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All Journal Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Tarbi: Jurnal Ilmiah Mahasiswa
Rochmah, Lailatur
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Computer Science & IT Decision Sciences, Operations Research & Management Other

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Implementation Of Machine Learning To Identify Types Of Waste Using CNN Algorithm Haqqi, Matsnan; Rochmah, Lailatur; Safitri, Arisanti Dwi; Pratama, Rizki Adhi; Tarwoto
JURNAL FASILKOM Vol. 14 No. 3 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i3.8116

Abstract

Waste management remains a significant challenge globally, particularly in Indonesia, where the annual waste generation reached 24.67 million tonnes in 2021, with only 50.43% properly managed. To address the issue of mixed organic and inorganic waste and the lack of public awareness regarding waste separation, this study applied machine learning, specifically the Convolutional Neural Network (CNN) algorithm, to classify waste types. The research aimed to develop an effective automated waste classification model to improve waste management processes. The research involved collecting a dataset of 2,848 images representing six waste categories: glass, cardboard, paper, metal, organic, and plastic. Preprocessing techniques such as cropping, noise reduction with Gaussian filters, and data augmentation were applied to enhance data quality. The dataset was divided into training, validation, and testing subsets in a 70:20:10 ratio. The CNN model employed feature extraction through convolution, activation, and pooling layers, followed by classification using a fully connected layer and a softmax function. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The model achieved an overall accuracy of 95%, with an average precision, recall, and F1-score of 0.95 across all classes. These results demonstrate the CNN model’s ability to reliably classify waste types. Compared to previous studies, this research achieved higher accuracy through the use of enhanced preprocessing and CNN optimization. This study highlights the potential of CNN-based models for automated waste classification, contributing to sustainable waste management practices and fostering environmental awareness in the future research.
Strategi Pembelajaran Berbasis Proyek dalam Menguatkan Hasil Belajar Afektif Pada Mata Pelajaran Pendidikan Agama Islam (PAI) di SMP Negeri 3 Kutowinangun Rochmah, Lailatur; Subarkah, Imam
Tarbi: Jurnal Ilmiah Mahasiswa Vol 5 No 1 (2026)
Publisher : IAINU Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33507/tarbi.v5i1.3194

Abstract

The objectives of this study are: (1) to analyze and describe the project-based learning strategy applied in Islamic Religious Education (PAI) subjects at SMP Negeri 3 Kutowinangun, especially in strengthening students' affective learning outcomes. (2) to analyze the obstacles of project- based learning strategies in strengthening affective learning outcomes in PAI subjects at SMP Negeri 3 Kutowinangun. (3) to analyze solutions to the obstacles of project-based learning strategies in strengthening affective learning outcomes in PAI subjects at SMP Negeri 3 Kutowinangun. This research uses a descriptive qualitative approach with a case study. The subjects in this study were Islamic Religious Education teachers and eighth-grade students of SMP Negeri 3 Kutowinangun in the 2024/2025 academic year. Data collection techniques were carried out through observation, interviews, and documentation. Data analysis was carried out through the stages of data reduction, data presentation, and drawing conclusions. The results of the study indicate that: (1) A project-based learning strategy has been implemented by emphasizing active student involvement in contextual and collaborative learning activities, such as buying and selling simulations, creating Islamic value posters, and group presentations; (2) Obstacles encountered include time constraints, lack of facilities, and teacher readiness in designing projects integrated with affective objectives; (3) The solutions implemented include strengthening learning planning, collaboration between teachers, and developing simple projects relevant to students' life contexts
Co-Authors Haqqi, Matsnan Pratama, Rizki Adhi Safitri, Arisanti Dwi Subarkah, Imam Tarwoto