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Rosandi, Triowali
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Pengembangan Game Edukasi 2D Berbasis Android untuk Meningkatkan Kesadaran Lingkungan pada Anak-Anak: SD N 3 Bumidaya Fernando, Rhino; Laila, Siti Nur; Rosandi, Triowali; Hasibuan, Muhammad Said
TEKNIKA Vol. 18 No. 2 (2024): Teknika Juli - Desember 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13294041

Abstract

Kurangnya kesadaran dan pemahaman masyarakat mengenai pembuangan dan pemilahan sampah yang benar, terutama di daerah perkotaan, masih menjadi masalah utama yang berpotensi menimbulkan dampak negatif bagi lingkungan dan kesehatan. Penelitian ini bertujuan untuk mengembangkan sebuah game edukasi interaktif berbasis Android yang dirancang untuk meningkatkan pengetahuan dan kesadaran anak-anak tentang pemilahan sampah. Metode yang digunakan dalam pengembangan game ini adalah Game Development Life Cycle (GDLC) yang terdiri dari enam tahap: inisiasi, pra-produksi, produksi, pengujian, beta, dan rilis. Hasil dari pengujian menunjukkan bahwa game "Pilah Sampah" mampu meningkatkan pemahaman siswa dalam memilah sampah dengan benar. Sebelum menggunakan aplikasi, hanya 76,67% siswa yang yakin dapat memilah sampah dengan benar, sedangkan setelah menggunakan aplikasi, persentase tersebut meningkat menjadi 93,33%. Game ini efektif sebagai media pembelajaran yang dapat meningkatkan kesadaran lingkungan pada anak-anak
The Application Of The Convolution Neural Network Method Uses A Webcam To Analyze The Facial Expressions Of Problematic Students In The Counseling Guidance Unit (Case Study At SMAN 1 Penengahan Lampung Selatan) Pratama, Rendi; Kurniawan, Rio; Rosandi, Triowali; Nisar, Nisar
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Guidance and Counseling is a service provided to students to help them develop their potential optimally. Detecting students' facial expressions in the counseling room plays a crucial role in assisting counselors in understanding the emotional state of students who may need help, such as depression, anxiety, or stress, as they often find it difficult to express their feelings verbally. Therefore, this research will focus on 7 types of facial expressions: Anger, Disgust, Fear, Happiness, Neutral, Sadness, and Surprise. To classify these facial expressions, a Convolutional Neural Network (CNN) technique will be used, which identifies objects based on color and contours in an image. The aim of this research is to create a CNN model that can detect students' facial expressions during counseling sessions. In this study, the machine learning life cycle method is also employed as a stage in building the CNN model, starting with data collection with a total of 618 images, data cleaning, labeling the data, splitting the data into training and testing data with an 80% training data and 20% testing data ratio, creating the CNN architecture, training and evaluating the created model, and finally implementing it using a webcam. The results of this research show that the model achieved an accuracy of 33%. However, the facial expression detection features using the CNN model successfully detected students' facial expressions despite having a low prediction accuracy rate. Keywords— Convolutional Neural Network, Facial Expression Detection, Guidance Counseling, Machine Learning, Webcam
Co-Authors Fernando, Rhino Laila, Siti Nur M Said Hasibuan Nisar, Nisar pratama, rendi Rio Kurniawan