Judul: Keanekaragaman Spesies Rayap dan Bakteri Simbionnya: Studi Kasus di Kampus IPB Dramaga, Bogor
Abstrak: As tropical country, Indonesia is very rich with biodiversity. Termite species diversity is quite high in this country, i.e around 200 spesies compared to 2000 spesies for the whole world. Since termites must have a symbioses with microbes to digest cellulose, so spesies diversity of those microbes must be correlated with termites spesies diversity. The objective of this research was to inventory spesies diversity of termites and their bacterial symbiont in Campus IPB Dramaga. Termites were collected through observation station installed in the ground and transect 10 m x 10 m which were set in Campus IPB Dramaga area. Symbiont microbes were extracted from proctodeum of each termites spesies with serial dilution technique and staining on culture media. Bacteria kolonied and characterized by Gram and morphology. The results showed that 4 species of termites belong to family Termitidae (Macrotermes gilvus, Capritermes mohri, Odontotermes javanicus, and Microtermes insperatus) and 2 species belong to family Rhinotermitidae (Coptotermes curvignathus and Schedorhinotermes javanicus) were founds. Symbiont bacteria extracted from proctodeum of those termites consist of 34 isolates from Termitidae and 9 isolates from Rhinotermitidae based on Gram and morphological characteristic.
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Judul: Keanekaragaman Rayap Tanah di Hutan Pendidikan Gunung Walat, Sukabumi.
Abstrak: Termites are social insects are included in the order blatodea. Termites are easily encountered in the lowland tropics and this is due to the spread of termite activity is influenced by temperature and precipitation. Termites are many benefits to the ecosystem of the earth, as makrofauna ground termites have a role in the manufacture of passageways in the soil and cause soil to be loose, so good for plant growth (Sigit & Hadi 2006), termites have a role in helping people as a way to destroy wood decomposers or other organic material and return the nutrients to the soil (Nandika et al. 2003). Most of the people thought that termites are destructive insects, it is not out of the activities of termites that cause damage to crops, properties, and damage to buildings made of wood to the detriment of the economy. Which is polymorphic termites live in colonies that have a caste system. Each caste has a different body morphology. Soldier caste has a distinctive form of the mandible. Termites can be identified by observing the size of the head and mandibel of the warrior caste. This study aims to determine the diversity of termites in the area of Mount Forest Education Walat Sukabumi West Java. Termites are found preserved into the film canister containing 70% alcohol. Based on the results of the study of termites from five locations: on the stand agathis, pine, puspa, agroforestry and mess around. The study was conducted in December 2011 to February 2012. Sampling occurs in HPGW Sukabumi, West Java. Specimen measurement, data analysis and image retrieval conducted at the Teknologi Pemanfaatan Mutu Kayu (TPMK) Department of Forest Products, Faculty of Forestry, Bogor Agricultural University. The results of this study indicate that Schedorhinotermes is a genus of Rhinotermitidae family members are most often found, of twenty-six samples obtained thirteen species of termites of whom are members of the genus Schedorhinotermes. Thirteen samples were from termite genus Macrotermes, Odontotermes, Pericapritermes and Nasutitermes. Has six species of the genus Macrotermes, Odontotermes has five species, genus Nasutitermes, Pericapritermes and each amounted to one example. Genus Macrotermes and Odontotermes is the most common genus and has a widespread distribution in almost all locations. Pericapritermes and Nasutitermes is the least genus is found only in one location. Observation needs to be done outside of the five locations that have been made to cover the entire area HPGW. Termite observation needs to be done at various seasons to obtain the completeness of data in different seasons.
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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