Main Article Content

Abstract

Recipes are used as a reference in processing cooking ingredients to meet personal nutritional needs, considering the ingredients used to make food sold freely that is not necessarily guaranteed in nutritional quality and safe to consume, especially during the pandemic as it is today. So cooking itself becomes a better alternative for the community. With a large number of food recipe options available for various media, the role of a Decision Support System is needed by people who will get food recipe recommendations. Research related to recipe recommendations that have been done are using SAW only and some add experts as a source of knowledge to provide value on the variable time and complexity of cooking recipes. Therefore, in this study, a comparison between the research of recipe recommendations with SAW only and research that added a subsystem of knowledge management derived from experts to support the decision support system of food recipe recommendations was conducted by using correlation testing. The results is there is a strong correlation between knowledge based SAW and user preference to the value of 0.9774. The result is better than SAW only and user preference with the value of 0.7262.

Article Details

How to Cite
Dewi, R. K., Brata , K. C. ., Afirianto, T., & Candra , E. N. . (2021). Comparison between SAW and Knowledge based SAW in Recipe Recommendation System. Journal of Information Technology and Computer Science, 6(3), 273–280. https://doi.org/10.25126/jitecs.202163363

References

  1. Turban, Efraim. Decision support and expert systems: management support systems. Prentice Hall PTR, 1993.
  2. Setyahadi, Pradiptya. "Rancang Bangun Aplikasi Resep Masakan Berbasis Mobile Web Dengan Metode Case-Based Reasoning." Yogyakarta: Universitas Islam Negeri Sunan Kalijaga (2014).
  3. Salsabella, Amira. "Sistem Pendukung Keputusan Penentuan Resep Masakan Berdasarkan Ketersediaan Bahan Makanan Menggunakan Metode Simple Additive Weighting (SAW) Berbasis Web." Jurnal Sistem dan Teknologi Informasi (JUSTIN)2.3 (2014): 110-117.
  4. Santoso, Tino Aprika. “Aplikasi Pencarian Resep Masakan Berbasis Mobile Web Berdasarkan Ketersediaan Bahan dengan Metode Simple Additive Weighting.” Diss. UII, 2016.
  5. Nabila; Dewi, Ratih Kartika; Brata, Komang Candra. ”SPK Pemilihan Resep Masakan dan Fitur Berbasis Lokasi”.JPTIIK. 2018.
  6. Dewi, Ratih Kartika, Komang Candra Brata, and Nabila Nabila. "Konsistensi Ranking pada Sistem Rekomendasi Resep Masakan dengan Simple Additive Weighting." Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI) 8.3 (2019): 235-240.
  7. The Fatsecret website. (Online), https://www.fatsecret.co.id/.
  8. Yoon, K. Paul, and Ching-Lai Hwang. Multiple attribute decision making: an introduction. Vol. 104. Sage publications, 1995.
  9. Sahir, Syafrida Hafni, R. Rosmawati, and Kresna Minan. "Simple additive weighting method to determining employee salary increase rate." Int. J. Sci. Res. Sci. Technol 3.8 (2017): 42-48.
  10. Adela, Hana, et al. "Selection of dancer member using simple additive weighting." International Journal of Engineering & Technology 7.3 (2018): 1096-1107.
  11. Nurmalini, N., and Robbi Rahim. "Study Approach of Simple Additive Weighting For Decision Support System." Int. J. Sci. Res. Sci. Technol 3.3 (2017): 541-544.
  12. Setiawan, Nashrudin, et al. "Simple additive weighting as decision support system for determining employees salary." Int. J. Eng. Technol 7.2.14 (2018): 309-313.
  13. Pratiwi, Dyah, Juliana Putri Lestari, and D. Agushita. "Decision Support System to Majoring High School Student Using Simple Additive Weighting Method." International Journal of Computer Trends and Technology 10.3 (2014): 153-159.
  14. Aminudin, Nur, et al. "Higher education selection using simple additive weighting." International Journal of Engineering and Technology (UAE) 7.2.27 (2018): 211-217.John R. Smith and Shih-Fu Chang. 1997. VisualSEEk: a fully automated content-based image query system. In Proceedings of the fourth ACM international conference on Multimedia (MULTIMEDIA ’96). Association for Computing Machinery, New York, NY, USA, 87–98. https://doi.org/10.1145/244130.244151