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Classification Of Rice Plant Diseases Using K-Nearest Neighbor Algorithm Based On Hue Saturation Value Color Extraction And Gray Level Co-Occurrence Matrix Features Siti Saniah; Mhd. Furqan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3972

Abstract

This research aims to classify diseases in rice plants using the K-Nearest Neighbor (K-NN) algorithm based on Hue Saturation Value (HSV) color feature extraction and Gray Level Co-Occurrence Matrix (GLCM) texture. The main problem faced is how to identify the type of disease in rice plants automatically using digital images. Diseases such as Blight, Tungro, and Crackle often attack rice plants and require an accurate early detection system. Lack of understanding in recognizing disease symptoms manually often leads to errors in handling. For this reason, this research develops an image processing-based classification system that can detect diseases such as Blight, Tungro, and Crackle. The method used in this research is image processing which includes RGB to HSV color space conversion, texture feature extraction using GLCM, and classification using K-NN algorithm. The dataset consists of 240 images, divided into training data and testing data, namely 192 training data and 48 testing data. Tests were conducted by calculating accuracy at various values of the K parameter, namely K = 1, K = 3, and K = 5, to determine the effectiveness of the model in classifying plant diseases. The purpose of this study was to evaluate the accuracy of the system in identifying rice diseases and test the combination of HSV and GLCM features in improving classification performance. The results showed that using HSV and GLCM features together resulted in the highest accuracy at K=3 with an accuracy value of 75%. The system is expected to assist farmers in detecting plant diseases quickly and effectively, thus minimizing production losses and supporting agricultural sustainability
Resitusi Tanah yang Dikuasai Negara untuk Kepentingan Proyek Kawasan Inti Pusat Pemerintah Ibu Kota Nusantara dalam Perseptif Hak Asasi Manusia Arief Kurniawan; Siti Saniah; Ongky Almus
Mahkamah : Jurnal Riset Ilmu Hukum Vol. 3 No. 1 (2026): Januari : Mahkamah : Jurnal Riset Ilmu Hukum
Publisher : Asosiasi Peneliti dan Pengajar Ilmu Hukum Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/mahkamah.v3i1.1408

Abstract

The development of the Central Government Core Area (KIPP) of the Capital City of Nusantara (IKN) is a national strategic project that has significant implications, particularly in relation to state control/domination of land. The relocation of the national capital to the Capital City of Nusantara (IKN) has become a strategic agenda of the Indonesian government, which aims to realize equitable development and a new administrative center in Indonesia (Law Number 3 of 2022 concerning the National Capital) and has an impact on all aspects of the lives of indigenous peoples in the IKN Nusantara region, particularly in the field of land. However, this project raises serious issues related to state control of land, especially in terms of the rights of the surrounding communities whose land is affected by the Development of the Central Government Area of the Capital City of Nusantara (KIPP IKN). Land restitution is a central issue because it concerns the guarantee of human rights, particularly the right to ownership, access to land, and social justice (Satjipto Rahardjo, Hukum dan Masyarakat [Law and Society] (Bandung: Alumni, 2000). This study analyzes how land restitution in the KIPP IKN development project is viewed from a human rights perspective, emphasizing the need for a balance between national development interests and the protection of citizens' rights.