Judul: Higiene Pekerja Kantin di Dalam Kampus Institut Pertanian Bogor Dramaga, Bogor
Abstrak: The aim of this study was to know the factors related with hygiene practices among food handlers at canteen in Bogor Agriculture University. Survey of KAP (knowledge, attitude, and practices) were used to know the relationship of knowledge and attitudes with their practices as its factors. Thirty nine food handlers were taken sampling randomly from sixty seven canteen in Bogor Agriculture University and become respondents for questionnaire about hygiene in handling food which is divided in to three aspect: personal hygiene, hygiene of production, and hygiene of facilities. The data were analyzed using the SPSS 16.0. A majority respondents have good knowledge (94.9%), attitude (100%), and practices (97.4%). Statistic analysis showed significant difference (p<0.05) between the relationship of knowledge, attitude, and main occupation with their practices
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Judul: Studi Knowledge, Attitude, and Practice (KAP) Higiene Pangan pada Food Handler di Kios Makanan di Dalam dan Luar Kampus IPB Dramaga, Bogor
Abstrak: Food besides giving benefit for human health is also easy to be contaminated with various contaminants so that can cause disease (foodborne disease). One of many factors influencing incidence of foodborne disease is food handler. Important factors on food handlers which have impacts on food hygiene are knowledge, attitude, and practice. The purpose of this study was to determine the level of knowledge, attitudes, and practices; correlation between knowledge, attitudes, and practices; and risk factors of food hygiene practices. Total of 77 kiosks from 373 food kiosks inside and outside of IPB campus in Dramaga, Bogor was sampled randomly. The data include characteristics and KAP food handler which is obtained from interviews with respondents using questionnaires and observations, and level surface sanitizing food handlers hands and dishes in kiosks with RODAC test (total plate count and the number of Staphylococcus aureus). This study showed that most of the food handlers were categorized as good in knowledge (55.8%) and practices (70.1%), while most of food handlers’ attitude were categorized as moderate (51.9%). The level of hygiene in food kiosks was mostly good (76.6%). Risk factors which influenced on hygiene level in food kiosks were age (young age, OR = 12.6), the participation in extension (never exposed to extension, OR = 8.3), and attitude (bad attitude, OR = 43.7). Characteristic variables that had significant correlation with knowledge, attitude, and practice were the correlation between extension and knowledge (r = 0.59), monitoring and knowledge (r = 0.63), work experience and attitude (r = 0.35), purpose of business and attitude (r = 0.51), extension and attitude (r = 0.53), and age and practice (r = 0.71). This study showed significant correlation (p<0.05) between knowledge and attitude (r=0.73), knowledge and practice (r=0.79), and attitude and practice (r=0.84). More than half of food kiosks showed bad sanitation level of hands and plates. Practice of personal hygiene showed significant correlation with score the number of Staphylococcus aureus in food handler hand (r=0.15). The results of this study should be considered as potential threat to consumer health inside and outside of IPB campus in Dramaga, Bogor.
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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