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International Journal of Information Technology and Computer Science Applications (IJITCSA)
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 50 Documents
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Business Intelligence (BI) System for Budgeting and Customer Satisfaction Chi, Aung Nay
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1136.928 KB) | DOI: 10.58776/ijitcsa.v1i2.31

Abstract

This research is about a casino company that wishes to use Business Intelligence (BI) system to solve their budgeting problems while attracting customers. They provided the dataset required to analyse their two casino branches and find what actions that they need take, with the help of visualizations. After analysing the visualizations, it was clear that there were many machines that their customers are not found of and that video machines are the most popular among the three types of machines. The least played type of machine was vpoker and only two manufactures provide them with the machines. The likely reason for people do not playing vpoker is that it requires mental strength and mathematics. It was also clear that customers come to the casinos in April, possibly due to holidays. With the help of new technologies, they can gather more information from their customers, without upsetting them and increasing the security to prevent vandalism and destruction of property by angry customers.
Business Intelligence (BI) Approach for Traffic Accidents Analysis Madnira, Shujana
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1763.07 KB) | DOI: 10.58776/ijitcsa.v1i2.32

Abstract

‘FLCRASH’ is the data source used for this report that consists of crash data from the year 2008 to 2009. The purpose of this report is to find ways to reduce the number of fatal accidents on the road by identifying the main culprits on why these accidents happen so frequently. Business intelligence is used in the process of finding the relationships and trends in the major causes of the crashes. The technologies related to Business Intelligence that will help in aiding the organization to their goal are also discussed along with the supporting factors for the use of Business Intelligence for the organization. A dashboard has been created from various graphs and charts for easy viewing and understanding of the situation so logical decisions can be made based on it. This report seeks to help us better understand the nature of why traffic accidents happen in the first place and how to prevent them from happening in the future.
Comparative Study of Classification Algorithms for Customer Decisions on Telecommunication Products Using Supervised Learning Kristian Vieri, Jhon; Munandar, Tb Ai; Srisulistiowati, Dwi Budi; Handayani, Dwipa; No’eman, Achmad; Sri Lestari, Tyastuti
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.899 KB) | DOI: 10.58776/ijitcsa.v1i2.34

Abstract

Customers are the main goal of all business fields, without customers the company will not be able to continue or compete in the business field it is in, even though the company has brilliant products, if it does not have an increase in the number of customers the business will not be able to develop or even go bankrupt. Therefore, it is necessary to make observations and make applications that are able to predict customers who will subscribe so that companies can predict customers who will subscribe correctly without having to wait for confirmation from customers whose possibilities are still unknown. This can be very useful for any company because companies no longer need to look for random customers where it only takes time to find customers. PT. Telekomunikasi Indonesia with its product (Indihome) which is struggling to compete in the business world in the telecommunications and internet sector. Therefore research and development of this application are carried out so that PT. Indonesian telecommunications can get its customers quickly without having to spend a lot of money and effort. Making this application uses a classification method from machine learning technology based on customer historical data. The classification method has many strong algorithms for predicting variables that have more than 1 label. Some of the algorithms used are Logistic Regression, Random Forest Classifier, Support Vector Machine and Decision Tree which are provided by modules in the python programming language, namely SkLearn. The four algorithms will be tested with data balanced using the Oversampling method from the Smote algorithm to get optimal results in automatically predicting customers.
Using the Service Quality approach, an analysis of customer satisfaction in early childhood education at Bina Mulia Muhammad Khaerudin
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1870.294 KB) | DOI: 10.58776/ijitcsa.v1i2.35

Abstract

Kindergarten is an early childhood education facility, Bina Mulia Cibitung strives to attract and keep clients, specifically parents and guardians of students, by raising the standard of service in all areas. Increased customer satisfaction and trust, in this example from the person or guardian of pupils, are anticipated benefits of better service quality. Customers will be satisfied when their needs, wants, and expectations are met or exceeded during a transaction, leading to continued loyalty. Customer satisfaction is defined by research in this paper as a customer's reaction to a difference between the prior degree of importance and the actual performance he perceives after use. A service quality technique is used to gauge how satisfied customers are (customer satisfaction). This strategy makes use of a questionnaire as a tool to help determine what the customer's expectations are as well as their desires and impressions. Additionally, the difference between expectations and perceptions is used to gauge the quality of a service. Customer impressions of the service they actually receive and the service they expect can be compared to determine service quality.
Sentiment Analysis of the Use of Digital Banking Service Applications On Google Play Store Reviews Using Naïve Bayes Method Amalia Nur Soliha; Tb Ai Munandar; Muhammad Yasir
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.40

Abstract

The development of the financial system is characterized by the emergence of digital banking service applications that are widely circulated and can be accessed for free. With so many applications, users often feel confused in choosing which applications are safe to use. Before downloading an application on the Google Play Store, users will usually look at ratings and reviews first. However, the title of the best application cannot be pinned if only seen from the rating and number of downloads. This research was conducted to analyze sentiment on user reviews of digital banking service applications on the Google Play Store using the NBC (Naïve Bayes Classifier) method. Research using the NBC algorithm produced an accuracy value of 81% on the classification of Allo Bank reviews and 78% on the classification of Line Bank reviews
Clustering of Child Nutrition Status using Hierarchical Agglomerative Clustering Algorithm in Bekasi City Ozzi ardhiyanto; Muhammad Salam Asyidqi; Ajif Yunizar Pratama Yusuf, S.Si, M.Eng; Dr. Tb. Ai Munandar, S.Kom., MT
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.42

