Effect of Temperature, Time and Amount of Alkaline Treated Cotton Seaweed (ATS) Products Dried in a Dryer Oven on Product Quality

Eucheuma cottonii seaweed contains carrageenan, which is used as an ingredient for the food and beverage industry. This must be processed first by an alkaline process and then dried to become chips known as alkaline treated cotton chips (ATC) products. The process of drying seaweed was done using an oven dryer using heat energy that can be adjusted to the drying time, temperature and number of products so that the quality of the dried products of seaweed products that have been processed into Alkaline Treated Cotton Seaweed (ATS) to be used as an advanced product becomes ATC (Alkali Treated Cotton Chips). The results of this study aim to find out the optimal value of temperature, drying time and the amount of ATS to get output from ATC in accordance with SNI 8170: 2015 standard and received by the customer. Based on the results of the study, it was found that the minimum significant drying process for moisture content was 12.10% at level 2, 1 kg weight, level 2 temperature 70 oC with level 3 drying time 400 minutes. Whereas the maximum gel strength is 910 gram / cm2 at level 1, weight 0.5 kg, level 2 temperature 70 oC with level 2 drying time 320 minutes

Identifikasi Jenis dan Mutu Teh Menggunakan Pengolahan Citra Digital dengan Metode Jaringan Syaraf Tiruan

Teh merupakan hasil pucuk daun muda tanaman Camelia sinensis dan menjadi salah satu produk ekspor terbesar. Salah satu kendala yang dihadapi konsumen dalam memilih teh berkualitas baik adalah minimnya pengetahuan konsumen terhadap jenis dan mutu teh, sehingga menyebabkan perbedaan penentuan jenis dan mutu teh. Penelitian untuk mengidentifikasi jenis dan mutu teh dari 3 jenis teh yaitu teh hitam, teh hijau, dan teh putih perlu dilakukan. Tujuan penelitian ini adalah merancang aplikasi sistem pengolahan citra digital untuk mengidentifikasi jenis dan mutu teh serta menentukan hasil pengenalan terbaik berdasarkan akurasi yang diperoleh. Penelitian ini menerapkan metode pengolahan citra digital dengan teknik Learning Vector Quantization yang menggunakan 6 parameter warna yaitu R, G, B, H, S, dan I sebagai neuron input dan 13 mutu dari 3 jenis teh sebagai neuron output. Penelitian menggunakan 403 citra dengan perbandingan training dan testing sebesar 80:20. Akurasi training diperoleh sebesar 62,7%. Prediksi menggunakan 26 sampel citra teh berbeda menunjukkan tingkat akurasi sebesar 42,31%. Kata Kunci: jaringan syaraf tiruan, learning vector quantization (LVQ), te

Fostering empowerment and building capacities of rural women through community-based agroindustry: A case study in Donowarih Village, Indonesia

Donowarih village, located in Malang Regency, East Java, Indonesia, is closed to the Universitas Brawijaya’s Educational Forest (known as UB Forest). The village has various potential local commodities such as orange fruits and batik. During harvesting season, the price of orange fruits declined, and inadequate storage system has led to a rapid deterioration of orange fruits. Furthermore, various problems faced by the community, such as poverty and lack of knowledge/skills, are becoming the major challenges to be tackled. On the other hand, orange fruits and batik are potential to be diversified into high value-added products, which can be done through the introduction of post-harvesting technology and trainings for skills improvement. Furthermore, the Indonesian Government program of one village one product (OVOP) is becoming key drivers to any community engagement program in Indonesia

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality