Along with technology that is very fast image processing with high quality can be presented and displayed in many ways. The image has detailed information that can cause problems during processing. Image quantization is done as a preprocessing stage to reduce the number of colors in the image so that the resulting image approaches the original image. The purpose of this study is to group clusters of characteristics with the same image value.
Abstract. Purpose: This desire for high resolution stems from two main application areas, namely improving pictorial information for human interpretation and assisting automatic machine perception in representing images or videos. Image resolution describes the detail contained in an image, the higher the resolution, the more detail there is. The resolution of a digital image can be classified into various types, namely pixel resolution, spatial resolution, temporal resolution, and radiometric resolution. In this context, we are interested in spatial resolution.Methods: Elements of a digital image consist of a collection of small images called pixels. Spatial resolution refers to the pixel density of an image and is measured in pixels per unit area. A quality digital image is determined by the size of the resolution it has. A low resolution or low-resolution is a drawback of a digital image because the information contained in the image means little compared to a high-resolution image.Result: Therefore, in this study, a digital image processing program was created in the form of Image Super-Resolution with the Convolutional Neural Network method to utilize low-resolution images to produce high-resolution images. With a fairly short training process, namely 6050 datasets with 100 CNN epochs, the average PSNR image is 5% higher.Novelty: Image quality can be improved by changing the parameters in the CNN method so that image quality can be improved.
Soil is the most crucial factor in the management of agriculture. To measure and monitor soil health status, soil health assessments can be undertaken in the management of agricultural land that aims to determine whether the land is being or will be used in an area in a healthy condition and can perform its functions properly. The results of soil health assessments can also be used as a reference for agricultural land managers to set planning targets and implementing systems to practice soil health management by reducing identified constraints, and assisting land managers in searching agricultural land. Comprehensive soil health assessments can be undertaken based on soil health indicators which consist physical, chemical, and biological properties of the soil. But there is no definite standard for assessing soil health comprehensively, and people who know and understand soil health indicators are still minimal. The number of indicators in soil health assessments can also make it difficult for experts to assess the health of the soil. Therefore, it is needed a Decision Support System of Soil Health Assessment Using Simple Additive Weighting Method so that with this application, it is expected to assist the community especially those involved in agriculture in assessing soil health easily, and quickly, and obtain land health status of an area based on predetermined soil health indicators. Abstrak Tanah merupakan faktor yang paling menentukan dalam
Dinas Komunikasi dan Informatika (DINKOMINFO) Banyumas adalah sebuah instansi yang bertanggung jawab atas pengolahan informasi dalam lingkungan Pemerintahan Banyumas. Pada tahun 2017, Kementrian Kominfo bekerja sama dengan kementrian lain untuk menginisiasi gerakan menuju 100 smart city atau mendorong terciptanya 100 kota cerdas pada tahun 2019. Kabupaten Banyumas terpilih dari salah satu diantara 25 Kota untuk menjadi plot project smart city. Kabupaten Banyumas melakukan akselerasi pembangunan dengan konsep pemanfaatan teknologi untuk mengembangkan smart city Banyumas. Dengan adanya hal tersebut DINKOMINFO menginginkan sebuat aplikasi yang dapat mendorong pengembangan smart city yang efektif, efisien, dan partisipatif serta sebagai bagian dari perencanaan operasional, yang disebut dengan master plan smart city. Pengembangan sistem yang dilakukan menggunakan metode kanban, dengan alat yang digunakan adalah papan kanban (Kanban Board). Hasil dari penelitian ini adalah memberikan informasi mengenai data – data yang masuk di sistem master plan smart city dan dapat mendorong pengembangan smart city yang efektif, efisien, dan partisipatif serta sebagai bagian perencanaan operasional.
Perekomendasian oli secara manual, tanpa menggunakan perhitungan yang akurat cenderung bersifat subyektif serta cukup sulit mengenali karakteristik oli yang paling tepat untuk jenis motor tertentu. Proses analisis data transaksi secara manual berdasarkan pada pengamatan akan mempengaruhi kualitas mesin. Sebagai contoh untuk memberikan rekomendasi oli terbaik bagi seorang konsumen, maka sebuah perusahaan/bengkel sepeda motor harus melihat data transaksi ganti oli yang lalu untuk mendapatkan data tentang oli yang digunakan untuk mengganti oli motor konsumen tersebut. . Penggunaan perangkat komputer dapat digunakan sebagai pendukung keputusan menjadi lebih cepat, tepat, dan akurat. Proses perekomendasian oli terbaik bagi kendaraan bermotor menggunakan metode fuzzy. Hasil perhitungan diperoleh direkomendasikan A3=0.72, A2 = 0.66, A1= 0.55, A4= 0.40.
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