ANALISIS PENENTUAN ASOSIASI PADA TRANSAKSI PENJUALAN OBAT MENGGUNAKAN ALGORITMA APRIORI (STUDI KASUS KLINIK BIDAN NENENG HASANAH, AM.KEB DI CIKARANG BARAT BEKASI)

Zahra Luthfiah, - (2023) ANALISIS PENENTUAN ASOSIASI PADA TRANSAKSI PENJUALAN OBAT MENGGUNAKAN ALGORITMA APRIORI (STUDI KASUS KLINIK BIDAN NENENG HASANAH, AM.KEB DI CIKARANG BARAT BEKASI). S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: http://repositori.upi.edu

Abstract

Salah satu data yang cukup krusial dalam bidang kesehatan adalah informasi mengenai data obat, kebutuhan obat menghasilkan transaksi penjualan setiap harinya dan kebanyakan transaksi penjualan obat di klinik tidak memiliki laporan terperinci. Contohnya pada klinik Bidan Neneng Hasanah, Am.Keb di Cikarang Barat Bekasi yang telah di observasi pada tanggal 6 Desember 2022, melihat kebutuhan informasi mengenai data transaksi penjualan obat yang tidak memiliki laporan terperinci maka perlu adanya pengolahan data agar mendapatkan suatu pola keterkaitan antar itemset produk yang sering dibeli dengan waktu yang sama. Berdasarkan hal tersebut, peneliti menggunakan pendekatan kuantitatif deskriptif dengan proses analisis yang dilakukan melalui observasi, pencatatan dan wawancara. Untuk mengetahui pola transaksi, peneliti menggunakan aturan asosiasi dengan algoritma apriori dengan parameter minimum support = 50% dan minimum confidence = 70% yang ditetapkan. Peneliti mengambil data transaksi selama 1 tahun pada tahun 2022 dan diolah dengan 3 bagian yaitu data pertahun, per-enam bulan dan per-enam bulan terakhir menggunakan alat uji Spreadsheet dan divalidasi oleh RapidMiner. Hasil alat uji menghasilkan analisis yang signifikan yaitu dengan 5 aturan asosiasi dan menghasilkan aturan asosiasi tertinggi dengan itemset “Jika membeli Andalan Suntik KB maka membeli Onemed One Swabs”, itemset tersebut memiliki masing-masing rules dengan item Andalan Suntik KB minimum support 72% dan Onemed One Swabs minimum confidence 100%. Hasil dari pengujian nantinya dipakai sebagai keputusan membeli obat di waktu yang akan mendatang. ----- One of the data that is quite crucial in the health sector is information about drug data, drug needs generate sales transactions every day and most drug sales transactions in clinics do not have detailed reports. For example, at the Midwife Neneng Hasanah clinic, Am.Keb in Cikarang Barat Bekasi, which was observed on December 6, 2022, seeing the need for information regarding drug sales transaction data that does not have a detailed report, it is necessary to process data in order to obtain a pattern of linkages between product item sets which are often purchased at the same time. Based on this, researchers used a descriptive quantitative approach with an analysis process carried out through observation, recording and interviews. To find out transaction patterns, researchers use association rules with the a priori algorithm with the parameters of minimum support = 50% and minimum confidence = 70% set. Researchers took transaction data for 1 year in 2022 and processed it into 3 parts, namely data per year, every six months and the last six months using the Spreadsheet test tool and validated by RapidMiner. The results of the test tool produce a significant analysis, namely with 5 association rules and produce the highest association rules with the itemset "If you buy the Mainstay for KB Injection then buy Onemed One Swabs", the itemset has each rule with the Mainstay for KB Injection minimum support 72% and Onemed One swab minimum 100% confidence. The results of the test will be used as a decision to buy drugs in the future.

Item Type: Thesis (S1)
Additional Information: Dosen Pembimbing Suprih Widodo Sinta ID : 5978120 https://scholar.google.com/citations?user=P-awTsUAAAAJ&hl=id&oi=ao Dosen Pembimbing Rian Andrian Sinta ID : 6681695 https://scholar.google.com/citations?user=UKmGK14AAAAJ&hl=id&oi=ao
Uncontrolled Keywords: aturan asosiasi, hasil perhitungan, pertahun, per-enam bulan
Subjects: L Education > L Education (General)
L Education > LC Special aspects of education
Divisions: UPI Kampus Purwakarta > S1 Pendidikan Sistem Teknologi dan Informasi
Depositing User: Zahra Luthfiah
Date Deposited: 29 Aug 2023 06:51
Last Modified: 29 Aug 2023 06:51
URI: http://repository.upi.edu/id/eprint/97858

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