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International Journal of Information Technology and Computer Science Applications (IJITCSA)

jitcsa
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Published by Jejaring Penelitian dan Pengabdian Masyarakat

ISSN : 29643139 EISSN : 29855330 DOI : https://doi.org/10.58776/ijitcsa.v1i2

Core Subject : Science, Education, Engineering,

Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

he Journal of Information Technology and Computer Science Applications (JITCSA) is an information technology and computer science publication. Applications from both fields for solving real cases are also welcome. JITCSA accepts research articles, systematic reviews, literature studies, and other relevant ones. Several fields of science that are the focus of JITCSA include information technology and the like, computer science fields, including artificial intelligence, data science, data mining, machine learning, deep learning, and the like. IJITCSA is published three times a year, in January, May, and September. The first issue in January 2023 had eight articles. Focus and Scope International Journal of Information Technology and Computer Science Applications includes scholarly writings on scientific research or review, pure research, and applied research in the field of computer science, information systems, and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Information systems System Software Artificial Intelligence Computer Architecture Distributed Systems System & Software Engineering Genomics & Bioinformatics Internet and Web AI & Expert systems Software Process and Life Cycle Database Systems Software Testing & Quality assurance Bioinformatics Information Technology Implementation Computing Languages & Algorithms E-commerce & M-Commerce Computer Networks & Communications Computing Systems Control Systems & Engineering Systems Engineering System Security Digital Forensics Data Mining & Machine Learning Data Modeling

Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer

Articles 20 Documents

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Sistem Pendukung Keputusan Penentuan Pelanggan Terbaik Dengan Metode Simple Multi Attribute Rating Technique (SMART) Vidila Rosalina; Wahyu Agustiawan; Ayu Purnamasari
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Jaya Bila Makmur is a nine-ingredient grocery store with products sold including cooking oil, instant noodles, rice, margarine, sugar, salt, and so on. With the continuous increase in the number of similar grocery stores on the market, business owners must have a strategy so that customers remain loyal and don't move elsewhere. One of the strategies is to give rewards or gifts to loyal customers for their cooperation so far, but the decisions taken by business owners are still not quite right. Then a decision support system (DSS) is needed that is able to provide alternative solutions. This system was built using PHP and MySQL, modeled using UML, and tested with Blackbox Testing. The method used in DSS uses the Simple Multi-Attribute Rating Technique (SMART) for multi-criteria decision making. The findings of this study are intended to assist in identifying the best customers who shop frequently and will become repeat customers. By implementing this decision-support system, business owners can improve their competitiveness and competence in the business world. From the results of the application built, it is hoped that it will make it easier for users to choose and determine the best customers according to the specified criteria.

Data Analysis Using Cluster and Logistic Regression Analysis (A Case Study) Puspa Byanjankar; Kabindra Marhatta; Yushma Himanshu
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Customer loyalty has been a concern to C&M. C&M implements logistic regression and cluster analysis to tackle customer churn on consulting services and products. Logistic regression analysis predicts whether chemical manufacturers and small personal services will purchase consulting services and training products with discount reduction in 18 months. Their pur-chase choices every 18 months are influenced by discounts or non-discount. Cluster analysis groups purchase power based on the age group. It forecasts business client’s transaction through purchase duration and frequent purchase on consulting services and items. Thus, C&M builds a long-term relationship with chemical manufacturers and small personal ser-vices by creating customer satisfaction on our consulting services and products.

COVID-19 Impacts: Empirical Studies on Orion Indoor Sports Business Using Visual Analytics Suzane Bellinda
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Covid-19 spreads across the world in just a few months and it has caused severe economic consequences to many countries. Many businesses are also affected dramatically due to the lockdown in order to stop the spread. It does not only affect businesses, it affects how consumers behave in buying and shopping as well. Consumers learn to improvise and get used to the new habits. For example, consumers are not allowed to go to the gyms as they are closed during the lockdown, and they start to work out at home. Technology advances has played a big role in helping the consumers to cope in this situation in an innovative way. Some changes done in an organization to adapt to the pandemic can potentially improve their business tremendously and reduce the losses that already exist before the pandemic. For example, gym equipment sales were only targeting business before the pandemic. However, due to the lockdown, many people were left nowhere to work out and they then prefer to buy gym equipment at home. This will increase the demand of gym equipment and thus boosting the fitness industry business. With the advancement of technology, fitness industry can sell their products online easily and they can also view real-time business performance.

Customer Value and Data Mining in Segmentation Analysis Ahmed Gunandi; Heba Awang; Eman Alhawad; Lotfy Shabaan
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Customer Value is the accessed value that a customer has to an organization. In Business, the customer is always right. This statement gives us the impression that all customers are viewed as equal in terms of potential value. Each customer is treated differently according to how much profit they can bring to a company. We use various Data Mining techniques to determine who are these customers and how we can acquire more customers like them who can bring more profit. A loyal customer will be treated differently than a customer that rarely do business with the organization. These customers are usually given bonus gifts and special offers as a form of thanks for their loyalty thus further strengthening that bond. Companies need a way to determine which of their hundreds of thousands of customers are deserving of this attention. Customer Value Segments are used in this specific situation.

Data Analytics Application in Fashion Retail SMEs (A Case Study in Caracas Fashion Store) Santorini Surabani; Bradlow Rodriguez
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Data analytics plays a paramount role in maximizing productivity and profitability for businesses by deriving insights from pre-existing data to predict market trends and client habits to make better business decisions. In accordance with Industrial Revolution 4.0, most SMEs have begun to implement an e-commerce business model, thus, customer data is generated at an exponential rate, allowing SMEs to further develop their services for greater user satisfaction. However, the abundance of unsorted and ambiguous data leads to issues such as server overload and inefficient customer sales cycle tracking. This paper will explain the application of data analytics techniques and architectures to overcome these issues in a fashion retail SME, as well as the benefits and drawbacks of these solutions.

