Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Soft Computing Exploration Journal of Information System Exploration and Research
Samantha, Nikita
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Business process modeling at steak restaurant using business process model and notation Nurdin, Alya Aulia; Pristanti, Aisyah Nungky; Samantha, Nikita
Journal of Soft Computing Exploration Vol. 3 No. 2 (2022): September 2022
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v3i2.84

Abstract

The complexity of business processes occurring today makes the company try to find ways to describe its business processes. Business processes are not only an operational standard but also become one of the determining factors for the smooth use of time and costs in a business unit to be more efficient. With good business processes, it makes the flow of information faster so that it can help in making the best decisions in the organization. The business process modeling that will be explained further in this study is the order and procurement business process at steak restaurant using the Business Process Model Notation (BPMN) approach. This research was conducted using a qualitative descriptive method with the aim of observing the business unit to help analyze and make improvements to its business processes. Several series of processes were carried out, namely business identification and modeling with bizagi modeler and process reengineering to produce recommended new business process models that could be beneficial for business units, namely the recommended automation in the form of the use of mobile applications, remote, and database systems to support the effectiveness of the order to cash and procure to pay processes.
Techniques of Applied Machine Learning Being Utilized for the Purpose of Selecting and Placing Human Resources within the Public Sector Pampouktsi, Panagiota; Avdimiotis, Spyridon; Maragoudakis, Manolis; Avlonitis, Markos; Samantha, Nikita; Hoogar, Praveen; Ruhago, George Mugambage; Rono, Wcyliffe
Journal of Information System Exploration and Research Vol. 1 No. 1 (2023): January 2023
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v1i1.91

Abstract

In strategic human resource management, one of the most critical issues to focus on is the correct selection and placement of people. Within the confines of this framework, the reason for the study that was conducted was to explore the machine learning approaches that proved to be the most effective in assisting with the recruitment of personnel and the assessment of their positions. To accomplish this goal, a in a series of tests involving workers in the public sector, categorization algorithms were used. The purpose of these tests was to determine which employees would be the ideal fit in which workstations and to determine how workers should be distributed. For supporting the decision support system, an algorithm model was created. Used in the process of recruiting and evaluating potential workers based on the results of the tests that were given. The most important results of this study support the idea that using the People's Evaluation for Recruitment and Promotion Algorithm Model (EERPAM) would make hiring and promoting people in a company fairer.
Co-Authors Avdimiotis, Spyridon Avlonitis, Markos Hoogar, Praveen Maragoudakis, Manolis Nurdin, Alya Aulia Pampouktsi, Panagiota Pristanti, Aisyah Nungky Rono, Wcyliffe Ruhago, George Mugambage