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All Journal JOURNAL ONLINE OF PHYSICS Jurnal Pendidikan Fisika dan Sains (JPFS)
Siswoyo Siswoyo
Jurusan Fisika, Fakultas Teknik, Universitas Bangka Belitung
Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Energy Physics

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Fabrikasi Perancah Berpori Hidroksiapatit dari Tulang Ikan Tenggiri dengan Alginat Sebagai Binder Alami: Sebuah Kajian Naratif Siswoyo Siswoyo; Kumalasari Kumalasari; Sari Wulan; Fitri Afriani
Jurnal Pendidikan Fisika dan Sains (JPFS) Vol. 3 No. 2 (2020): September
Publisher : Pendidikan Fisika, FKIP, Universitas Nahdlatul Ulama Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (350.055 KB) | DOI: 10.52188/jpfs.v3i2.82

Abstract

Porous scaffolding is an alternative solution developed to assist the bone therapy process. Hydroxyapatite (HAp) is a widely developed material into porous scaffolding because it has good biocompatibility. As a maritime country, Indonesia has high fisheries potential. One potential maritime product waste that could be synthesized into HAp is mackerel bone because it contains high amounts of CaO. This narrative describes a potential method for HAp synthesis from mackerel fish bones and a fabrication method that can be applied to a porous scaffold. Alginate is a natural ingredient from brown algae, which can be used as a porogen to synthesize porous HAp. Because it comes from maritime-based natural materials, algae are relatively safe and easy to produce in Indonesia. It is hoped that from this study, a more comprehensive picture can be obtained related to the development of HAp-based porous scaffolding from mackerel fish bones so that it can be considered for further development.
PEMANFAATAN EKSTRAK UBI UNGU SEBAGAI INDIKATOR LABEL DALAM PEMANTAUAN KESEGARAN UDANG MENGUNAKAN NEURAL NETWORK Siswoyo Siswoyo; Anisah Mega Andini; Dea Amelia; Aisyah Deri Ayu Tungga Safitri; Yuant Tiandho
JOURNAL ONLINE OF PHYSICS Vol. 7 No. 1 (2021): JOP (Journal Online of Physics) Vol 7 No 1
Publisher : Prodi Fisika FST UNJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jop.v7i1.14500

Abstract

The main weakness in shrimp marketing is the perishable food nature of shrimp. Generally, people identify the freshness of shrimp by direct observation. However, it will be difficult to detect the freshness of shrimp if it is marketed in a closed container. In this study, a label indicator of purple sweet potato will be made to detect the freshness of shrimp. The increase in the efficiency of indicator readings is carried out using a neural network algorithm. The results of the sensitivity test showed that the label indicator of purple sweet potato extract was sensitive to the presence of ammonia.Through a comparison between the storage time of shrimp and the organoleptic quality of shrimp, it is known that the quality of shrimp is divided into four classes, namely: (i) "Very fresh" marked with a solid red color (ii) "Fresh marked with a deep blue color (iii) "not fresh marked with a dark red color. gray and (iv) “very unrefreshing marked with a faded brown color. Through label indicator image classification using a neural network algorithm, from 73 training data obtained an accuracy rate of 95.89% and a precision of 92%.
Co-Authors Aisyah Deri Ayu Tungga Safitri Anisah Mega Andini Dea Amelia Fitri Afriani Kumalasari Kumalasari Sari Wulan Yuant Tiandho