IMPLEMENT OF APRIORIAL ALGORITHM FOR PROCUREMENT OF MEDICINE AND HEALTH EQUIPMENT ON RADIOLOGY DEPARTMENT OF MAYAPADA HOSPITAL

Penerapan Algoritma Apriori Untuk Pengadaan Obat Dan Alat Kesehatan Pada Departement Radiologi Mayapada Hospital

  • Muhammad Afif (1) Sistem Informasi STMIK Nusa Mandiri
  • Dewi Ayu Nur Wulandari (2*) Universitas Bina Sarana Informatika

  • (*) Corresponding Author
Keywords: Apriori Algoritm, Assosiation, Mayapada Hospital

Abstract

The pattern of drug and medical device needs at Mayapada Hospital in South Jakarta has a tendency to be repeated and similar in a relatively long period of time, especially in one particular department, because the cases found are often similar or even similar. Ensuring the availability of stock in each department's deposit is very vital, because the procurement of medical equipment must go through a certain process and time, so there are often cases where there is a critical resus but the equipment needed in the deposit does not meet the needs or escape from inventory and must indent first. By calculating the tendency (Apriori Association) demand patterns in the relevant departments, especially in the radiology department at Mayapada Hospital, South Jakarta, a rule was formed that resulted in a pattern of dependency between itemsets that had supporting criteria in the form of support of 33.3% and Confidence by 85%, where the items that appear are items with a high frequency of appearance and association, so they can be taken into consideration to ensure the availability of drugs and medical devices.

References

Afif, M., & Wulandari, D. A. N. (2019). Laporan Penelitian : Implementasi Data Mining Algoritma Apriori Pada Pengadaan Obat Dan Alat Kesehatan Pada Departemen Radiologi Mayapada Hospital. Jakarta.

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Published
2019-09-06
How to Cite
Afif, M., & Wulandari, D. A. (2019). IMPLEMENT OF APRIORIAL ALGORITHM FOR PROCUREMENT OF MEDICINE AND HEALTH EQUIPMENT ON RADIOLOGY DEPARTMENT OF MAYAPADA HOSPITAL. Jurnal Techno Nusa Mandiri, 16(2), 99-104. https://doi.org/10.33480/techno.v16i2.737
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