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Journal : PELS (Procedia of Engineering and Life Science)

Classification of Calligraphy Writing Types Using Convolutional Neural Network Method (CNN) Oddy Virgantara Putra; Aziz Musthafa; Muhammad Nur; Muhamad Rido
Procedia of Engineering and Life Science Vol 2 (2021): Proceedings of the 3rd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (467.808 KB) | DOI: 10.21070/pels.v2i0.1136

Abstract

Calligraphy is the art of beautiful Arabic writing in which a series of letters are formed in appropriate proportions, maintaining distance and accuracy containing verses from the Qur'an or Hadith. There is a challenge to recognize the type of calligraphy using machine learning. This study aims to classify the types of calligraphy writing for ordinary people who do not understand the differences between each type of calligraphy writing. This study builds a model using the Convolutional Neural Network (CNN) method. The image used will go through a noise cleaning, resizing, and cropping process. This method is to carry out the process of classifying the type of calligraphy using a dataset consisting of 230 of 2 different types of calligraphy, namely the Naskhi and Riq'ah types. 80% is used as training data and 20% for test data. In the modeling process there are two convolutional layers and two MaxPooling layers followed by a Fully connected layer. The CNN modeling results used to test the built data have an average percentage result of 89% accuracy from the training data used. For further research, it can be developed with other types of calligraphy.
Design and Build Smart Aquascape Based on PH and TDS With IoT System Using Fuzzy Logic Muhammad Fikri; Aziz Musthafa; Faishal Reza Pradhana
Procedia of Engineering and Life Science Vol 2 (2021): Proceedings of the 3rd Seminar Nasional Sains 2021
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (281.899 KB) | DOI: 10.21070/pels.v2i0.1166

Abstract

Acid (pH) and Total Dissolve Solid (TDS) are the two most important factors of the many parameters that must be considered to maintain water quality in Aquascape. A good normal pH for plant life in Aquascape is 6.8 and a good TDS for water in aquascape is below 150 ppm. This study aims to design an IOT system to maintain the pH and TDS of water in aquascapes. In this study using the fuzzy method as a controller and determinant of the added value of acid or wet water in the aquascape. The pH set in this system is between 6.5-7.3. This system maintains the pH by adding alkaline or acidic water into the aquascape, so that the pH of the water in the aquascape is at a predetermined safe limit. the TDS system will drain the water in the aquascape, and add water with a lower TDS level. By calculating how many additions are right to keep the TDS of water in the aquascape at 150ppm. The result of this research is a system design that is able to control the pH and TDS of water in Aquascape.