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All Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Rangkiang Mathematics Journal
Sa’adah, Aminatus
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Computer Science & IT Education Engineering Mathematics Other

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Banana and Orange Classification Detection Using Convolutional Neural Network Lumban Batu, Benedict Evan Lumban Batu; Saputra, Wahyu Andi; Sa’adah, Aminatus
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.80032

Abstract

Fruits play a crucial role in human health, with an average consumption of 81.14 grams per capita per day in Indonesia, where bananas and oranges are the most consumed fruits. Inconsistent fruit quality, typically evaluated manually by farmers, can influence consumer decisions. Artificial intelligence (AI) and computer vision can enhance efficiency and consistency in analyzing fruit quality. Convolutional Neural Networks (CNN) are particularly effective in image recognition. This research uses CNN to classify the quality of bananas and oranges from a dataset of 4000 images, divided into 10% test data, 80% training data, and 10% validation data. Among three models tested, Model 2 performed best with an accuracy of 96.75% and balanced high F1-scores across all categories. The results demonstrate that the CNN model is capable of classifying the quality of bananas and oranges with high accuracy and good evaluation results.
Analysis of Nonlinear Oscillation Models with External Forcing Using the Multiple Scales Method Safira, Ayuni Kemala; Sa’adah, Aminatus; Sulvianuri, Rani; Agnesia, Yoli
Rangkiang Mathematics Journal Vol. 5 No. 1 (2026): Rangkiang Mathematics Journal
Publisher : Department of Mathematics, Universitas Negeri Padang (UNP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/rmj.v5i1.138

Abstract

Nonlinear effects accompanied by external forces can cause the behaviour of the system to become more complex and difficult to explain using linear analysis. Therefore, analytical methods are needed to obtain approximate solutions. This paper presents an analysis of approximate solutions to nonlinear oscillation models subject to periodic external forces. The analysis was conducted using the Multiple Scales Method, a perturbation technique for obtaining asymptotic solutions to nonlinear differential equations. This approach is carried out by introducing several time scales and developing solutions as series in ε. The differential equations that model the system are analysed to orders.  and to obtain approximate solutions that describe the oscillation dynamics of the system. The analysis was performed under two main conditions: when the external force frequency approached the system's natural frequency (main resonance) and when the two were not close. In the non-resonance condition, several special cases were also examined: non-resonant, superharmonic resonance, subharmonic resonance, and low excitation frequency. The results show that first-order asymptotic solutions agree well with numerical solutions. The system response is influenced by parameters such as the amplitude and frequency of the external force, as well as the damping parameter. These findings support further research on more complex nonlinear systems and have practical applications in the design of vibration absorbers and rotating mechanical components to control resonance and improve system stability.
Co-Authors Agnesia, Yoli Ayuni Kemala Safira Lumban Batu, Benedict Evan Lumban Batu Sulvianuri, Rani Wahyu Andi Saputra