Penerapan Metode Mabac Dalam Menentukan Kopi Terlaris Berdasarkan Tingkat Harga Pada Perusahaan Kopi Kenangan

Aprizal Hidayat, Dodi Siregar, Divi Handoko

Abstract


Kopi Kenangan is a coffee beverage company founded in Indonesia in 2017 by Edward Tirtanata, James Prananto and Cynthia Chaerunnisa. Currently, Kopi Memories has opened as many as 230 outlets throughout Indonesia. Various menus have been served at Kopi Memories, especially at Kopi Memories, which is located in the city of Medan, so far there are 60 menus available. The number of menus that have been presented, sometimes people who just want to buy memories coffee products are still confused in choosing the best-selling memory coffee products in their coffee products, plus there is no system in determining the best-selling coffee for memories coffee. Departing from the problems above, the author is interested in making a decision support system in determining the best-selling coffee products based on price and sales levels. The decision support system itself is a system that is able to provide both problem-solving abilities and the ability to solve semi-structured problems. The decision system method used is the MABAC method which is a multi-criteria comparison method. This method was chosen because, service companies with other methods of multi-criteria decision making and this study resulted in the memory of Thai tea coffee products succeeded in producing the best products with a calculation value of 0.331616

 

Keywords: Mabac, Memories Coffee, Decision Support System


Full Text:

PDF

References


CNBN Indonesia, “No Title,” 2022. https://www.cnbcindonesia.com/market/20220715114238-17-355908/intip-sumber-kekayaan-sosok-pemilik-600-gerai-kopi-kenangan.

K. Umam, V. E. Sulastri, D. U. Sutiksno, and Mesran, “Perancangan Sistem Pendukung Keputusan Penentuan Prioritas Produk Unggulan Daerah Menggunakan Metode VIKOR,” J. Ris. Komput., vol. 5, no. 1, pp. 43–49, 2018.

D. A. Ramadandi, “Sistem Pendukung Keputusan Penilaian Matras Springbed Dengan Metode MABAC (Studi Kasus PT. Ocean Centra Furnindo),” Semin. Nas. Inform., vol. 6, no. 3, 2022, [Online]. Available: http://www.jurnal.kaputama.ac.id/index.php/SENATIKA/article/download/1008/696.

M. I. M. Al Abid and G. Abdurahman, “Implementasi Metode Multi Atrributive Borderapproximation Area Comparison (MABAC) untuk Penilaian Desa,” J. Univ. Muhammadiyah Jember, p. 1, 2021.

S. M. Sumarno and J. M. Harahap, “Sistem Pendukung Keputusan Dalam Menentukan Pemilihan Posisi Kepala Unit (Kanit) Ppa Dengan Metode Weight Product,” JUST IT J. Sist. Informasi, Teknol. Inf. dan Komput., vol. 11, no. 1, p. 37, 2020, doi: 10.24853/justit.11.1.37-44.

U. Rahardja, N. Lutfiani, and R. Rahmawati, “APTISI Student Perception to the News on The APTISI Website,” J. Ilm. SISFOTENIKA, vol. 8, no. 2, pp. 117–127, 2018.

E. B. Barus, “Sistem Pendukung Keputusan Pemilihan Best Employee Dengan Menerapkan Metode MABAC,” TIN Terap. Inform. Nusant., vol. 2, no. 9, pp. 551–557, 2022, doi: 10.47065/tin.v2i9.1028.




DOI: http://dx.doi.org/10.30829/algoritma.v7i1.15368

Refbacks

  • There are currently no refbacks.


Indexing:

    

 

 

Creative Commons License

Algoritma: Jurnal Ilmu Komputer dan Informatika

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.