ANALISIS POLA ASOSIASI KELUHAN PASIEN AMBULANCE HEBAT KOTA SEMARANG MENGGUNAKAN ALGORITMA APRIORI

Wulandari, Aryati (2021) ANALISIS POLA ASOSIASI KELUHAN PASIEN AMBULANCE HEBAT KOTA SEMARANG MENGGUNAKAN ALGORITMA APRIORI. Undergraduate thesis, Universitas Stikubank.

	PDF (HLM JDL) Download (674kB)
	PDF (ABSTRAK) Download (160kB)
	PDF (BAB I) Download (291kB)
	PDF (BAB II) Restricted to Repository staff only Download (599kB)
	PDF (BAB III) Restricted to Repository staff only Download (647kB)
	PDF (BAB IV) Restricted to Repository staff only Download (1MB)
	PDF (BAB V) Restricted to Repository staff only Download (156kB)
	PDF (DAFTAR PUSTAKA) Download (265kB)
	PDF (LAMPIRAN) Restricted to Repository staff only Download (1MB)

Abstract

Ambulance Hebat adalah sebuah pelayanan kesehatan masyarakat dari Pemkot Kota Semarang. Layanan kesehatan ini menyediakan alat dan obat dalam penanganan pasien ditempat entah itu pasien yang mengalami kecelakaan ataupun sakit. Karena setiap pasien memiliki sebuah keluhan maka tenaga medis harus mengetahui cara penanganan dan persiapan saat mendapatkan pasien. Dengan mengetahui pola keluhan pasien pengambilan keputusan dalam penanganan pasien akan lebih efektif Data Mining dijelaskan sebagai proses menemukan sebuah aturan pola pola tersembunyi dalam data yang besar. Dengan memanfaatkan teknik Data Mining menggunakan metode asosiasi algoritma apriori dalam pengolahan data keluhan pasien Ambulance Hebat dapat menghasilkan pola asosiastif keluhan yang dapat di analisa. Dengan menetapkan parameter nilai kepercayaan (minimum confidence) 40% dan nilai support (minnimun support) 6% dalam periode Oktober, November, Desember menghasilkan 9 pola asosiasi. Diharapkan dengan mengetahui pola asosiasi dari keluhan yang terjadi akan dapat membantu petugas medis Ambulance Hebat dalam memberikan pelayanan yang optimal dalam penyediaan obat dan peralatan medis saat kejadian. Abstrack Great Ambulance is a public health service from the City Government of Semarang City. This health service provides tools and drugs in handling patients on the spot, whether it's a patient who has an accident or is sick. Because every patient has a complaint, medical personnel must know how to handle and prepare when getting a patient. By knowing the pattern of patient complaints, decision making in handling patients will be more effective Data mining is described as the process of finding a hidden pattern of rules in big data. By utilizing the Data Mining technique using the a priori algorithm association method in processing the complaint data of the Great Ambulance patient, it can produce an associative pattern of complaints that can be analyzed. By setting the parameters of the confidence value (minimum confidence) of 40% and the support value (minnimun support) of 6% in the period of October, November, December, resulting in 9 association patterns {fever, weakness}{difficult to communicate, weak}{nausea, weakness}{problem in the head, weakness}{cough, shortness of breath}{cough, fever}}{fever, decreased condition, weakness}{fever, weakness, decreased condition}{decreased condition, weakness, fever}. Knowing the high frequency value of disease complaints that often occur in the city of Semarang helps the Great Ambulance medical officer to provide maximum service in the provision of drugs and medical equipment by knowing the pattern of disease complaints.

Item Type:	Thesis (Undergraduate)
Additional Information:	NIM : 17.01.55.0054 SKR.I.05.02.1973
Uncontrolled Keywords:	Data Mining, Algoritma apriori, keluhan penya
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Faculty / Institution:	Fakultas Teknologi Informasi > Program Studi Sistem Informasi
Depositing User:	Ani Mariawati
Date Deposited:	10 Nov 2021 04:47
Last Modified:	10 Nov 2021 04:47
URI:	https://eprints.unisbank.ac.id/id/eprint/8029

Actions (login required)

View Item