Judul: Studi interaksi Fusarium sp. dengan pohon gaharu (Aquilaria sp.) menggunakan pendekatan sitologi
Abstrak: The research is aiming to study the pathogenesis mechanism of Fusarium sp. IPBCC. 08.569 on Aquilaria sp. seedling in respect to the respons of the host towards Fusarium sp. IPBCC. 08.569 infection. Penetration mechanism was determined by observing the appresorium formation on the bark surface in vitro, the potency to produce lignocellulase and toxin. While colonization was studied by histopathological methods using both staining process and SEM. The respons of the tree towards infection was observed at either cellular by histochemestry or organ level using scoring system. Fusarium sp. IPBCC. 08.569 showed no appresorium formation but had lignocellulolytic activity. Hypersensitivity reaction of tobacco leaf towards crude extract of extracellular substance indicated that Fusarium sp. IPBCC. 08.569 produce toxin. Direct penetration into the bark was not found, therefore penetration had to be through wounded area. While modification of hyphae was observed in the living cells of the wood tissue (parenchyma rays, included phloem, and pith) these cells might contain terpenoid as conversion of starch. These cellular changes might be observed as discolored wood and the wood became scented. Discolored wood was extended outside the colonization area, indicated that the dark substance might be part of hypersensitive respons to delimit the infection. Using scoring system, after inoculation Fusarium sp. IPBCC. 08.569 can be stated as wound infection fungi with limited colonization in living tissue and induce terpenoid formation in certain tissue.
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Judul: Peranan Zat Ekstraktif Dalam Pembentukan Gaharu Pada Aquilaria crassna Pierre ex Lecomte dan Aquilaria microcarpa Baill
Abstrak: This research is aimed at investigating the anti fungal activity (AFA), the correlation of gaharu tree’s phenolics in relation with the susceptibility of the trees to Fusarium bulbigenum attack in the formation of agarwood, and to observe total phenolics content and tree’s chemicals of Aquilaria crassna and Aquilaria microcarpa pre-inoculation, the reology of tree’s chemical and microorganism change along inoculation time. There were variations of anti fungal activity among trees, and the highest is at tree no. 10 that AFA was in the middle class (39,77%), but entirely agarwood trees exhibited a low anti fungal activity at lab scale. Further fractionation and bioassay showed that the most active component are likely in the ethyl acetate fraction that exhibited strong anti fungal activity at 4% concentration. Trees as many as 20 of A. microcarpa at Carita and 10 of A. crassna at Darmaga were inoculated with isolate of F.bulbigenum in spiral pattern around the stem. Prior to inoculation, strips were taken from the stem for total phenolics content and chemicals analyzing. The result revealed that total phenolics content and infection area exhibited a negative correlation, which means the higher the phenolics content, the smaller the infection area. The preinoculation chemicals analysis showed that tree with smaller infection area had larger type of compounds and higher concentration of phenolics than tree with wider one. Some chemicals that at certain plants acted as defense system, according to some references, were found at higher concentration in the gaharu trees with smaller infection or they were not even traced in other tree. The reology analysis revealed that the largest types of compounds were noticed at three day’s old inoculation. Agarwood constituents and other aromatic compounds were detected since three days after inoculation which is indicated the agarwood formation was taken place. Meanwhile, the microbiology analysis showed there was no microbes change in the inoculation sites along 6 month inoculation time, but some small insects, such as ants and bugs, were found at the area.
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Judul: Implementation of Long Short-Term Memory for Gold Prices Forecasting
Abstrak: Emas merupakan salah satu bentuk investasi dan disebut sebagai aset safe haven karena kestabilannya dalam kondisi pasar yang tidak stabil. Peramalan harga emas menjadi penting bagi investor sebagai alat bantu pengambilan keputusan. Penelitian ini bertujuan untuk melihat pengaruh validasi silang dalam memperoleh hyperparameter LSTM (optimizer, learning rate, dan epoch) terbaik yang akan digunakan dalam peramalan. LSTM sebagai bagian metode deep learning dapat digunakan dalam peramalan selain menggunakan metode klasik. Algoritma ini merupakan pengembangan dari recurrent neural network yang banyak digunakan dalam peramalan deret waktu. LSTM dianggap unggul dan mampu meminimalkan kesalahan, serta mampu melakukan peramalan untuk periode jangka panjang dibanding metode lain. Walk forward validation dengan skenario pergeseran jendela (tahunan, semester, dan kuartal) sebagai bentuk validasi silang digunakan untuk melihat keakuratan metode. Data yang digunakan berasal dari World Gold Council dengan periode data harian untuk tanggal 1 Januari 2003 sampai dengan 20 Januari 2023. Optimizer yang digunakan adalah adam dan RMSProp dengan nilai learning rate 0,01; 0,001; dan 0,0001, serta nilai epoch 100, 500, dan 1000. Model terbaik adalah model dengan nilai MAPE terkecil sebesar 12,41% pada proses validasi menggunakan optimizer RMSProp, nilai learning rate 0,01, dan epoch 100. Hasil peramalan menunjukkan kecenderungan harga emas untuk meningkat dalam delapan tahun mendatang., Gold is a form of investment and is referred to as a safe haven asset because of its stability in unstable market conditions. Gold price forecasting is important for investors as decisions making tool. This study aims to study the effect of cross-validation in obtaining the best LSTM hyperparameters (optimizer, learning rate, and epoch) to be used in forecasting. LSTM as part of deep learning methods can be used in forecasting beside the classical method. Algorithm in the LSTM is developed based on a recurrent neural network that is widely used in time series forecasting. It was found that the LSTM is superior compared to other methods for its ability to minimize errors and to forecast for long-term periods. Walk forward validation with window shift scenarios (annual, semester, and quarter) as a form of cross validation is used to see the accuracy of the method. The data used came from the World Gold Council with daily data periods for January 1, 2003, to January 20, 2023. The optimizer used is adam and RMSProp each with learning rate values of 0.01; 0.001; and 0.0001, and with epoch values of 100, 500, and 1000. The best model was the model with the smallest MAPE value of 12.41% in the validation process using an optimizer RMSProp, a learning rate of 0.01, and epoch value of 100. Forecasting results show a tendency for gold prices to increase in the next eight years.
Keyword: deep learning, forecasting, gold, hyperparameter, LSTM