Judul: Predict the NDVI Trend of Rubber Plants Using Random Sentinel-2 Image-Based Forest Regressor (Case Study: Pusat Sembawa Rubber Research)
Abstrak: Karet merupakan salah satu komoditas ekspor unggulan pada sektor perkebunan yang berperan besar sebagai penghasil devisa negara Indonesia. Namun dengan banyaknya permintaan terhadap bahan baku karet tidak diimbangi dengan laju peningkatan produksi karet di Indonesia. Penurunan produksi karet ini disebabkan oleh adanya penyakit gugur daun yang disebabkan oleh jamur Pestalotiopsis Sp. Oleh sebab itu, diperlukannya sistem monitoring kesehatan tanaman karet dengan menggunakan teknologi remote sensing untuk memprediksi trend kesehatan tanaman karet berdasarkan nilai NDVI sehingga pemerintah dapat membantu petani karet dalam melakukan monitoring kesehatan tanaman karet. Tujuan dari penelitian ini untuk memprediksi trend dan analisis kesehatan tanaman karet berdasarkan nilai indeks NDVI untuk 1 bulan hingga 12 bulan kedepan dengan menggunakan model machine learning random forest regressor. Nilai mean absolute error yang didapatkan oleh model random forest regressor pada setiap klon sekitar antara 0,02334 – 0,06546.
Keyword: Normalized Difference Vegetation Index (NDVI), Random Forest  Regressor, Remote Sensing, Rubber, Sentinel-2, Pestalotiopsis Sp

Judul: Prediction of Rubber Plantation  Productivity Using Sentinel-2A Satellite Imagery in PT. Perkebunan Nusantara III
Abstrak: Karet merupakan komoditas penting di Indonesia dengan sumbangan ekspor yang tinggi dan kegunaannya sebagai bahan baku berbagai industri. Hal ini perlu digunakan sebagai kesempatan untuk memperbarui penggunaan penginderaan jauh sebagai prediktor produktivitas perkebunan karet. Analisis untuk menguji keterkaitan normalized difference vegetation index (NDVI) dengan produktivitas perkebunan karet dilakukan untuk menentukan keterkaitan antara NDVI median dengan produksi lateks di perkebunan karet. Penelitian ini menggunakan Google Earth Engine sebagai alat untuk memperoleh nilai NDVI dari Sentinel-2A dan diuji keterkaitannya dengan menggunakan pengukuran berdasarkan nilai koefisien determinasi atau R2. Nilai rerata koefisien determinasi yang rendah, yaitu kurang dari 0,5, menunjukkan bahwa nilai NDVI median tidak dapat digunakan sebagai prediktor produktivitas perkebunan karet dalam jangka waktu yang lama, melainkan hanya dalam jangka waktu semusim dan hanya berlaku di beberapa kelompok tertentu, seperti di kelompok meningkat dan lembah Afdeling 1, dan kelompok puncak dan menurun di Afdeling 5, yang mempunyai nilai rerata R2 lebih dari 0,5. Keadaan tersebut disebabkan oleh faktor tutupan awan, jenis klon yang digunakan, dan penggunaan stimulan di perkebunan karet., Rubber is an important commodity in Indonesia with a high export contribution and its use as a raw material for various industries. This needs to be used as an opportunity to renew the use of remote sensing as a predictor of rubber plantation productivity. An analysis to test the relationship between normalized difference vegetation index (NDVI) and rubber plantation productivity was carried out to determine the relationship between median NDVI and latex production in rubber plantations. This research uses Google Earth Engine as a tool to obtain NDVI values from Sentinel-2A and tests the correlation using measurements based on the coefficient of determination or R2 value. The low average value of the coefficient of determination, namely less than 0,5, indicates that the median NDVI value cannot be used as a predictor of rubber plantation productivity over a long period of time, but only over a season and only applies in certain phases, such as in the meningkat and bottom Afdeling 1, and peak and downward phases in Afdeling 5, which have an average R2 value of more than 0,5. This situation is caused by cloud cover, the type of clone used, and the use of stimulants in rubber plantations.
Keyword: karet, ndvi, keterkaitan, prediksi, produktivitas, correlation, rubber, productivity, prediction

Judul: Algorithm construction of HLI hash function
Abstrak: Cryptography is a study of mathematical techniques related to aspects of information security regarding on confidentiality, data integrity, entity authentication, and data origin authentication. Data integrity is a service, which is associated with the conversion of data carried out by unauthorized parties. To maintain data integrity, one can use hash functions. An hash function is a computationally efficient function to map an arbitrary length bitstring to a fixed length bitstring called as hash value. The use of hash function in maintaining the information integrity and authentication is in digital signatures, virus protection, and software distribution. Illustration of the hash function in the integrity and authentication of information that is emailed as follow. The sender sends the information and hash value to the recipient. If the hash value of the information is equal to the hash value that is sent by the sender, then information has not been changed. Otherwise the information has been changed. An hash function has two properties, one way and collision resistance. An hash function is called one way if it is computationally infeasible to find any input such that when given any hash value . Meanwhile an hash function is called collision resistant if it is computationally infeasible to find any two inputs where such that . The purpose of this study is to construct a HLI hash function algorithm, to analyze the speed and security of the hash functions as a results of construction. Furthermore, it is to compare it with SWIFFT. Hash function is constructed based on the result of algebraic operations on modular polynomial ringwith . Modular polynomial ring noted as is a set of all polynomials of degree at most with coefficients in . can be represented as a set of integer vector of modulo in dimension . So, it is simple to implement in a computer. In vector operations, is lattice . Furthermore, alattice that is defined from certain polynomial ring is called ideal lattice. HLI hash function is consists of addition and multiplication algorithm in the ring. Addition algorithm consists of sumation operations of modulo and multiplication consists of multiplication operations of modulo . Generally, algorithm of HLI hash function consists of multiplication operations of modulo and addition operations of modulo . However, if the input is binary number then multiplication algorithm only consists of multiplication operation of modulo , so algorithm of HLI hash function consists of multiplication operations of modulo and addtion operations of modulo . An hash function is secured if it has two properties, i.e., one way and collision resistance. HLI hash function hash is one way, it is following the proof of Micciancio. It is has collision resistant because of polynomial is irreducible over and monic. Moreover, it is proved that for every unit vector , the vector is small vector. If the input of hash function is a binary number then HLI hash function only involves addition operations of modulo . So the time that used almost same with SWIFFT. The excellence of HLI hash function is the key size smaller than SWIFFT. This effect on
Keyword: hash function, modular polynomial ring, lattice