demonstrates that CNN outperforms traditional methods such as Viola-Jones and Support Vector Machine (SVM) under various lighting and angle conditions, achieving an average accuracy of 92%. These results prove the model's reliability in detecting emotional expressions with high precision. Further development is proposed to enhance performance, such as expanding the dataset variety and employing more advanced image processing techniques. Consequently, this system has the potential to make a positive impact on human-computer interaction.
Analisis Decision Table Testing untuk Pengujian Blackbox Website Pusat Studi Bencana IPB Nasir, Muhammad; Nurjihan, Saniyyah Wafa; Nurbadillah, Nurbadillah; Faturrahman, Nafis; Wiguna, Indra Maki; Lasardi, Ekky Mulia; Wicaksono, Aditya
JATISI Vol 11 No 4 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i4.9618

Abstract

 This research examines black box testing using the Decision Table Testing technique on the Disaster Study Center website at IPB. This technique was chosen for its ability to identify logical errors and relevant testing scenarios, thereby optimizing test coverage in software development. The research method involves analyzing the website's features to identify potential conditions and actions that serve as the foundation for constructing the decision table. Each condition and action is systematically tested to detect any discrepancies or errors that may arise during website use. The testing results reveal several scenarios that the system has not adequately accommodated, particularly in user input handling and data validation. This finding indicates that the application of Decision Table Testing can improve test quality, especially for features with complex logic. In conclusion, this study highlights the importance of decision table-based testing in enhancing the reliability and accuracy of website functions, making a significant contribution to reducing potential errors that may impact user experience.
ROOTINE: PROTOTIPE ASISTEN RAWAT TANAMAN DENGAN API VISUALCROSSING Rasendriya, Achmad Syahmi; Faturrahman, Nafis; Mahardhika, Bima Julian; Rabika, Jonathan Cristiano; Minhalina, Sharfina Andzani
Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian Vol. 15 No. 1 (2025): Jurnal Sains Terapan: Wahana Informasi dan Alih Teknologi Pertanian
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jstsv.15.1.44-55

Abstract

Berkebun diyakini sebagai salah satu alternatif manajemen stres karena menggabungkan aktivitas fisik dengan kesenangan dalam merawat tanaman. Namun, bagi pemula, kurangnya pengetahuan dapat menjadi hambatan dan menimbulkan berbagai masalah dalam proses berkebun. Oleh karena itu, dirancang sebuah prototipe asisten rawat tanaman berbasis aplikasi mobile untuk membantu para pemula memulai kegiatan berkebun. Prototipe ini dikembangkan menggunakan metode Evolutionary Prototype serta memanfaatkan API Visual Crossing dan OpenAI sebagai pendukung utama fitur-fitur yang tersedia. Aplikasi ini bertujuan untuk memberikan panduan dan rekomendasi berbasis cuaca serta bantuan interaktif agar proses berkebun menjadi lebih mudah dan menyenangkan bagi pemula.
Co-Authors Aditya Wicaksono Endang Purnama Giri Lasardi, Ekky Mulia Mahardhika, Bima Julian Mindara, Gema Parasti Minhalina, Sharfina Andzani Muhammad Nasir Nurbadillah, Nurbadillah Nurjihan, Saniyyah Wafa Rabika, Jonathan Cristiano Rasendriya, Achmad Syahmi Wiguna, Indra Maki