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Anjar Wanto
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JOMLAI: Journal of Machine Learning and Artificial Intelligence
Published by Yayasan Literasi Sains Indonesia
ISSN : 28289102     EISSN : 28289099     DOI : 10.55123/jomlai
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well as an overview of the development of theories, methods, and related applied sciences. Topics cover the following areas (but are not limited to): Software engineering Hardware Engineering Information Security System Engineering Expert system Decision Support System Data Mining Artificial Intelligence System Computer network Computer Engineering Image processing Genetic Algorithm Information Systems Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Other relevant study topics Noted: Articles have primary citations and have never been published online or printed before
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 12 Documents
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Search results for , issue "Vol. 1 No. 4 (2022): December" : 12 Documents clear
Application of Data Mining Classification C4.5 Patient Satisfaction with Tuan Rondahaim Simalungun Hospital Service Nadrah Fauziah; Muhammad Ridwan Lubis; Bahrudi Efendi Damanik
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.312 KB) | DOI: 10.55123/jomlai.v1i4.1678

Abstract

The purpose of this study was to produce a measuring instrument for patient satisfaction with hospital services. In order to further improve patient care. The method used in this study is the C4.5 Algorithm, where the data source used is a questionnaire/questionnaire technique which is given a questionnaire to the general public who visit the hospital. The results of this study are expected to provide input to the Tuan Rondahaim Hospital in Simalungun by using the C4.5 Algorithm. This can be done by using a decision tree model or decision tree in the C4.5 algorithm. In this study, the researchers used data from the patients of RSUD Tuan Rondahaim, totaling 105 patients through a questionnaire that the researchers distributed. The variables are Hospital Place (C1), Empathy (C2) and Responsiveness (C3). The testing process of this study uses Rapid Miner software to generate rules and a decision tree model or decision tree that will be used in determining the patient satisfaction factor for Tuan Rondahaim Hospital. The results of this study obtained 14 rules with an accuracy rate of 93.55%.
Application of Associations Using the Apriori Algorithm to Analyze Consumer Purchase Patterns at Grocery Stores Oka Ristawaty Sirait; Sumarno Sumarno; Nani Hidayati
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (578.322 KB) | DOI: 10.55123/jomlai.v1i4.1679

Abstract

The grocery store sells various types of ingredients for everyday life. Every day many customers shop at the grocery store. Every item sold at the Grocery Store will generate sales data, but this data cannot be utilized optimally. So we need a data analysis to help the Grocery Store gain knowledge of sales patterns in a certain period. The algorithm used as the primary process of analyzing the sale of ingredients in grocery stores is an a priori algorithm using the application of a minimum support value of 50% and a minimum confidence value of 70%, which meets the minimum support value and minimum confidence value, and sales transactions to find association rules. The Apriori algorithm test results will show results that have met the needs and determine the pattern of purchasing materials at the Grocery Store based on the items that customers most frequently purchase.

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