Judul: Studi Kasus Infestasi Pinjal Kucing (Ctenocephalides felis) pada Manusia di Desa Cangkurawok Kabupaten Bogor
Abstrak: This case study reports cat flea infestations (Ctenocephalides felis) in humans on October 2012. Fleas attacked five members of a family who lived in Cangkurawok village Bogor regency. Clinical disorders appeared only in three children, all of them suffered from severe itching after flea bites then led to a maculopapular rash on the site. Allergic reaction that occured was hypersensitivity due to flea bites (flea allergic dermatitis). Interview revealed the presence of stray cat in front of their home, one week before this case happened. Fleas were collected manually by using cloth or cotton that had been soaked with alcohol on the toe, hands, and neck being bitten. Microscopic identification confirmed that the flea is cat flea (C. felis). This finding indicates that humans could be accidental host for cat fleas which lose its natural host. Finally this result showed that fleas do not have specific host and could be residential pest.
Keyword: stray cat, flea allergic dermatitis, Ctenocephalides felis

Judul: Infestasi Pinjal dan Infeksi Dipylidium caninum pada Kucing Liar Di Kampus Institut Pertanian Bogor Dramaga
Abstrak: This study was conducted to investigate flea infestation and Dipylidium caninum infection on stray cat in Bogor Agricultural University Dramaga. The totals of 30 stray cats were collected from various places which found commonly in Bogor Agricultural University Dramaga. The stray cats were collected purposifelly which showed pruritus and alopecia. The whole body of cat powdered by gamexan powder, after that the fleas were collected by manual and examined microscopically. The D. caninum were examined from 30 fecal samples of stray cats used McMaster methode, flotation methode and observed by existence of proglotids. Fleas identification were conducted in Laboratory Entomology, while fecals were examined in Laboratory Helminthology, Faculty of Veterinary Medicine Bogor Agricultural University. The identification showed that was only one spesies of flea namely Ctenocephalides felis, while D. caninum were not found. Twenty one (70%) from thirty cats were infestated by the flea with density average of fleas per cat was 3.8±1.9.
Keyword: Ctenocephalides felis, Dipylidium caninum, Prevalence, Stray cat.

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