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All Journal Jurnal Pengolahan Hasil Perikanan Indonesia Indonesian Aquaculture Journal
Sedayu, Bakti Berlyanto
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology

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Optimasi formula nori like product dari Ulva spp., Gracilaria sp. dan gliserol menggunakan metode mixture design : Optimization of nori like product formulation from Ulva spp., Gracilaria sp., and glycerol using mixture design method Sihono, Sihono; Sinurat, Ellya; Fateha, Fateha; Supriyanto, Agus; Suryaningrum, Theresia Dwi; Nurhayati, Nurhayati; Fransiska, Dina; Utomo , Bagus Sediadi Bandol; Subaryono, Subaryono; Sedayu, Bakti Berlyanto; Waryanto, Waryanto; Nurjanah, Nurjanah; Ramadhan, Wahyu; Fadillah, Hafidz Maulana; Muzayyanah, Alief Laily
Jurnal Pengolahan Hasil Perikanan Indonesia Vol. 26 No. 3 (2023): Jurnal Pengolahan Hasil Perikanan Indonesia 26 (3)
Publisher : Department of Aquatic Product Technology IPB University in collaboration with Masyarakat Pengolahan Hasil Perikanan Indonesia (MPHPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17844/jphpi.v26i3.48337

Abstract

Nori merupakan produk olahan rumput laut Phorphyra spp. yang berbentuk lembaran kering dan memiliki cita rasa khas. Nori kaya akan protein dan disukai konsumen. Tingkat konsumsi nori di Indonesia yang tinggi berdampak pada nilai impor nori yang meningkat tiap tahunnya. Rumput laut Phorphyra spp. sebagai bahan baku nori hanya tumbuh di perairan sub tropis. Pengembangan nori dari rumput laut lokal Indonesia perlu dilakukan untuk mengurangi ketergantungan produk impor dan meningkatkan nilai tambah rumput laut local. Tujuan penelitian adalah untuk menentukan formula terbaik nori like product dari Ulva spp, Gracilaria sp., dan gliserol menggunakan metode mixture design berdasarkan mutu fisik dan sensori. Penelitian dilakukan dalam 4 tahap, yaitu pembuatan rancangan formulasi nori dengan Design Expert 13® dan penentuan respon, pembuatan nori, analisis respon yang ditentukan, dan optimasi formula yang direkomendasikan. Hasil penelitian menunjukkan bahwa pada respon sifat fisik, komposisi Ulva spp, Gracilaria sp., dan gliserol serta interaksi antar komponen tidak memengaruhi nilai ketebalan nori, namun secara signifikan memengaruhi nilai kuat tarik dan pemanjangan. Hasil respon terhadap nilai sensori, komposisi Ulva spp, Gracilaria sp., dan gliserol serta interaksi antar komponen tidak memengaruhi nilai warna, kenampakan, dan aroma, namun secara signifikan memengaruhi nilai tekstur dan rasa. Komposisi Ulva spp, Gracilaria sp., dan gliserol serta interaksi antar komponen tidak memengaruhi nilai warna kecerahan (L*), namun secara signifikan memengaruhi nilai redness (a*) dan yellowness (b*). Formula nori like product terbaik adalah Ulva spp 26,9%, Gracilaria sp. 4,9%, dan gliserol 2,2%.
IMAGE PROCESSING METHOD TO DETECT THE POSITION OF VANNAMEI SHRIMP IN MUDDY WATERS Waryanto, Waryanto; Setiawan, Joga Dharma; Arianto, Mochammad; Sedayu, Bakti Berlyanto; Hartanti, Ninik Umi; Suyono, Suyono; Dina, Karina Farkha; Alamsyah, Heru Kurniawan; Aziz, Hozin; Taukhid, Imam; Supriyanto, Supriyanto; Zulkarnain, Riza; Siregar, Zaenal Arifin
Indonesian Aquaculture Journal Vol 20, No 2 (2025): (December, 2025)
Publisher : Agency for Marine and Fisheries Extension and Human Resources

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/iaj.20.2.2025.145-156

Abstract

One way to help the feeding process vannamei shrimp in ponds that have cloudy surface using constructed with a size of 50 × 50 × 18 cm with a water height in the pond of 7 cm from bottom, where the data in the form of images was obtained from data collection 25 times using a camera is placed at a height of 52 cm above the water surface. The pond’s entire surface was captured with one click of the camera. The number of vannamei shrimp used in this study was 7. The method used for data processing is thresholding, in which the threshold value is generated using a histogram-based technique from the image data. This method is employed to distinguish shrimp from non-shrimp regions in the image. From this study, a vannamei shrimp detection technique was developed, producing results in the form of a script that distinguishes vannamei shrimp objects from non-vannamei shrimp. The detection accuracy achieved using the thresholding method in this study is 94.28%. The positions of the shrimp were produced in the form of coordinates as a step to success according to the objectives of this study, which were able to detect positions, in order to help facilitate the process of feeding in ponds. This detection technique could be developed for application on full-scale ponds, utilizing cameras mounted on drones as a tool for detecting vannamei shrimp positions in cloudy pond water. This technology may be adapted to allow targeted feeding of shrimp in ponds, thus maximizing food consumption and minimizing food wastage.
Co-Authors Agus Supriyanto Arianto, Mochammad Aziz, Hozin Dina, Karina Farkha Fadillah, Hafidz Maulana Fateha, Fateha Fransiska, Dina Heru Kurniawan Alamsyah Joga Dharma Setiawan Muzayyanah, Alief Laily N. Nurjanah Ninik Umi Hartanti Nurhayati Nurhayati Sihono Sihono Sinurat, Ellya Siregar, Zaenal Arifin Subaryono Subaryono, Subaryono Supriyanto Supriyanto Suryaningrum, Theresia Dwi Suyono Suyono Taukhid, Imam Utomo , Bagus Sediadi Bandol Wahyu Ramadhan Waryanto, Waryanto Zulkarnain, Riza