THE USE OF A MAGNETIC SENSOR TO DETECT LOBSTER (Panulirus spp.) CATCHES ON THE LABORATORY SCALE

Andri Wahyudi; Maman Hermawan; Heri Triyono

doi:10.15578/chanos.v21i2.13406

THE USE OF A MAGNETIC SENSOR TO DETECT LOBSTER (Panulirus spp.) CATCHES ON THE LABORATORY SCALE

Andri Wahyudi, Maman Hermawan, Heri Triyono

Abstract

Problems in operating trap fish tool are that fishermen do not know the actual condition of the traps. Thus, it causes the effectiveness of time and number of catches to be not optimal. Based on the conditions and problems above, the writer concluded that an innovation in the operation of the trap to design a magnetic sensor-based system/tool to detect lobster catches that can be accessed via smartphone is required. The aim of this study is to design and observe the performance of using a magnetic sensor to detect lobsters' (Panulirus spp.) movements on a laboratory scale (in the aquarium). Data analysis in this study used the Confusion Matrix method, where this method divides the test results into 4 common conditions: TP (True Positive), TN (True Negative), FP (False Positive), and FN (False Negative). From the 4 conditions, Recall, Specificity, Precision, Accuracy, and F1 Score can be calculated. From 16 tests with the 16 lobsters of 60-190 grams/individual, it obtained conditions of TP of 25 times, TN of 109 times, FP of 11 times, and FN of 15 times. From the four conditions, it was obtained a Recall value of 0.625 or 62.50%, Specificity of 0.9083 or 90.83%, Precision of 0.6944 or 69.44%, Accuracy of 0.8375 or 83.75%, and F1 Score of 0.6579 or 65.79%. Based on the observations and test results of the actual detection and application system in this study, performance reference for using magnetic sensors was by using Accuracy with a score of 83.75%.

Keywords

lobster trap; internet of things (IoT); lobster; magnetic sensor.

Full Text:

PDF

References

Arafat. (2016). Sistem Pengamanan Pintu Rumah Berbasis Internet of Things (IoT) Dengan ESP8266. Technologia, 7(4), 639. https://doi.org/10.1126/science.195.4279.639

Ardiyanto, Y. (2016). Implementasi Metrik Keluaran Unjuk Kerja Network Intrusion Detection System. Semesta Teknika, 19(2), 113–118.

Arthana, R. (2019). Mengenal Accuracy, Precision, Recall dan Specificity serta yang diprioritaskan dalam Machine Learning. Rey1024.Medium.Com.

Azhari, M., Situmorang, Z., & Rosnelly, R. (2021). Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes. Jurnal Media Informatika Budidarma, 5(2), 640. https://doi.org/10.30865/mib.v5i2.2937

Bakhtiar, E., Boesono, H., & Sardiyanto. (2014). Pengaruh Perbedaan Waktu dan Umpan Penangkapan Lobster (Panulirus sp) dengan Alat Tangkap Krendet (Trap Net) di Perairan Watukarung Kabupaten Pacitan. Journal of Fisheries Resources Utilization Management and Technology, 3(3), 168–175.

Chicco, D., & Jurman, G. (2020). The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC Genomics, 21(1), 1–13. https://doi.org/10.1186/s12864-019-6413-7

Cobb, J. S. (1971). The Shelter Related Behaviour of The Lobster Homarus americanus. Ecological Society of America, 52(1), 108–115. https://doi.org/10.1038/news050808-1

Cooper, R. A., & Uzmann, J. R. (1980). The Biology and Management of Lobsters: Ecology and Management. Academic Press, Inc. New York. https://books.google.co.id/books?hl=id&lr=&id=55nZVzwAnPIC&oi=fnd&pg=PA97&ots=N1pmQSQyMG&sig=4K65AasfqHIMkT1rZ4mNsAsnUkQ&redir_esc=y#v=onepage&q&f=false

Eno, N. C., Macdonald, D. S., Jim, A. M., Amos, S. C., Chapman, C. J., Robin, A., Bunker, F. S. P. D., Munro, C., St, F. P. D., & E, C. (2001). Effects of Crustacean Traps on Benthic Fauna. ICES Journal Marine Science, 58, 11–20. https://doi.org/10.1006/jmsc.2000.0984

FAO. (1995). Code of Conduct for Responsible Fisheries. In Food and Agriculture Organization Of The United Nations: Roma. https://doi.org/10.5040/9781509955572.0062

Fibrianda, M. F., & Bhawiyuga, A. (2018). Analisis Perbandingan Akurasi Deteksi Serangan pada Jaringan Komputer dengan Metode Naive Bayes dan Support Vector Machine (SVM). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(9), 3112–3123. http://j-ptiik.ub.ac.id

Ghoneim, S. (2019). Accuracy, Recall, Precision, F-Score & Specificity, which to optimize on? Towards Data Science. https://towardsdatascience.com/accuracy-recall-precision-f-score-specificity-which-to-optimize-on-867d3f11124

Groeneveld, J. C. (2000). Stock Assessment, Ecology and Economics as Criteria for Choosing between Trap and Trawl Fisheries for Spiny Lobster Palinurus delagoae. Fisheries Research, 48(2), 141–155. https://doi.org/10.1016/S0165-7836(00)00178-8

Hakim, R. S., Winarno, I., & Yuwono, W. (2012). Verifikasi Alert Berdasarkan Klasifikasi Serangan Pada Deteksi Intrusi Kolaboratif. 1–13.

Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques. In Proceedings - 2013 International Conference on Machine Intelligence Research and Advancement, ICMIRA 2013 (Third Edit). https://doi.org/10.1109/ICMIRA.2013.45

Jury, S. H. (1999). Behavioral and Physiological Responses of The Lobster, Homarus americanus, to Temperature: A New Synthesis. University of New Hampshire. https://scholars.unh.edu/dissertation/2072/

Jury, S. H., Howell, H., O’Grady, D. F., & Watson III, W. H. (2001). Lobster Trap Video : In Situ Video Surveillance of The Behaviour of Homarus americanus In and Around Traps. Marine Freshwater Research, 52, 1125–1132.

Kadafi, M., Widaningroem, R., & Soeparno, S. (2006). Aspek Biologi dan Potensi Lestari Sumberdaya Lobster (Panulirus spp.) di Perairan Pantai Kecamatan Ayah Kabupaten Kebumen. Jurnal Perikanan Universitas Gadjah Mada, 8(1), 108. https://doi.org/10.22146/jfs.171

Karnofsky, E. B., & Price, H. J. (1989). Behavioral Response of The Lobster Homarus americanus to Traps. Can. J. Fish. Aquat. Sci., 46(Duggan 1985), 1625-1632.

Khikmawati, L. T., Boesono, H., Studi, P., Sumberdaya, P., Perikanan, J., Diponegoro, U., Dinding, K., Kerucut, B., & Perendaman, L. (2015). Pengaruh Perbedaan Lama Pengoperasian dan Kemiringan Dinding Bubu Terhadap Hasil Tangkapan Lobster (Panulirus sp.) di Perairan Argopeni Kabupaten Kebumen. Journal of Fisheries Resources Utilazation Management and Technology, 4(2), 83–92.

Kuruppu, S., & Zou, Y. (2021). Static Position Sensor Bias Fault Diagnosis in Permanent Magnet Synchronous Machines via Current Estimation. IEEE/ASME Transactions on Mechatronics, 26(2), 888–896.

Kusuma, R. D., Asriyanto, & Sardiyatmo. (2012). Pengaruh Kedalaman dan Umpan Berbeda Terhadap Hasil Tangkapan Lobster (Panulirus sp)dengan Jaring Lobster (Bottom Gill Net Monofilament) di Perairan Argopeni Kabupaten Kebumen. Journal of Fisheries Resources Utilazation Management and Technology, 1(1), 11–21.

Lawton, P. (1987). Diel Activity and Foraging Behaviour of Juvenile American Lobsters, Homarus americanus. Canadian Journal of Fisheries and Aquatic Sciences, 44, 1195–1205.

Lawton, P., & Lavalli, K. L. (1995). Postlarval, Juvenile, Adolescent, and Adult Ecology. Biology of the Lobster, 47–88. https://doi.org/10.1016/b978-012247570-2/50026-8

Miswar, E., Puspito, G., Yusfiandayani, R., & Zulkarnain. (2016). Rekonstruksi Pintu Masuk Bubu Lipat Lobster dan Pengaruh Penggunaan Tutupan Terhadap Hasil Tangkapan. Jurnal Teknologi Perikanan Dan Kelautan, 7(1), 99–106.

Nursahid. (2022). Mengenal Accuracy, Precision, Recall dan Specificity serta yang diprioritaskan dalam Machine Learning. Nursahid.Com. https://www.nursahid.com/mengenal-accuracy-precision-recall-dan-specificity-serta-yang-diprioritaskan-dalam-machine-learning

Prariska, D., Supriyono, E., Soelistyowati, D. T., Puteri, R. E., Sari, S. R., Sa’adah, R., & Guttifera. (2020). Kelangsungan Hidup Lobster Pasir (Panulirus homarus) yang Dipelihara pada Sistem Resirkulasi. Clarias : Jurnal Perikanan Air Tawar, 1(1), 1–7. https://doi.org/10.56869/clarias.v1i1.52

Rafsanjani, M. S., Suryani, V., & Pahlevi, R. R. (2022). Deteksi Serangan Botnet pada Jaringan Internet of Things Menggunakan Algoritma Random Forest (RF). E-Proceeding of Engineering, 9(3), 1862–1871.

