Judul: Estimasi Kandungan Lignin pada Dedak Padi Menggunakan KNN dengan Praproses PCA Berdasarkan Citra Grayscale
Abstrak: Pemalsuan dedak padi yang telah tercampur sekam bisa menurunkan kualitas pakan. Pengujian kandungan sekam dapat diukur dari kandungan lignin melalui reaksi pewarnaan menggunakan larutan phloroglucinol. Warna merah yang semakin pekat menunjukkan semakin tinggi kandungan sekam pada dedak padi. Oleh karenanya, pada penelitian ini akan dilakukan estimasi kandungan lignin pada dedak padi yang telah diwarnai tersebut dengan ekstraksi fitur berbasis Principal Component Analysis (PCA) dengan metode klasifkasi K-Nearest Neighbor (KNN). Citra yang digunakan adalah citra grayscale yang diperoleh dari transformasi citra RGB. Penelitian ini menghasilkan akurasi prediksi tertinggi sebesar 77.27%., Counterfeiting of rice bran mixed with husks can reduce feed quality. The husk content test can be measured from the lignin content through a staining reaction using a phloroglucinol solution. The darker red color indicates the higher the husk content in the rice bran. Therefore, this study will estimate the lignin content of rice bran mixed with husks using feature extraction based on Principal Component Analysis (PCA) with the K-Nearest Neighbor (KNN) classification method. The image used is a grayscale image obtained from the RGB image transformation. This research resulted in the highest prediction accuracy of 77.27%.
Keyword: grayscale, K-Nearest Neighbor, Principal component analysis, rice bran

Judul: Using KNN for Lignin Estimation in Rice Bran Based on Color Image with PCA Preprocessing data
Abstrak: Dedak padi pada umumnya digunakan sebagai bahan pakan tapi mengalami penurunan kualitas ketika dicampurkan dengan bahan lain seperti sekam untuk mendapatkan keuntungan lebih besar dengan memanfaatkan ketersediaan dedak sehingga kualitas dedak padi mengalami penurunan. Pemalsuan dapat diketahui melalui estimasi kandungan lignin dari proses reaksi pewarnaan. Penelitian ini dilakukan untuk mengestimasi kandungan lignin dari citra pewarnaan dedak padi berwarna model RGB dengan menggunakan metode ekstraksi fitur berbasis Principal Component Analysis (PCA) dan K-Nearest Neighbour (KNN) sebagai teknik klasifikasinya. Penelitian ini menghasilkan akurasi terbaik sebesar 77.27 % pada komponen warna merah., Rice bran is generally used as a feed ingredient but decreases in quality when mixed with other ingredients such as husks. to get greater profits by utilizing the availability of bran so that the quality of rice bran has decreased. Forgery can be determined by estimating the lignin content of the staining reaction process. This study was conducted to estimate the lignin content of the RGB model of rice bran coloring images using feature extraction methods based on Principal Component Analysis (PCA) and K-Nearest Neighbor (KNN) as classification techniques. This study resulted in the best accuracy of 77.27% on the red component.
Keyword: K-Nearest Neighbor, Principal Component Analysis, RGB, rice bran

Judul: Dynamical System of Hepatitis B in Three Groups with Vaccination
Abstrak: The aim of this study is to modify the hepatitis B transmission model in three age groups involving vaccination from the model conducted by Zhoe and Zhang.The method used is to analyze the stability of the fixed point and its basic reproduction number (R_0). Performed stability analysis and numerical simulation to see population dynamics. Next, a sensitivity analysis of the parameters was carried out to see its effect on R_0. From the analysis obtained two fixed points, namely non-endemic and endemic fixed points. Non-endemic fixed points are locally asymptotically stable if R_0 <1 Meanwhile, the endemic fixed point is locally asymptotically stable if R_0 > 1. Hepatitis vaccination affects the number of susceptible population, because the more successful the vaccination, the smaller the number of susceptible populations so that the smaller the population will be infected.
Keyword: Dynamic, Hepatitis B, Vaccine, Mathematical model