Sistem Klasifikasi Kualitas Bunga Cengkeh Kering berbasis Website menggunakan Logika Fuzzy Metode Tsukamoto

Authors

DOI:

https://doi.org/10.29408/edumatic.v8i2.27983

Keywords:

clove classification, clove tester, clove quality, fuzzy logic, tsukamoto method

Abstract

Indonesian cloves have strong competitiveness in the main market due to their economic benefits, such as being raw materials for kretek cigarettes, spices, and the perfume industry. However, high global competition demands improvements in product quality and consistency. The manual and subjective sorting of cloves often leads to inaccuracies and inconsistencies in quality, which can be detrimental to farmers, especially in smallholdings. The objective of our research is to develop a web-based system for classifying the quality of dried clove flowers using the Tsukamoto fuzzy logic method. The stages of system development using the waterfall method include system requirements analysis, architecture and interface design, website implementation with the Tsukamoto fuzzy method, and testing. The Tsukamoto fuzzy logic implementation method was chosen due to its ability to process uncertain data and produce consistent output. Our findings successfully produced a web-based system called 'Clove Tester', with an average sensitivity of 45.99% from sensitivity testing based on modifications to the membership function of condition and quality variables. These results indicate that the system has a good adaptability to variations in input data, making it suitable for application to data with a high level of uncertainty or ambiguity in this research.

References

Al Hafidz, A. F., Dharmawan, D. P., Anggraeni, S. D., & Sari, A. P. (2023). Perbandingan Penerapan Logika Fuzzy Metode Mamdani dan Metode Tsukamoto pada Sistem Diagnosa Penyakit Tanaman Padi. Prosiding Seminar Nasional Informatika Bela Negara, 3, 28-36.

Al Rivan, M. E., Octavia, A., & Wijaya, I. (2021). Desain Model Fuzzy-tsukamoto Untuk Penentuan Kualitas Buah Pepaya California (Carica Papaya L.) Berdasarkan Bentuk Fisik. Jurnal Saintekom: Sains, Teknologi, Komputer dan Manajemen, 11(1), 11-21. https://doi.org/10.33020/saintekom.v11i1.155

Chalik, F. A., & Al Maki, W. F. (2021). Classification of dried clove flower quality using convolutional neural network. International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA) (pp. 40-45). IEEE. https://doi.org/10.1109/DATABIA53375.2021.9650199

Dewi, C., Achsanulnashir, A., & Widiyono, W. (2021). Analisis Daya Saing Ekspor Cengkeh Indonesia Di Pasar Internasional. JAMBIS: Jurnal Administrasi Bisnis, 1(1), 24-30. https://doi.org/10.20527/frontbiz.v5i3.5925

Fatony, Y. R., & Nugroho, K. (2023). Penentuan Pemilihan Varitas Unggul Pada Tanaman Padi Menggunakan Logika Fuzzy Tsukamoto Berbasis Web. Elkom: Jurnal Elektronika dan Komputer, 16(2), 406-415.

Heriyanti, F., & Ishak, A. (2020). Design of logistics information system in the finished product warehouse with the waterfall method: review literature. IOP Conference Series: Materials Science and Engineering 801(1), 012100. IOP Publishing. https://doi.org/10.1088/1757-899X/801/1/012100

Hidayah, M., Fariyanti, A., & Anggraeni, L. (2022). Daya Saing Ekspor Cengkeh Indonesia. Jurnal Ekonomi Pertanian Dan Agribisnis, 6(3), 930-937. https://doi.org/10.21776/ub.jepa.2022.006.03.14

Lumbessy, A. S. (2023, July). Kajian Penyusunan Masterplant Pengembangan Hulu–Hilir Produk Turunan Cengkeh Varietas Afo Maluku Utara. Prosiding Seminar Nasional Pertanian, 6(1), 76-86.

Maryam, S., Bu'Ulolo, E., & Hatmi, E. (2021). Penerapan Metode Fuzzy Mamdani dan Fuzzy Tsukamoto Dalam Menentukan Harga Mobil Bekas. Journal of Informatics, Electrical and Electronics Engineering, 1(1), 10-14.

