Judul: Detection of Authenticity of Aceh Sigupai Rice Using Portable Near Infrared Spectrometer
Abstrak: Sigupai merupakan varietas beras aromatik yang menjadi ciri khas kabupaten Aceh Barat Daya. Banyaknya varietas beras dengan kemiripan karakter, memperbesar peluang pencampuran beras dalam pendistribusian. Tujuan dari penelitian ini adalah memprediksi keaslian beras sigupai dan persentase tingkat keaslian beras sigupai secara non-destruktif menggunakan portable near-infrared (NIR) spectrometer. Penelitian ini dianalisis dengan metode Partial Least Square-Driscriminant Analysis (PLS-DA) dan Partial Least Squares-Regression (PLS-R) pada dua perlakuan. Perlakuan pertama, beras yang digunakan adalah sigupai murni (tanpa campuran) dan sigupai campuran (sigupai dan inpari dengan persentase 1% sampai 30% atau pada tingkat keaslian 69,9% sampai 99%) masing-masing 43 sampel. Perlakuan kedua, beras yang digunakan adalah sigupai yang dicampur dengan inpari pada konsentrasi 0% sampai 30% atau pada tingkat keaslian 69,9% sampai 100% sebanyak 44 sampel. NeoSpectra dan SCiO dengan metode Partial Least Square-Driscriminant Analysis (PLS-DA) mampu memprediksi keaslian beras sigupai dengan hasil terbaik menggunakan data original (tanpa pre-treatment). Hasil terbaik dengan NeoSpectra menghasilkan nilai akurasi, sensitivitas, spesifisitas, dan false positive rate, yaitu masing-masing 89,29%; 92,86%; 85,71% dan 14,29%, sedangkan SCiO menghasilkan nilai akurasi, sensitivitas, spesifisitas, dan false positive rate, yaitu masing-masing 97,44%; 100%; 94,87% dan 5,13%. Analisis dengan metode Partial Least Squares-Regression (PLS-R) juga mampu menduga persentase tingkat keaslian beras sigupai dengan hasil terbaik menggunakan pre-treatment derivative SG1. NeoSpectra menghasilkan nilai koefisien korelasi kalibrasi, koefisien korelasi validasi, SEC, SEP, RPD, dan konsistensi, yaitu masing-masing 0,99; 0,96; 1,52%; 1,50%; 5,93, dan 100,69%. SCiO menghasilkan nilai koefisien korelasi kalibrasi, koefisien korelasi validasi, SEC, SEP, RPD, dan konsistensi, yaitu masing-masing 0,99; 0,98; 1,37%; 1,31%; 6,83 dan 104,78%. Hasil penelitian menunjukkan bahwa portable near-infrared spectrometer, baik NeoSpectra maupun SCiO berpotensi digunakan sebagai alat analisis keaslian beras sigupai di lapangan., Sigupai is one of the local rice varieties that characterizes the Southwest Aceh district. Wide rice varieties with similar characters increase the chances of mixing rice in distribution.The purpose of this study was to non-destructively predict the authenticity of sigupai rice and the percentage of authenticity in sigupai rice using a portable near-infrared (NIR) spectrometer. This study was analyzed using the Partial Least Square-Driscriminant Analysis (PLS-DA) and Partial Least Squares-Regression (PLS-R) methods for the two treatments. In the first treatment, the rice used was pure sigupai (without mixture) and mixed sigupai (sigupai and inpari with a percentage of 1% to 30% or at an authenticity level of 69,9% to 99%), each of 43 samples. In the second treatment, the rice used was sigupai mixed with inpari at a concentration of 0% to 30% or at an original level of 69,9% to 100% for 44 samples. NeoSpectra and SCiO with the Partial Least Square-Driscriminant Analysis (PLS-DA) method were able to predict the authenticity of sigupai rice with the best results using original data (without pre-treatment). The best results with NeoSpectra produced accuracy values, sensitivity, specificity and false positive rate values, namely 89,29%; 92,86%; 85,71% and 14,29%, while SCiO produced accuracy values, sensitivity, specificity, and false positive rate, namely 97,44%; 100%; 94,87% and 5,13%. Analysis using the Partial Least Squares-Regression (PLS-R) method was also able to estimate the percentage of authenticity in sigupai rice with the best results using pre-treatment derivatives SG1.
Keyword: Authenticity, NeoSpectra, SCiO, Portable NIR, Sigupai rice

Judul: Spectral Pattern Analysis of Rice Varieties with Proximal Sensing Method and Sentinel-2 Imagery
Abstrak: Pemantauan pertumbuhan padi melalui berbagai wahana penginderaan jauh seperti satelit Sentinel-2 sudah banyak dilakukan, namun variasi ketinggian dan bauran reflektansi menyebabkan tingkat akurasi berbeda. Proximal sensing memungkinkan pemantauan dekat (ground-level) melalui sensor beresolusi tinggi. Spectroradiometer merupakan perangkat penginderaan proksimal yang mampu merekam pola spektral secara kontinu suatu objek, sehingga informasi yang diperoleh lebih rinci. Penelitian ini bertujuan menganalisis karakteristik pola spektral tanaman padi varietas Ciherang dan Ketan Grendel berdasarkan metode proximal sensing dan menganalisis keterkaitan pola spektral kedua varietas hasil pengukuran spectroradiometer dengan citra Sentinel-2. Berdasarkan analisis spektral, varietas Ciherang mencapai nilai reflektansi maksimum untuk panjang gelombang red-edge dan NIR pada 56 HST kemudian menurun pada 81 HST, sedangkan varietas Grendel baru mencapai nilai reflektansi maksimum pada 81 HST dan menurun pada 86 HST. Berdasarkan regresi linier, hubungan antara nilai reflektan hasil pengukuran spectroradiometer dan citra Sentinel-2 pada 23 HST memiliki nilai R² yang lebih rendah yaitu 0.5869 dan 0.5178. Hal ini dikarenakan tanaman belum berkembang dan permukaan sawah belum tertutup seluruhnya oleh kanopi tanaman. Hubungan nilai spektral pada 56, 81, 86, dan 90 HST menunjukkan nilai reflektansi pengukuran spectroradiometer setara atau ekuivalen dengan nilai reflektansi hasil ekstraksi citra Sentinel-2 dengan rata-rata R² di atas 86%., Rice growth monitoring through remote sensing such as Sentinel-2 imagery has been widely used, yet the accuracy level is different due to variations in altitude and object reflectance. Proximal sensing provides site (ground-level) monitoring via high-resolution sensors. Spectroradiometer is a proximal sensing device that can continuously record the spectral pattern of an object. This research aims to analyze spectral pattern characteristics of Grendel sticky and Ciherang rice varieties based on proximal sensing and to analyze relationship between reflectance value of spectroradiometer and Sentinel-2. Based on spectral analysis, Ciherang variety reached the maximum reflectance value for red-edge and NIR wavelength at 56 DAP and then decreased at 81 DAP, while Grendel variety just reached the maximum value at 81 DAP and decreased at 86 DAP. The relationship between the reflectance value of spectroradiometer and Sentinel-2 at 23 DAP had a lower R² value, 0.5869 and 0.5178. These are because plants have not yet developed and the rice fields surface has not been completely covered by plant canopy. Relationships at 56, 81, 86, and 90 DAP indicated reflectance values of spectroradiometer measurement are equivalent to value of Sentinel-2 image extraction with an average of R² above 86%.
Keyword: Ciherang rice, Grendel sticky rice, reflectance value, spectroradiometer

Judul: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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