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All Journal CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics
Gina Purnama Insany
Universitas Nusa Putra, Sukabumi, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice

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Klasifikasi Tanaman Hias Philodendron Berdasarkan Citra Daun Menggunakan Metode Convolutional Neural Network Muhamad Cepnur Al-Basori; Gina Purnama Insany; Ivana Lucia Kharisma
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 10 No 2 (2024): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v10i2.3238

Abstract

Philodendron ornamental plants have a unique and varied aesthetic beauty, making them sought after in the landscaping and decoration industry. However, accurate classification of the various Philodendron species is challenging due to their morphological similarities and complex variations. In this research, an approach using Convolutional Neural Networks (CNN) is introduced to classify Philodendron ornamental plants based on the image of their leaves. This method aims to automatically identify Philodendron species through the use of artificial neural networks trained on leaf images. A CNN architecture was developed which includes a convolution layer and a max-pooling layer to extract features from the input image hierarchically. Also applied are data augmentation techniques to increase the variety of training samples and reduce overfitting. Experimental results show that the proposed CNN method is able to classify Philodendron ornamental plants with good accuracy, reaching 95,00% on the test dataset. This research contributes to the development of an automatic system for identifying Philodendron ornamental plants, which can be used in planting, plant care and plant identification applications.
Implementasi Automatic Speech Recognition Pada Penilaian Hafalan Al-Quran Dengan Metode Muroja’ah Berbasis Android Alun Sujjada; Gina Purnama Insany; Muhamad Fajar Nugraha
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 10 No 2 (2024): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v10i2.3247

Abstract

This research implements Automatic Speech Recognition (ASR) technology in the process of assessing Al-Qur'an memorization to overcome the problem of the increasing number of people who cannot read the Al-Qur'an fluently. With ASR, computers can recognize and transcribe human speech accurately, thereby improving the quality and accuracy of pronunciation and providing constructive feedback to learners. An Android-based application that uses the ASR service from the Google Speech API allows users to recite verses from the Koran and automatically recognize and evaluate what they have memorized. The hope is that the use of ASR technology can improve the ability to memorize the Al-Qur'an more effectively and flexibly without requiring direct teacher assistance. This system was developed using the Rapid Application Development (RAD) method with Blackbox Testing.
Co-Authors Alun Sujjada Ivana Lucia Kharisma Muhamad Cepnur Al-Basori Muhamad Fajar Nugraha