Prayogi, I. Y., & Hendrawan, Y. (2021). Image classification of different clove (Syzygium aromaticum) quality using deep learning method with convolutional neural network algorithm. Conference Series: Earth and Environmental Science, 905(1), 012018. IOP Publishing. https://doi.org/10.1088/1755-1315/905/1/012018

Mellinia, S. P., & Wijayanti, I. K. E. (2024). Analisis Daya Saing Ekspor Cengkeh Indonesia Di Pasar Internasional. Jurnal Ekonomi Pertanian dan Agribisnis, 8(3), 947-958.

Ramadhani, D. H., Srikandi, R., Ikhwan, M., & Saputra, R. A. (2024). Penerapan Logika Fuzzy Dalam Klasifikasi Status Gizi Balita Di Puskesmas Pondidaha Menggunakan Metode Fuzzy Tsukamoto. Jurnal Informatika Dan Teknik Elektro Terapan, 12(2), 903-911. https://doi.org/10.23960/jitet.v12i2.4017

Saputra, D., Lestanti, S., & Rahmat, M. F. (2024). Implementasi Logika Fuzzy Pada Rancang Bangun Sistem Informasi Parkir Berbasis Web Di Universitas Islam Balitar. Jurnal Informatika Dan Teknik Elektro Terapan, 12(3), 3058-3065. https://doi.org/10.23960/jitet.v12i3.5087

Sinuhaji, N., Ginting Raheliya Br, Benar, & Lestiana Cindy. (2022). Sistem Pendukung Keputusan Untuk Menentukan Kualitas Crude Palm Oil Sebagai Bahan Baku Minyak Goreng Menggunakan Matlab Dengan Metode Fuzzy Logic Tsukamoto. Jurnal Informatika Dan Perancangan Sistem (Jips), 4(2), 1-6.

Talib, S., Sudin, S., & Suratin, M. D. (2024). Penerapan Metode Support Vector Machine (Svm) Pada Klasifikasi Jenis Cengkeh Berdasarkan Fitur Tekstur Daun. PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer, 11(1), 26-34. https://doi.org/10.30656/prosisko.v11i1.7911

Tempola, F., Wardoyo, R., Musdholifah, A., Rosihan, & Sumaryanti, L. (2024). Classification Of Clove Types Using Convolution Neural Network Algorithm With Optimizing Hyperparamters. Bulletin Of Electrical Engineering and Informatics, 13(1), 444–452. https://doi.org/10.11591/eei.v13i1.5533

Vicidomini, C., Roviello, V., & Roviello, G. N. (2021). Molecular basis of the therapeutical potential of clove (Syzygium aromaticum L.) and clues to its anti-COVID-19 utility. Molecules, 26(7), 1880. https://doi.org/10.3390/molecules26071880

Wijayanti, I. K. E., Rachmanto, A., Soedirman, J., Drsoeparno, J., & Jawa Tengah, P. (2023). Daya Saing Dan Faktor-Faktor Yang Mempengaruhi Ekspor Cengkeh Indonesia Competitiveness and Factors That Affecting Exports of Indonesian Clove. Jurnal Dinamika Sosial Ekonomi, 24(2), 126–140. https://doi.org/10.31315/jdse.v24i2.10021

Yaspin, Y. N., Widodo, D. W., & SETIAWAN, A. B. (2020). Klasifikasi Kualitas Bunga Cengkeh untuk Meningkatkan Mutu Dengan Pemanfaatan Ciri Gray Level Co-Occurence Matrix (GLCM) (Doctoral dissertation, Universitas Nusantara PGRI Kediri).

Zamzani, Z. M., Nurdiansyah N.A, M. R., & Yana, B. Y. (2023). Deteksi Stres Manusia Melalui Analisis Tidur Dengan Metode Fuzzy. Technovatar Jurnal Teknologi, Industri, Dan Informasi, 1(1), 58–71. https://doi.org/10.61434/technovatar.v1i1.60

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Published

2024-12-19

How to Cite

Fadhila, A. F., & Avianto, D. (2024). Sistem Klasifikasi Kualitas Bunga Cengkeh Kering berbasis Website menggunakan Logika Fuzzy Metode Tsukamoto. Edumatic: Jurnal Pendidikan Informatika, 8(2), 704–713. https://doi.org/10.29408/edumatic.v8i2.27983