Analisa Hasil Performansi Algoritma Apriori dan FP-Growth dalam Rekomendasi Kombinasi Menu
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Analisa Hasil Performansi Algoritma Apriori dan FP-Growth dalam Rekomendasi Kombinasi Menu |
| 2. | Creator | Author's name, affiliation, country | Maulana Hassan Sechuti; Universitas Pembangunan Nasional Veteran Jawa Timur, Indonesia; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Yisti Vita Via; Universitas Pembangunan Nasional Veteran Jawa Timur, Indonesia; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Hendra Maulana; Universitas Pembangunan Nasional Veteran Jawa Timur, Indonesia; Indonesia |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | |
| 4. | Description | Abstract | Currently, technological developments are increasingly rapid with the emergence of various technologies that make it easier for humans to do their activities, for example in the food business sector. However, the development of technology has not been maximally utilized by several food business, one of which is the Sidoarjo area ropi bakery which has problems managing its stock and has difficulty in determining menu combinations for promotional activities. This can be overcome by analyzing all transaction data at the Sidoarjo area ropi bakery. Analysis of transaction patterns is carried out to obtain menu combinations. This analysis can be done using data mining association algorithms. This research focuses more on comparing the Apriori and FP-Growth data mining association algorithms when the two algorithms are implemented into a web-based information system. In this study, a comparison was made by analyzing 637 transaction data. In analyzing 637 transaction data, the minimum support value variation used is less then equal 10% with a minimum confidence value of 60%. The result of the analysis of the two algorithms when implemented into the information system are superior to the FP-Growth algorithm. |
| 5. | Publisher | Organizing agency, location | LPPM STIKOM Tunas Bangsa |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2024-04-30 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://tunasbangsa.ac.id/pkm/index.php/kesatria/article/view/386 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.30645/kesatria.v5i2.386 |
| 10. | Identifier | Digital Object Identifier (DOI) (PDF) |
https://doi.org/10.30645/kesatria.v5i2.386.g382 |
| 11. | Source | Title; vol., no. (year) | Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen); Vol 5, No 2 (2024): Edisi April |
| 12. | Language | English=en | |
| 13. | Relation | Supp. Files | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2024 Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) |