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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Building of Informatics, Technology and Science Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal Pengabdian Masyarakat IPTEK
Anwar, Badrul
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Computer Science & IT

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Journal : Sinkron : Jurnal dan Penelitian Teknik Informatika

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Application of the FP-Growth Method to Determine Drug Sales Patterns Anwar, Badrul; Ambiyar, Ambiyar; Fadhilah, Fadhilah
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12004

Abstract

Pharmacies are shops that sell and mix medicines based on doctors’ prescriptions and trade medical goods. Apart from being a business actor, the pharmacy also plays a role in providing health services that are easily accessible to the public. The problem that often occurs in pharmacies selling drugs is that they are less than optimal in service to consumers. The habit of consumers buying more than one type of drug makes pharmacy staff slow in providing the drug due to the inaccurate layout of the drug. The FP-Growth method in Data Mining is a method that can provide a solution in determining drug sales patterns at pharmacies. The FP-Growth method is a method used in determining the data set that occurs most frequently together (Frequent Itemset). The research objective was to determine drug sales patterns based on drug sales transaction data so that drug layouts could be determined. This research was conducted at the Pharmacy at the Pratama Sehati Husada Clinic in Medan with drug sales transaction data from November 2021 to December 2021. The results of applying the FP-Growth method with a value of ≥ 15% as a minimum support and a value of ≥ 15% as a minimum confidence, a pattern of drug sales in pairs. The application of Data Mining with the FP-Growth method has been implemented at the Pharmacy at the Pratama Sehati Husada Clinic with the desired goals with the final result in the form of a report on the results of determining drug sales patterns.
Weather Forecast In Medan City With Hopfield Artificial Neural Network Algorithm Anwar, Badrul; Jalinus, Nizwardi; Abdullah, Rijal
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12048

Abstract

Many aspects are very influential for the continuity of Indonesian society, especially Medan. One of the aspects that affect the continuity of the people of Medan is the weather. Weather plays an important role in various sectors, such as agriculture, aviation, and many other sectors. The Meteorology, Climatology and Geophysics Agency (BMKG) is always trying to develop their innovations to be able to provide accurate weather information to the public. To assist the process of disseminating weather information to the public in Medan City, we need a Weather Forecast application that uses Website-based computer technology so that it can help disseminate weather information easily and effectively which is generated through the support of the Hopfield method by connecting the application with BMKG data. Based on the results of this study, a weather forecasting application was successfully built to help disseminate weather information in Medan City to all Medan City people who want to get information about the weather.
Co-Authors Abdullah, MT, Dr. Rijal Ambiyar, Ambiyar Asyahri Hadi Nasyuha Budi Nugroho, Nurcahyo Dedy Irfan Fadhilah Fadhilah Kustini, Rini Mariami, Ita Muskhir, Mukhlidi Nizwardi Jalinus Samuel Ginting, Cris Santoso, Ismawardi Sari Ramadhan, Puji Simatupang, Wakhinuddin Sobirin Sobirin Syah Putra, Surianto T. Riza Zarzani N