Judul: Identifikasi Komponen Antibakteri pada Ekstrak Buah Takokak (Solanum torvum Swartz) dengan Kromatografi Lapis Tipis
Abstrak: Turkey berry (Solanum torvum Swartz) is one of medicinal plants and indigenous vegetables which grows abundantly in Indonesia. It has been known to have antibacterial activity againts some pathogen bacterias, including Bacillus cereus. The aim of this study is to determine turkey berry’s metabolites that have antibacterial activity by TLC method. The dried turkey berry was extracted by eight different combinations of methanol and water. These extracts were then divided into two parts: for antibacterial activity analysis and for TLC analysis. Extract with good antibacterial activity and showed more spots in TLC was further identified by two-dimentional TLC. The Rf score of this extract was also compared with reference compounds. F1 extract which was extracted by methanol:water (1:0) showed the highest diameter of inhibition. It also had more TLC spots than other extracts. F1 extract was then chosen to be identified by two-dimentional TLC. It showed 14 sub-spots which have maximum absorption at 200-400 nm. Some sub-spots of F1 extract also showed similar Rf score with reference compounds. Based on its TLC profile, F1 extract may contain saponin, gallic acid, quercetin, myricetin, kaempferol, and apigenin. However, since TLC has limited resolution, it is possible that F1 contains other flavonoids and phenolic acids that may also responsible for its antibacterial activity.
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Judul: Aktivitas Antioksidan Ekstrak Buah Takokak (Solanum torvum Swartz.)
Abstrak: Turkey berry fruit (Solanum torvum Swartz.) is one of indigenous fruit vegetables that widely used in traditional medicine. Because, it has some functional properties such as antioxidant, antibacterial, antifungal, and antiviral. The functional properties come from the activity of some phytochemicals compound that Turkey berry fruit contents, such as phenolics and non phenolics. This research was designed to identify the chemical content of Turkey berry fruit, change content, and antioxidant activity of crushed form. The research method consisted of treatment phase of fresh Turkey berry fruit through the destruction process and extraction phase of Turkey berry fruit powder with organic solvents (methanol, etil acetat, and hexane). The results showed that methanol extract of both whole and crushed Turkey berry fruit, contains alkaloids, flavons, tannins, and saponins. The etil acetat and hexan extracts of both whole and crushed form, contains alkaloids, flavons, terpenoids, and saponins. Thus, the presence of phenolic compounds in Turkey berry fruit can be affected by Phenylalanin Ammonia Lyase (PAL) activity, but not always influenced by the total anthocyanin. In addition, the antioxidant activity (DPPH assay) between whole and crushed Turkey berry fruit extracts is not significantly different (p>0.05) by t-test. It was demonstrated that the destruction process has a little affecting to the presence of phenolic compounds that act as antioxidants, such as anthocyanin. However, the antioxidant activity of extracts is not always determined from total phenolic, but depending on the ability of -OH group to donate H atoms and to bind with free radicals rapidly. The antioxidant activity of Turkey berry fruit extract was slightly be affected by ascorbic acid (vitamin C) compound.
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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