Ifan Prihandi
Universitas Mercu Buana

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

Aplikasi Monitoring Tender Project Dengan Metode Prototyping (Studi Kasus : PT Sinergy Informasi Pratama) Ilham Maulana; Ifan Prihandi
FORMAT Vol 8, No 2 (2019)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2019.v8.i2.004

Abstract

PT Sinergy Informasi Pratama merupakan salah satu perusahaan Sistem Integrator yang menyediakan produk dan layanan Teknologi Informasi dan Komunikasi (TIK) khususnya di bidang Informasi Teknologi. PT  Sinergy Informasi Pratama  memiliki beberapa  masalah diantaranya tidak adanya sistem yang memantau perkembangan tender project, pencatatan keikut sertaan tender dan begitu juga dalam penomoran suatu tender. Setiap tender memiliki penomoran dan penomoran tersebut dinamakan dengan sebutan lead. Oleh karena itu diusulkan pembuatan sebuah aplikasi yang dapat memecahkan masalah tersebut. Dalam jurnal ini, penulis mencoba mengusulkan dan membuat sistem aplikasi monitoring tender project berbasis web untuk membantu dalam proses bisnis dan operasional di dalam perusahaan dengan dibantu  metode analisa PIECES dan  metode pengembangan  prototyping. Dengan ini diharapkan informasi menjadi lebih akurat sehingga membantu dalam pengambilan keputusan. 
Optimizing JMeter on Performance Testing Using the Bulk Data Method Nurullah Husufa; Ifan Prihandi
Journal of Information System and Informatics Vol 4 No 2 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i2.244

Abstract

Company X is one of the companies engaged in the telecommunications business. To improve customer service, the company developed an Application Programming Interface). The developed API is used to promote product packages to customers. Sending data via API to millions of customers at the same time, can lead to failures due to the inability of the server to process that data. JMeter is one of the tools that can be used to perform performance testing of an API by providing TPS calculation output. Bulk data files are used as input to process large amounts of customer data on JMeter. Proper thread properties settings affect the TPS value, and the study has managed to achieve the TPS value to be achieved with error rate = 0, which means success.
Design and Build A Customer-Finding Application For Leko Restaurant Using The K-Means Algorithm Mohamad Yusuf; Muhaimin Hasanudin; Ifan Prihandi
IJISTECH (International Journal of Information System and Technology) Vol 6, No 2 (2022): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (618.288 KB) | DOI: 10.30645/ijistech.v6i2.238

Abstract

Warung Makan Leko is one of the restaurants in the Jakarta area that offers local cuisine, a diverse menu and delivery orders via phone order. Customers are one source of income for Warung Makan Leko. The amount of competition makes Warung Makan Leko have difficulty in retaining loyal customers. For this reason, further analysis is needed to find out who these potential customers are. Then an application was developed to classify customer data using the K-Means (clustering) algorithm. The data used as an example in this study is the sales transaction data of Warung Makan Leko. Run the process to calculate the total sales to customers and the number of transactions with customers to classify customer data. The K-Means clustering method tries to group the existing data into groups. Data in groups have the same properties. Customer data is grouped into two clusters, no and implicit. Each cluster is then classified based on the prioritized criteria. The cluster with the highest centroid value is the cluster that is rewarded, and the cluster with the lowest centroid value is the non-rewarded cluster. The results of this process form clusters, which are used for advice and consideration to determine sales strategy, namely to reward customers who rank higher in the cluster