Abstract

Clustering infant nutrition based on weight, height, and age is a data analysis method used to group infant nutritional status based on these characteristics. The research on clustering infant nutrition aims to analyze whether there are still many infants in the area with insufficient or excessive nutrition, and to identify groups of infants requiring special attention regarding their nutritional intake. In the analysis of infant nutrition clustering, data on weight, height, and age of infants are collected and then grouped based on similarities in body height and weight at certain ages. The method used in this research is hierarchical clustering, which can help in grouping the data. Clustering analysis can help understand how infants' feeding patterns vary based on their weight, height, and age. The results of research on clustering infant nutrition based on weight, height, and age can provide valuable insights for nutrition experts, pediatricians, and community health workers in developing appropriate intervention programs to improve infant feeding patterns and meet their nutritional needs. Additionally, the results of clustering infant nutrition can also be used to identify groups of infants requiring special attention regarding their nutritional needs, thus minimizing the risk of malnutrition and unhealthy growth in infants.
Overcoming Challenges and Unlocking the Potential: Empowering Small and Medium Enterprises (SMEs) with Data Analytics Solutions Brandy, Susan
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.47

Abstract

In today's data-driven business landscape, Data Analytics (DA) has emerged as a vital tool for organizations to extract insights from their existing data, enabling informed decision-making. While large enterprises have wholeheartedly embraced DA as a strategic asset for operational enhancement, SMEs have been comparatively slower in adopting these transformative solutions. To remain competitive and surpass their rivals, SMEs must recognize the significance of harnessing their data assets effectively to drive decision-making processes. This research aims to delve into the challenges hindering the adoption of DA among SMEs, particularly focusing on issues such as inadequate information infrastructure and limited awareness of the benefits that DA can offer. Furthermore, this study investigates the implementation of data analytics as a practical solution to address these challenges, providing a comprehensive analysis of both the advantages and disadvantages associated with DA adoption in the SME context. By shedding light on the untapped potential of data analytics, this research aims to empower SMEs and equip them with the necessary tools to thrive in today's digitally-driven era of business.
Addressing Inconsistent Sales and Determining Continent-Specific Discounts: A Case Study of CeilBrakes Furniture Retail Company Baghati, Huyanah
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.50

Abstract

This paper highlights the primary business issues faced by CeilBrakes Furniture Retail Company, namely inconsistent sales across different continents. While Europe demonstrates strong sales, North America, Australia, Asia, and Africa exhibit varying levels of mediocre and low sales in terms of the quantity of products ordered. Additionally, determining appropriate discount percentages for each continent poses a challenge. To address the issue of inconsistent sales, the company aims to enhance advertising efforts, improve customer relationships, and analyze trends in continents with low sales (excluding Europe). For determining continent-specific discounts, a solution involves identifying continents with low sales and offering higher discounts accordingly. In the case of Australia, which experiences low sales, CeilBrakes should provide more significant discounts. Despite Asia and Africa already having high discounts, their sales remain low. This situation calls for considering factors beyond retail price reductions, such as cultural influences. To facilitate easier viewing and analysis, a dashboard has been developed to visualize the aforementioned issues. The dashboard enables the identification of trends and patterns, empowering the company to make informed decisions in addressing the observed problems.
Development and Analysis of a Unified Mobile App for Coffee Shop Operations and Ordering Experience: A Proposal Review Maulana, Waleed
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.52

Abstract

This study extends the exploration of ordering apps in the context of coffee shop owners, specifically focusing on the utilization of popular apps like Grabfood and Foodpanda. With the increasing number of coffee shops adopting ordering apps, there arises a clear necessity for a coffee-focused app that can effectively address the unique demands of establishments. The objective of this study is to conduct a comprehensive review of a mobile app specifically designed to streamline the process of ordering coffee in advance, with a paramount emphasis on ensuring its reliability. By developing an app that caters to the specific needs of coffee shops, both owners and customers can benefit greatly. The app will serve as a dedicated platform, connecting coffee enthusiasts with quality coffee shops, while offering a seamless and convenient ordering experience. By providing a high-quality ordering system that encompasses the full range of customization options for beverages, the developed app is expected to significantly enhance the customer experience and ultimately boost sales for the coffee establishments listed on the platform. With a focus on reliability, the app will enable coffee shop owners to efficiently manage orders, minimize errors, and improve overall operational efficiency. Moreover, by fostering a user-friendly interface and intuitive design, the app will engage customers and encourage them to explore new coffee shops, further promoting the growth of the coffee industry. This study will contribute to the existing body of knowledge by highlighting the importance of tailored ordering apps for coffee shops and providing insights into the development and implementation of such apps. The findings will be valuable not only for coffee shop owners seeking to enhance their business operations but also for app developers looking to cater to the specific needs of the coffee industry. Ultimately, the study aims to bridge the gap between technology and the coffee business, fostering innovation and growth in the ever-evolving digital landscape.
Utilizing Linear Regression for Predicting Sales of Top-Performing Products Pratama, matthew
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 3 (2023): September - December 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v1i3.92

Abstract

PT Ajidarma Delta Medika is a company engaged in the sale of medical devices in the city of Bekasi. This company markets a variety of medical device products. Judging from the large number of consumer requests for medical device products based on sales data for the last 3 years, predictions are needed for the best-selling product sales, in order to facilitate the company in planning the supply of stock. To find out the best-selling medical device product sales, data prediction techniques are used with the Linear Regression algorithm. By using the Linear Regression algorithm, the results are obtained to predict the best-selling sales of several products sold at PT Ajidarma Delta Medika. This research produces an accuracy value with the MAPE formula for predicting the best-selling product sales of 14.2%. This shows that the linear regression method is good at predicting sales of medical devices in the following year.

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