Judul: Pengembangan Produk Dimsum Tinggi Zat Besi dan Vitamin A sebagai Camilan untuk Wanita Usia Subur
Abstrak: Kekurangan asupan zat besi dan vitamin A berperan dalam penyebab anemia pada wanita usia subur. Hati ayam memiliki kandungan zat besi dan vitamin A yang cukup tinggi. Ikan gurami merupakan salah satu ikan air tawar khas Indonesia yang produktivitasnya semakin meningkat. Penelitian ini bertujuan mengembangkan dan mengkaji nilai gizi produk dimsum ikan gurami dengan substitusi hati ayam. Tahap penelitian ini meliputi pembuatan formula, uji sensori, analisis kandungan zat gizi, dan analisis karakteristik fisik. Penelitian ini menggunakan empat formula dengan proporsi ikan gurami dan hati ayam yang berbeda, yaitu F0 (100:0), F1 (91:9), F2 (82:18), dan F3 (73:27). Substitusi hati ayam memberikan pengaruh signifikan terhadap karakteristik dimsum. Berdasarkan hasil analisis uji sensori, analisis kandungan gizi, dan karakteristik fisik, F2 ditetapkan sebagai formula terpilih dengan kandungan 65,04% air, 1,98% abu, 9,81% protein, 2,56% lemak, 20,60% karbohidrat, 7,46 mg/100 gram zat besi, dan 975,08 µg/100 gram. Satu takaran saji dimsum ikan gurami dalam penelitian ini dapat memenuhi kebutuhan energi sebesar 6,4%–7,1% dan dapat memenuhi klaim tinggi zat besi dan tinggi vitamin A., Lack of iron and vitamin A intake have a role in causing anemia among reproductive age women. Chicken liver contains high levels of iron and vitamin A. Gouramy is one of the typical Indonesian freshwater fish whose increased productivity. This study aims to develop and examine the nutritional value of gouramy dimsum products with chicken liver substitution. This research phase includes formula making, sensory testing, analysis of nutrient content, and analysis of physical characteristics. This study used four formulas with different proportions of gouramy and chicken liver, namely F0 (100:0), F1 (91:9), F2 (82:18), and F3 (73:27). Chicken liver substitution has a significant effect on the characteristics of dimsum. Based on the results of sensory test analysis, analysis of nutritional content, and physical characteristics, F2 was determined as the selected formula with a content of 65.04% water, 1.98% ash, 9.81% protein, 2.56% fat, 20.60% carbohydrate, 7.46 mg/100 grams of iron, and 975.08 g/100 grams. One serving of gouramy dimsum in this study can provide 6.4%-7.1% of energy and can be claimed as the high iron and high vitamin A product.
Keyword: chicken liver, dimsum, gourami, iron, vitamin A

Judul: Powder Formulation High in Protein, Iron, and Calcium from Rebon Shrimp and Spinach Leaves for Women of Reproductive Age
Abstrak: Anemia merupakan masalah gizi dan kesehatan yang dihadapi masyarakat luas terutama wanita akibat kurangnya asupan pangan sumber zat besi serta keengganan mengonsumsi suplementasi zat besi. Salah satu pencegahan anemia adalah mengonsumsi pangan sumber zat besi. Penelitian ini bertujuan mengembangkan formulasi olahan udang rebon dan daun bayam sebagai pangan sumber zat besi berupa bubuk tabur yang mudah dijangkau oleh masyarakat luas dan menjadi alternatif untuk meningkatkan asupan zat besi. Penelitian ini terdiri dari formulasi, evaluasi sensori, uji karakteristik fisik, dan analisis kimia. Formulasi dilakukan menggunakan tiga formula dengan perbandingan bubuk udang rebon dan daun bayam yang bervariasi yaitu F1 (70:30), F2 (80:20), dan F3 (90:10). Formula terpilih yaitu F3 yang ditentukan berdasarkan hasil seluruh analisis. Satu takaran saji bubuk tabur yaitu 2,5 g atau setengah sendok teh mengandung 8 kkal energi; 1,3 g protein; 0,1 g lemak; 0,3 g karbohidrat; 1,18 mg zat besi; 119,96 mg kalsium; dan 0,68 mcg asam folat serta mampu memenuhi 0,4% energi; 2,2 % protein; 0,2% lemak; 0,1% karbohidrat; 5,4% kebutuhan zat besi; 11,7% kebutuhan kalsium; dan 0,2% kebutuhan asam folat orang dewasa. Formula terpilih berpotensi memenuhi klaim sebagai pangan tinggi protein, zat besi, dan kalsium. Biaya bahan baku formula terpilih sebesar Rp600,00 per sajian., Anemia is a nutritional and health problem faced by the general public, especially women, due to a lack of food intake from iron sources and a reluctance to consume iron supplementation. One way to prevent anemia is to consume foods that are sources of iron. This research aims to develop a formulation of processed rebon shrimp and spinach leaves as a food source of iron in sprinkled, which is easily accessible to the broader community and is an alternative to increasing iron intake. This research includes formulation, sensory evaluation, physical characteristic tests, and chemical analysis. The formulation was carried out using three formulas with varying ratios of rebon shrimp sprinkle and spinach leaves powder, namely F1 (70:30), F2 (80:20), and F3 (90:10). The selected formula, namely F3, is determined based on the results of all analyzes. One serving of product is 2.5 g or half a teaspoon, contains 8 kcal of energi, 1.4 g protein, 0.1 g fat, 0.3 g carbohydrates, 1.18 mg iron, 119.96 mg calcium, and 0.68 mcg of folic acid and can meet 0.4% of energi, 2.2% protein, 0.2% fat, 0.1% carbohydrates, 5.5% iron requirements, 11.7% calcium requirements, and 0.2% folic acid requirements of adult. The selected formula has the potential to fulfill the claim of being a food high in protein, iron, and calcium. The raw material cost of the selected formula is Rp600.00 per serving size.
Keyword: anemia, iron, powder, rebon shrimp, spinach leaves

Judul: Sistem Pengklasifikasian Entitas pada Pesan Twitter Menggunakan Ekspresi Regular dan Naïve Bayes
Abstrak: The widespread use of social networks like Twitter encourages some institutions to find out the entities that are discussed and the sentiment toward the entities. This research aims to build a system that can extract entities in tweets and classify the sentiment from the tweets. Entity extraction process is done using regular expressions. Writing regular expressions can capture the diverse entities. Sentiment classification is performed using naïve Bayes classification with Multinomial and Bernoulli models. Sentiment in this research consists of three classes, namely positive, negative, and neutral. Before entering the classification, tweets are normalized by replacing the non-standard words with the standard ones. The test results show that regular expression is quite effective for the entity extraction process. As for the results of the classification, naïve Bayes method produces high accuracy (96.75% for Multinomial and 96.33% for Bernoulli). However, the accuracy obtained depends on the neutral class which amounts to 97.88% for Multinomial and 99.95% for Bernoulli, while the positive class are 85.66% and 33.13% and negative class are 33.67% and 0%.
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