Rezi Elsya Putra
Sekolah Tinggi Ilmu Komputer Muhammadiyah Batam

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Metode Simple Multi Attribute Rating Technique dalam Keputusan Pemilihan Dosen Berprestasi yang Tepat Rezi Elsya Putra; Selvia Djasmayena
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i1.29

Abstract

Each lecturer is required to carry out the tridarma of higher education, a career to become a lecturer must be professional in accordance with his knowledge and expertise. Almost every year state or private tertiary institutions, give an award to lecturers who excel one of the benchmarks is from the tri darma performance of higher education. At present in determining the right lecturer with good achievements there are still many weaknesses of one of the criteria used. Then the research has the aim to determine the outstanding lecturers by using the right criteria effectively. The method used is the Simple Multi Attribute Rating Technique (SMART) method using Sekolah Tinggi Ilmu Komputer (STIKOM) Muhammadiyah Batam’s lecturer data. The results of this study set the right criteria, so get a very high level of accuracy which is 79%. So this research becomes the right indicator in determining the outstanding lecturers.
Prediksi Pola Penjualan Produk Herbal Menggunakan Algoritma FP-Growth Supinah; Rezi Elsya Putra; Mohd. Iqbal
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.167

Abstract

The pattern of sales is a necessity in a business, in increasing sales strategies setting patterns will help the business progress. The pattern of selling these herbal products can increase sales and convenience for sellers and buyers compared to manual settings. Setting the layout of herbal products can facilitate customers in the selection of interrelated products. Continuous product prediction can be easily recognized by the seller. The sales pattern prediction in this study uses transaction data as many as 33 sales transactions in less than the last three months originating from the sale of Batam HNI Bussiness Center 2 herbal products. Based on sales analysis using the FP-Growth algorithm can predict the pattern of sales of herbal products for the future. Furthermore, transaction data is processed using Rapidminer Studio version 9.0 software with 68 transaction data, then from the results of testing on this method the percentage of success is 80%. Comparison uses 10 sales data samples. Opportunities to choose interrelated products greatly help customers when shopping and predict future customer needs. The sales pattern prediction has helped to overcome the instability of herbal product supplies at Batam's HNI Bussiness Center 2.
Pemilihan Supplier Obat yang Tepat Menggunakan Metode Multi Attribut Utility Theory Selvia Djasmayena; Yuhandri Yunus; Rezi Elsya Putra
Jurnal Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v1i4.27

Abstract

Drug suppliers are those who sell and distribute drugs to pharmacies or sections that carry out pharmaceutical activities. Selection of the right supplier can support the operational activities of the pharmacy. Pharmacists must know the right criteria in choosing a supplier. Criteria determined by pharmacies not all suppliers can fulfill it. Overcoming this decision support system is very necessary in the selection of suppliers. Multi-Attribute Utility Theory is a ranking method that helps in supporting supplier selection decisions at Pekanbaru Assyafni Pharmacy. Supplier selection uses 15 sample supplier data and 5 criterion data used as a basis for supplier selection. Such as drug production, delivery time, quality stability, service response, and guarantee. The results of the study get a high degree of accuracy that is 86.67% of the right suppliers and in accordance with the realization of test data. So this research is very important in choosing the right supplier.