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All Journal Jurnal Terapan Abdimas JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sains dan Informatika Decode: Jurnal Pendidikan Teknologi Informasi Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Bulletin of Information Technology (BIT) Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Jurnal Sains dan Teknologi SATIN - Sains dan Teknologi Informasi Ahsana: Jurnal Penelitian dan Pengabdian kepada Masyarakat Jurnal Teknik Informatika dan Teknologi Informasi
Pratiwi Susanti
Program Studi Informatika, Fakultas Informatika, Universitas PGRI Madiun
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Sistem Informasi Deteksi Penyakit Pada Tanaman Padi (Brown Spot, Hispa, Leaf Blast) Menggunakan Metode Convolutional Neural Network (CNN) Rachman, Yusuf Fadlila; Susanti, Pratiwi; Putra, Affriza Brilyan Relo Pambudi Agus; Rahmawati, Nuriya Imroatu
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 3: NOVEMBER 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i3.846

Abstract

Sebagai salah satu produsen padi terbesar di dunia, sering menghadapi penurunan produksi akibat serangan penyakit padi. Pendeteksian penyakit secara manual kurang efektif karena keterbatasan pengetahuan petani. Solusi yang ditawarkan untuk mengatasi masalah ini adalah untuk mengembangkan sistem informasi berbasis kecerdasan buatan yang mampu mendeteksi secara otomatis penyakit pada tanaman padi, termasuk Brown Spot, Hispa, dan Leaf Blast, dengan menggunakan metode Convolutional Neural Network (CNN). Sistem ini diharapkan dapat membantu petani dalam melakukan deteksi dini terhadap penyakit padi, sehingga meningkatkan efisiensi dan kualitas produksi pertanian. Sistemmengolah data gambar padi dan mendeteksi kondisi kesehatannya, termasuk mendeteksi padi sehat serta penyakit Brown Spot, Hispa, dan Leaf Blast. Penelitian ini menggunakan 3.355 dataset yang dibagi menjadi 335 untuk proses training, 335 untuk testing, dan 2.685 untuk validasi. Metode yang digunakan pada pengembangan system menerapkan pendekatan pengembangan perangkat lunak Waterfall, yang mencakup analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan system. Sistem "Paddy-AI" yang dikembangkan mampu mencapai akurasi 85% dalam mendeteksi gambar.
Pemanfaatan Metode TOPSIS dalam Menentukan Rekomendasi Laptop Unggulan di Marketplace Tokopedia Pratiwi Susanti; Saifulloh Saifulloh; Alim Citra Aria Bima; Muh Nur Lutfi Aziz; Latjuba Sofyana STT
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 1 (2025): April: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i1.5357

Abstract

The increasing public demand for laptop devices, particularly through marketplace platforms like Tokopedia, results in challenges when selecting a laptop that meets users' needs and preferences. Explore the key laptop specifications that are most important to consumers, such as battery life, RAM, and storage options. Discuss current market trends in laptop sales, including the most popular brands and models among users on platforms like Tokopedia. Highlight the importance of user reviews and testimonials in guiding potential buyers toward their ideal laptop choice. Provide tips for effective comparison shopping on marketplace platforms to help users narrow down their options. Analyze how different consumer preferences (e.g., gaming vs. productivity) influence the types of laptops that are in demand. This study aims to build a Decision Support System (DSS) for selecting the best laptop using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The study was conducted by identifying the main criteria, such as price, RAM, CPU, memory, and dimensions of the laptop, which were then used in the TOPSIS calculation process to determine the best alternative from 15 laptop choices. The results of the study show that the TOPSIS method is able to provide accurate and swift recommendations in choosing a laptop based on user preferences. We implement the system as a website, enabling users to input their preferences and receive automatic laptop recommendations. We expect this study to assist users in making laptop purchasing decisions more effectively and efficiently
Co-Authors Abdul Rozaq Affriza Brilyan Relo Pambudi Agus Putra Ahmad, Khairul Adila Aldida, Jovanza Denis Alim Citra Aria Bima Aminuyati Astuti, Anggun Yuli Eka, Muhammad Rendy Fatim Nugrahati Jayadi, Puguh Juwari Juwari Kurniawati, Inung Diah Latjuba Sofyana STT Moch Yusuf Asyhari Moch. Yusuf Asyari Muh Nur Lutfi Aziz Nasrul Rofiah Hidayati, Nasrul Rofiah Nugrahanti, Fatim Puguh Jayadi Putrian, Aurisha Lutvinda R. Bekti Kiswardianta, R. Bekti Rachman, Yusuf Fadlila Rahmawati, Nuriya Imroatu Riza Akhsani Setyo Prayoga Saifulloh Saifulloh saifulloh Saifulloh, saifulloh Shamsuddin, Norin Rahayu Syamsiar, Syamsiar Tajuddin, Taniza Yessi Yunitasari