Discovering Patterns in Textual Data Using SAS Visual Analytic Wintuik Majaliwa
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Today's generation are more tech savvy than previous generations. They tend to complete their everyday tasks from making their daily schedule to purchasing their daily necessities on the internet. Due to the boom in this culture, e-commerce retail stores have increased their retail sales. According to the United States of America’s Census Bureau, the retail online sales in the year 2012 has peaked at $45.6 billion from the year 2001. This is an increase of 26.9%. This proves that the digital economy is growing and will continue to grow further. In e-commerce platforms there will definitely be a large requirement for logistics which develop a cross organisational support between supply chain management and retail sales. Using text analysis an in depth review of understanding customer satisfaction towards logistical issues to further enhance product delivery and logistical improvements in terms of logistics operations. Mainly using sentiment analysis. Challenges to product delivery are discussed and viable solutions to overcome current or existing logistical issues are presented in this paper.

Exclusive Clustering Technique for Customer Segmentation in National Telecommunications Companies Jhon Kristian Vieri; Tb Ai Munandar; Dwi Budi Srisulistiowati
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

This study aims to empirically examine consumer behavior based on customer transaction history. Analyzing consumer behavior can provide very useful information for businesses in making decisions, particularly business decisions toward customers, in order to survive in such intense competition.Companies are becoming faster and more precise in reading environmental conditions and predicting what conditions may occur as a result of machine learning technology.This technology can also assist companies in making decisions that are more targeted according to actual secondary data provided for research. One of the machine learning methods, unsupervised learning, can help explicitly identify hidden structures or patterns in data and determine correlations. This method uses the Exclusive Clustering method, using two algorithms, namely, K-Means and K-Medoids, to use the comparison method to get optimal segmentation results. The results obtained are expected to be a reference for making a change in the company's marketing policy in order to retain and gain customers who are constantly decreasing.

K-Means Cluster Algorithm for Grouping Inequality in Regional Development Tb Ai Munandar; Dwipa Handayani
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Unsupervised learning is a subset of machine learning. Many unsupervised learning algorithms are used to solve various problems, especially the extraction of hidden data patterns. One of the problems that concerns unsupervised tasks is clustering. Clustering techniques are widely used for data grouping needs, one of which is development inequality clustering. The classification of development inequality is an important consideration in a country's regional development strategy. However, development groupings often do not pay attention to the hidden information aspects of the data, so they do not get the appropriate results. This research was conducted to provide an additional alternative in the realm of development inequality clustering, namely by classifying development data using the k-means algorithm. The data used is GRDP data for 41 regions in the western part of Java Island for the 2010–2021 range. The results show that the forty-one regions are grouped into four clusters. The first cluster (C1) contains 35 regions, the second cluster (C2) contains three regions, the third cluster (C3) contains four regions, and the fourth cluster (C4) contains three regions. Based on the cluster results, it can be seen that all members of cluster C4 are areas with the best level of development, while cluster C1 is the area with the lowest level of development. As for clusters C2 and C3, these are areas with development levels between clusters C1 and C4. The grouping results can be used by policymakers or local governments to determine the direction of future development priorities based on the cluster with the lowest level of development.

Decision Support System for Teacher Performance Assessment Using the Weighted Product Method Dentik Karyaningsih
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

The quality of teachers can be seen from the results of their performance assessment whether they have increased or vice versa. Therefore, an objective performance appraisal system is needed, in addition to reviewing performance results, the assessment system can also be a reference for determining the best teacher, so that teachers are more motivated in teaching. In making decisions on teacher performance evaluation at Pelita Insani Special Schools, they still experience problems when the process is done manually and the assessment system is less objective. So we need a Decision Support System that can produce the best alternative, can be done automatically and objectively. Practitioners This study produced a web-based decision support system that can provide alternative decision-making for school principals based on teacher performance results. By using the Weighted Product method. There are six criteria, namely: learning planning, implementing learning, assessing learning outcomes, training and guiding, additional assignments, and developing professional activities, then processed with data on teacher performance results with this method and produces teacher rankings which can be recommendations for decision making for school principals

Challenges and Strategies for Inventory Management in Small and Medium-Sized Cosmetic Enterprises: A Review Arthit Kittisak
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

This research paper presents a case study analysis of the inventory management challenges faced by small and medium-sized cosmetic enterprises (SMEs) and the strategies employed to overcome them. The study was conducted through qualitative research methods, including in-depth interviews with managers of SMEs in the cosmetics industry. The findings revealed that the major challenges faced by SMEs in managing their inventory were poor demand forecasting, inadequate storage facilities, and lack of efficient inventory control systems. To mitigate these challenges, SMEs employed strategies such as outsourcing inventory management, adopting technology-driven inventory control systems, and establishing efficient supply chain networks. The study concludes that effective inventory management is crucial for the success of SMEs in the cosmetics industry, and the strategies identified in this study could be useful for practitioners seeking to improve their inventory management practices.

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Ai Munandar

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ijitcsa@gmail.com

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+62+6282111152015

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Kota serang,

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Ai Munandar

Contact Email ijitcsa@gmail.com

Phone +62+6282111152015

Journal Mail Official ijitcsa@gmail.com

Location Kota serang, Banten INDONESIA

Abstract

Abstract

Abstract

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Abstract

Contact Name
Ai Munandar

Contact Email
ijitcsa@gmail.com

Phone
+62+6282111152015

Journal Mail Official
ijitcsa@gmail.com

Location
Kota serang,

Banten

INDONESIA