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All Journal FaST : Jurnal Sains dan Teknologi Journal of Informatics, Information System, Software Engineering and Applications (INISTA)
Kuntardjo, Samuel Beta
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Computer Science & IT Environmental Science

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Application of MobileNetV2-Based Deep Learning in Detecting Diseases in Chili Plants Aji, Nurseno Bayu; Yudantoro, Tri Raharjo; Safitri, Zulfa; Kuntardjo, Samuel Beta; Mardiyono, Mardiyono; Prayitno, Prayitno; Santoso, Kuwat
Journal of INISTA Vol 7 No 2 (2025): May 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v7i2.1825

Abstract

This study proposes a deep learning model based on MobileNetV2 architecture for the classification of chili leaf diseases using image data. The dataset was compiled from both public and private sources, covering six distinct categories of chili leaf conditions. MobileNetV2 was selected due to its efficiency and accuracy, making it ideal for real-time agricultural applications. The model was enhanced with additional layers to improve feature extraction and classification performance. Stratified 10-fold cross-validation was employed to ensure balanced evaluation across an imbalanced dataset. The experimental results showed an overall accuracy of 91.04% and an average F1-score of 0.906, indicating consistent and reliable classification performance across classes. Confusion matrix analysis highlighted strong predictive capability, particularly in detecting healthy leaves and severe disease symptoms, with minor misclassifications among visually similar categories. The findings confirm the potential of lightweight CNN architectures for practical, mobile-based agricultural diagnostics, contributing to advancements in precision farming and early disease management.
Alat Peraga Kendali Pemanas Udara Berbasis Arduino Uno Sebagai Penunjang Praktikum Laboratorium Kendali Politeknik Negeri Semarang [A Demonstration Tool of Arduino Based Air Heater Controller to Support Control Laboratory of Politeknik Negeri Semarang] Supriyo, Bambang; Kuntardjo, Samuel Beta; Sihono, Sihono
FaST - Jurnal Sains dan Teknologi (Journal of Science and Technology) Vol. 1 No. 1 (2017): NOVEMBER
Publisher : Universitas Pelita Harapan

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Abstract

The objective of this research is to develop and test the demonstration tool of Arduino based air heater controller with Proportional Integral Derivative (PID) based control methods for the temperature range between 50ºC and 70ºC.   Arduino Uno was programmed using C-language to do control tasks and to transfer control data serially to computer via USB port. The selection of the initial PID  parameters are determined using the combination of Relay Feedback method and Ziegler-Nichols  formula.  The control methods were focused on proportional (P), proportional derivative (PD) dan Proportional Integral Derivative (PID) with the performance criteria based on overshoot  dan steady state error.  The experimental results show that the PID controllers give best output responses in terms of zero steady state errors, while P and PD controllers still result in steady state errors of about 3ºC. In addition, P controllers still give about 2,5ºC-4ºC fluctuative output values below set points, while the PD and PID have very small fluctuative values and even very close to zero. This laboratory demonstration tool has shown very good PID based controller performance, so it is feasible to be used as a supporting demonstration tool for control system laboratory in Politeknik Negeri Semarang or even other universities.
Co-Authors Bambang Supriyo, Bambang Mardiyono Mardiyono Nurseno Bayu Aji, Nurseno Bayu Prayitno Prayitno Safitri, Zulfa Santoso, Kuwat Sihono Sihono Tri Raharjo Yudantoro