Rahman, F., Asriyanto, & Pramonowibowo. (2015). Pengaruh Perbedaan Jenis Umpan dan Lama Perendaman Bubu terhadap Hasil Tangkapan Lobster (Panulirus sp.) di Perairan Argopeni Kabupaten Kebumen. Journal of Fisheries Resources Utilization Management and Technology, 4(3), 54–61. https://ejournal3.undip.ac.id/index.php/jfrumt/article/viewFile/18807/17891

Reynolds, W. W., & Casterlin, M. E. (1979). Behavioral Thermoregulation and Activity in Homarus americanus. Comparative Biochemistry and Physiology -- Part A: Physiology, 64(1), 25–28. https://doi.org/10.1016/0300-9629(79)90424-9

Rizky, M. F., Anna, Z., Rizal, A., & Handaka Suryana, A. A. (2018). Sosial Ekonomi dan Lingkungan Perikanan Bubu di Desa Karongsong Kabupaten Indramayu, Jawa Barat. Jurnal Kebijakan Sosial Ekonomi Kelautan Dan Perikanan, 8(2). https://doi.org/10.15578/jksekp.v8i2.7213

Salah, K., & Qahtan, A. (2009). Improving Snort Performance Under Linux. IET Communications, 3(12).

Septiansyah, A., Yuliawati, A., & Santoso, I. (2023). Analisis Sentimen Terhadap Layanan Internet di Indonesia Menggunakan Metode K-Nearest Neighbor. Ikraith-Informatika, 7(2), 32–41. https://doi.org/10.35957/mdp-sc.v2i1.4554

Setiawan, I. (2009). Buku Ajar Sensor dan Tranduser. In Semarang, Universitas Diponegoro.

Setiawan, S. (2020). Membicarakan Precision, Recall, dan F1-Score. Stevkarta.Medium.Com.

Sipayung, E. P., Bustari, H., Syofyan, I., Perikanan, F., Ilmu, D., Riau, U., Perikanan, F., Ilmu, D., & Riau, U. (2016). Uji Coba Penggunaan Berbagai Macam Bahan Bubu Untuk Penangkapan Lobster di Danau Maninjau.

Sokolova, M., Japkowicz, N., & Szpakowicz, S. (2006). Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation. AI 2006: Advances in Artificial Intelligence, c, 1015–1021. http://dx.doi.org/10.1007/11941439_114

Suhana. (2022). Tingkat Pemanfaatan Ikan di WPPNRI Dominan fully dan over exploited. Data Suhana Literasi Ekonomi Kelautan. https://suhana.web.id/2022/04/08/tingkat-pemanfaatan-ikan-di-wppnri-dominan-fully-dan-over-exploited/?subscribe=pending#subscribe-blog-blog_subscription-2

Tamarol, J., Luasunaung, A., & Budiman, J. (2012). Dampak Perikanan Tangkap Terhadap Sumberdaya Ikan dan Habitatnya di Perairan Pantai Tabukan Tengah Kepulauan Sangihe. Jurnal Perikanan Dan Kelautan Tropis, VIII(1), 12–16.

Widharma, I. G. S. (2020). Sensor Magnet pada Sistem Instrumentasi. Politeknik Negeri Bali, December.

Yudhono, M. S. R., Wibisono, W., & Ciptaningtyas, H. T. (2015). Rancang Bangun Sistem Fall Detection dengan Analisa Percepatan Sudut Rotasi (Quaternion) secara Real Time Menggunakan Mikrokontroler Arduino. Jurnal Teknik ITS, 4(1), 1–6.

Zulkarnain, Z., Baskoro, M., Martasuganda, S., & Monintja, D. (2011a). Efektivitas Bubu Lipat Modifikasi Dan Penggunaan Umpan Cacing Tanah (Lumbricus rubellus) pada Penangkapan Spiny Lobster (Panulirus Spp.) di Perairan Pesisir Timur Teluk Palabuhanratu Jawa Barat. Buletin PSP, 19(3), 242698.

Zulkarnain, Z., Baskoro, M., Martasuganda, S., & Monintja, D. (2011b). Pengembangan Desain Bubu Lobster yang Efektif. Buletin PSP, 19(2), 242605.

Zulma, G. D. M., Angelika, & Chamidah, N. (2021). Perbandingan Metode Klasifikasi Naive Bayes, Decision Tree Dan K-Nearest Neighbor Pada Data Log Firewall. Seminar Nasional Mahasiswa Ilmu Komputer Dan Aplikasinya (SENAMIKA) Jakarta-Indonesia, April, 679–688.

DOI: http://dx.doi.org/10.15578/chanos.v21i2.13406