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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika) Media Elektrik
Pailus, Muhammad
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering

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Model Identifikasi Penyakit Pada Tumbuhan Padi Berbasiskan DenseNet Pailus, Muhammad; Fudholi, Dhomas Hatta; Hidayat, Syarif
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.478

Abstract

Errors in identifying diseases in rice plants can cause the potential for crop failure to increase by 18-80%, according to data from the Indonesian Ministry of Agriculture. This could be due to the lack of expertise in agriculture when compared to the amount of land in Indonesia. Recent research in the field of deep learning using neural networks has achieved remarkable improvements. Research on the identification of plant diseases in rice plants, using the MobileNet, NasNet and SqueezeNet architecture that supports mobile devices has been carried out. The experimental results show that the proposed architecture can achieve an accuracy of 93.3%. Motivated by previous research, this research will use DenseNet architecture (Dense Convolutional Network) to detect diseases in rice plants. The dataset used is relatively small, between 100-200 photos for each disease. To cover the lack of dataset augmentation is done to the dataset. The final results obtained are quite satisfactory with an accuracy of 96% with a Weighted Average of 97%.
Model Identifikasi Penyakit Pada Tumbuhan Padi Berbasiskan DenseNet Pailus, Muhammad; Fudholi, Dhomas Hatta; Hidayat, Syarif
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.478

Abstract

Errors in identifying diseases in rice plants can cause the potential for crop failure to increase by 18-80%, according to data from the Indonesian Ministry of Agriculture. This could be due to the lack of expertise in agriculture when compared to the amount of land in Indonesia. Recent research in the field of deep learning using neural networks has achieved remarkable improvements. Research on the identification of plant diseases in rice plants, using the MobileNet, NasNet and SqueezeNet architecture that supports mobile devices has been carried out. The experimental results show that the proposed architecture can achieve an accuracy of 93.3%. Motivated by previous research, this research will use DenseNet architecture (Dense Convolutional Network) to detect diseases in rice plants. The dataset used is relatively small, between 100-200 photos for each disease. To cover the lack of dataset augmentation is done to the dataset. The final results obtained are quite satisfactory with an accuracy of 96% with a Weighted Average of 97%.
IMPLEMENTATION OF INFORMATION SYSTEM FOR ADMINISTRATION AND GEOSPATIAL OF WERNAS VILLAGE IN SOUTH SORONG BASED ON WEBSITE AND ANDROID Novandi Rezeki; Pailus, Muhammad
Jurnal Media Elektrik Vol. 22 No. 2 (2025): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v22i2.6808

Abstract

This research aims to address the challenges of administration and natural resource management in Wernas Village, South Sorong, Southwest Papua, through the implementation of website-based administrative and geospatial information systems and Android applications. Wernas Village, which is currently still lagging behind in terms of technology, has great potential to develop a modern digital village, especially by utilizing abundant natural resources such as rivers. In order to achieve these objectives, this research uses mixed methods research that combines qualitative and quantitative approaches. The initial stage involved a preliminary study to analyze the needs and challenges of the village, followed by the design of an information system that included website design, Android application, and geospatial mapping.The prototype of the information system was then developed and tested in a limited environment in the village. Evaluation and refinement were carried out based on the results of the trial, with the aim of ensuring the information system was ready for full implementation. The targeted outputs of this research include the design of an information system prototype that is ready to be implemented, mapping of administrative needs and management of village natural resources, as well as improving the quality of public services and administrative efficiency. It is expected that the results of this research can make a significant contribution in improving the quality of life of the people of Wernas Village, accelerating inclusive and sustainable village development, and becoming an example for other villages in the South Sorong Regency area to adopt information technology to advance local development.
Co-Authors Fudholi, Dhomas Hatta Novandi Rezeki Syarif Hidayat