Jurnal SINTA 2
Deteksi Kesegaran Ikan Tongkol (Euthynnus Affinis) secara Otomatis Berdasarkan Citra Mata Menggunakan Binary Similarity
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 7 No. 5 (2020) · pp. 879–886
- ISSN
- 2528-6579, 2355-7699
- Published
- 2020-10-08
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- id
Abstract
Ikan tongkol (Euthynnus Affinis) adalah salah satu ikan yang paling banyak diminati di Indonesia karena kandungan proteinnya hampir setara ikan tuna, namun dengan harga relatif lebih murah. Ikan termasuk komoditi pangan yang mudah rusak tanpa adanya penanganan khusus ketika ikan ditangkap. Padahal, mutu dan nilai jual ikan sangat tergantung dari parameter kesegaran ikan itu sendiri. Penelitian ini mengembangkan metode deteksi kesegaran ikan tongkol menggunakan fitur berupa citra mata ikan. Mata ikan dapat digunakan untuk mengetahui tingkat kesegarannya. Ikan segar memiliki pupil bulat berwarna hitam yang utuh dan jernih di tengahnya. Hal tersebut kemudian dijadikan knowledge-based dari proses deteksi kesegaran ikan. Sebelum dilakukan proses deteksi, dilakukan proses pre-processing untuk mendapatkan gambar kepala ikan secara otomatis. Selanjutnya dilakukan perhitungan similarity antara citra biner kepala ikan dengan 2 buah template, yakni Template-Mata untuk mendeteksi mata dan Template-Tengah untuk mendeteksi bulat hitam di tengah mata. Sebanyak 30 citra mata ikan dengan kriteria segar dan tidak segar digunakan sebagai data pengujian. Dari pengujian, kedua template tersebut mampu membedakan ciri morfologis dari mata ikan yang segar dengan tepat.AbstractTongkol fish (Euthynnus Affinis) is one of the most popular fish in Indonesia because it has more protein than tuna, but with a relatively cheaper price. Fish is a perishable food commodities if it is caught without any special handling. In fact, the quality and value of fish selling depends on the parameters of the freshness of the fish itself. This study developed a method for detecting freshness of tongkol fish using features that is extracted from the image of a fish's eye. Fish eye can be used to determine the level of freshness. Fresh fish have whole round and clear black pupils in the middle. This is then made into knowledge-base on the process of detecting the freshness. First, this fully automatic detection performed a pre-processing process to obtain automatic fish head images. It was then compared with two templates, which are eye-template and middle-template. If the fish head image has similarity below certain threshold then it is classified as fresh fish, or else it is non-fresh fish. A total of 30 images of fish with fresh and non-fresh criteria were used as test data. From the test, the two templates can classify the morphological characteristics of fresh fish eyes precisely.
Collaboration network of the authors
32 authors · 106 co-authorship links · 15 across different organisations
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Politeknik Negeri Malang
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Rizal Maulana | University of Brawijaya | 7 |
| Barlian Henryranu Prasetio | University of Brawijaya | 4 |
| Fitri Utaminingrum | University of Brawijaya | 4 |
| Randy Cahya Wihandika | University of Brawijaya | 4 |
| Muhammad Ali Fauzi | University of Brawijaya | 4 |
| Agung Setia Budi | University of Brawijaya | 2 |
| Eko Setiawan | University of Brawijaya | 2 |
| Edita Rosana Widasari | University of Brawijaya | 2 |
| Eko Setiawan | University of Brawijaya | 2 |
| Gembong Edhi Setyawan | University of Brawijaya | 1 |
| Benny Adiwijaya | University of Brawijaya | 1 |
| Widhy Hayuhardhika Nugraha Putra | University of Brawijaya | 1 |
| Indrazno Siradjuddin | Politeknik Negeri Malang | 1 |
| Ferdian Ronilaya | Politeknik Negeri Malang | 1 |
| Adhitya Bhawiyuga | University of Brawijaya | 1 |
| Budi Eko Prasetyo | Politeknik Negeri Malang | 1 |
| Sigi Syah Wibowo | Politeknik Negeri Malang | 1 |
| Supriatna Adhisuwignjo | Politeknik Negeri Malang | 1 |
| Septiyo Budi Perkasa | University of Brawijaya | 1 |
| Imam Cholissodin | University of Brawijaya | 1 |
| Dwi Ady Firmanda | University of Brawijaya | 1 |
| Ibrahim Aji | University of Brawijaya | 1 |
| Edy Rahman | University of Brawijaya | 1 |
| Syazwandy Harahap | University of Brawijaya | 1 |
| Fernando Septino | University of Brawijaya | 1 |
| Fahmi Erza | University of Brawijaya | 1 |
| Jevandika | University of Brawijaya | 1 |
| Brylliano Maza Putra | University of Brawijaya | 1 |
| Rakhmadhany Primananda | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.