Judul: Implikasi eksistensi chromolaena odorata (l.) King & robinson (asteraceae) dan agens hayatinya cecidochares connexa macquart (diptera: tephritidae) terhadap struktur komunitas serangga dan tumbuhan lokal
Abstrak: ALAL HUDA JAYA. S. Implication of existence both of Chromolaena odorata (L.) King & Robinson (Asteraceae) and its biological control agent - Cecidochares connexa Macquart (Diptera: Tephritidae) to local plant and insect community structure. Supervisors: DAMAYANTI BUCHORI and SOEKISMAN TJITROSEMITO. The aims of this research were (1) to study density and population distribution of C. odorata and its biological control agent - C. connexa, and (2) to study local plant and insect community structure in invaded area of C. odorata. Several activities have been conducted i.e. survey of research sites, vegetation analysis, and insect sampling. The study sites were selected base on purposive sampling method. All area located in Bogor district (Parung Panjang, Setu, Darmaga, Gunung Bunder, Ciawi, and Cisarua), Sukabumi district (Gunung Salak, Gunung Halimun, and Pakuwon), and Cianjur district. Analysis of vegetation were conducted using combination of transect and quadrate method. Insect were sampled by setting up several traps inside the plots. Pitfall trap and yellow pan trap were set up inside the plot, whereas malaise trap were placed between two transect lines. The result found that invasive exotic plant species (C. odorata) spread on whole study sites and well-growth on different habitat types (plantations, production forest, low land, and high land). Their population densities tend to decrease with increasing altitude. The occurrences of C. odorata co-exist with its biological control, the gall flies C. connexa. Almost all study sites (except Gunung Halimun and Cianjur) found these flies. Recently, C. connexa have established and wide spread, although the present of barrier (like mountain) is restriction factor for distribution of flies in West Java. Over 131.132 individual of plants consist of 21 families and 44 species were identified co-exist with C. odorata in Bogor area (Parung Panjang, Setu, Darmaga, and Gunung Bunder). In the same area, over 24.213 individual of insect consist of 14 orders, 132 families, and 568 species were found in C. odorata habitat. Three dominance insect orders i.e. Hymenoptera, Diptera, and Hemiptera were collected with high species richness and abundance. Implication of existence of C. odorata caused replacement local plant species and homogenization habitat on spatial scale. Introduction of C. odorata and its biological control agent caused and consequently associate with local insects.
Keyword: 

Judul: Implikasi eksistensi Chromolaena odorata (L.) King & Robinson (Asteraceae) dan agens hayatinya Cecidochares connexa Macquart (Diptera: Tephritidae) terhadap struktur komunitas serangga dan tumbuhan lokal
Abstrak: Penelitian ini bertujuan untuk mempelajari distribusi dan kelimpahan populasi C. odorata dan agens hayatinya C. connexa, serta mempelajari struktur komunitas serangga dan tumbuhan lokal di daerah yang telah diinvasi oleh C. odorata. Kegiatan yang dilakukan adalah survei lokasi penelitian, analisis vegetasi, dan koleksi serangga. Penelitian ini berlokasi di Jawa Barat yang meliputi daerah Parung Panjang, Setu, Darmaga, Gunung Bunder, Gunung Salak, Gunung Halimun, Pakuwon, Ciawi, Cisarua, dan Cianjur. Lokasi penelitian tersebut ditentukan berdasarkan metode purposive sampling. Analisis vegetasi dilakukan dengan metode transek yang dikombinasikan dengan metode kuadrat. Koleksi serangga dilakukan di dalam petak contoh dengan memasang perangkap pitfall trap dan yellow pan trap, sedangkan perangkap malaise trap diletakkan secara diagonal diantara jalur transek.
Keyword: 

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