cover
Contact Name
Siti Mutrofin
Contact Email
sitimutrofin@untag-sby.ac.id
Phone
+6287852416880
Journal Mail Official
jitcs@untag-sby.ac.id
Editorial Address
Department of Information Systems and Technology, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya, No. 45 Semolowaru St., Semolowaru Dist., Surabaya, East Java, Indonesia 60118
Location
Kota surabaya,
Jawa timur
INDONESIA
Journal of Information Technology and Cyber Security
ISSN : 29873878     EISSN : 2987386X     DOI : https://doi.org/10.30996/jitcs
Journal of Information Technology and Cyber Security (JITCS) is a refereed international journal whose focus is on exchanging information relating to Information Technology and Cyber Security in industry, government, and universities worldwide. The thrust of the journal is to publish papers dealing with the the design, development, testing, implementation, and/or management of Information Technology and Cyber Security, and also to provide practical guidelines in the development and management of these systems. The journal will publish papers in Information Technology and Cyber Security in the areas of, but not limited to: 1. Enterprise Systems (ES): o Enterprise Resource Planning, o Business Process Management, o Customer Relationship Management, o System Dynamics, o E-business and e-Commerce, o Marketing Analytics, o Supply Chain Management and Logistics, o Business Analytics and Knowledge Discovery, o Production Management, o Task Analysis, o Process Mining, o Discrete Event Simulation, o Service Science and Innovation, and o Innovation in the Digital Economy. 2. Information Systems Management (ISM): o Software Engineering, o Software Design Pattern, o System Analysis and Design, o Software Quality Assurance, o Green Technology Strategies, o Strategic Information Systems, o IT Governance and Audits, o E-Government, o IT Service Management, o IT Project Management, o Information System Development, o Research Methods of Information Systems, o Adoption and Diffusion of Information Technology, o Health Information Systems and Technology, o Accounting Information Systems, o Human Behavior in Information System, o Social Technical Issues and Social Inclusion, o Domestication of Information Technology, o ICTs and Sustainable Development, o Information System in developing countries, o Software metric and cost estimation, o IT/IS audit, and o IT Risk and Management. 3. Data Acquisition and Information Dissemination (DAID): o Open Data, o Social Media, o Knowledge Management, o Social Networks, o Big Data, o Web Services, o Database Management Systems, o Semantics Web and Linked Data, o Visualization Information, o Social Information Systems, o Social Informatics, o Spatial Informatics Systems, and o Geographical Information Systems. 4. Data Engineering and Business Intelligence (DEBI): o Business Intelligence, o Data Mining, o Intelligent Systems, o Artificial Intelligence, o Autonomous Agents, o Intelligent Agents, o Multi-Agent Systems, o Expert Systems, o Pattern Recognition, o Machine Learning, o Soft Computing, o Optimization, o Forecasting, o Meta-Heuristics, o Computational Intelligence, and o Decision Support Systems. 5. IT Infrastructure and Security (ITIS): o Information Security and Privacy, o Digital Forensics, o Network Security, o Cryptography, o Cloud and Virtualization, o Emerging Technologies, o Computer Vision and Image, o Ethics in Information Systems, o Human Computer Interaction, o Wireless Sensor Networks, o Medical Image Analysis, o Internet of Things, o Mobile and Pervasive Computing, o Real-time Systems and Embedded Systems, o Parallel and Distributed Systems, o Cyber attacks, o Machine learning mechanisms for cyber security, o Modern tools for improving cyber security, o Emerging trends in cyber security, o Cyber security in Internet of Things (IoT), and o Cyber security in Cloud.
Articles 5 Documents
Search results for , issue "Vol. 1 No. 1 (2023): January" : 5 Documents clear
Recommendation System Using the K-Nearest Neighbor Approach: A Case Study of Dual Camera Quality as a Smartphone Selection Criterion Pasha, Parcelliana Binar; Muflihah, Yusrida
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.7559

Abstract

Many smartphones today need to be more precise about choosing one that suits the user's needs. In fact, smartphone sellers sometimes need help recommending smartphones that suit buyers' needs. Generally, buyers search for smartphone specifications with keywords they desire, but the results appear different from what they expected. Users need the main specifications, such as Random Access Memory (RAM) and Read Only Memory (ROM) capacity, battery, and high camera quality. This research aims to implement the K-Nearest Neighbor (KNN) algorithm for recommendation smartphone selection based on the criteria mentioned. The data test results show that the combination of KNN with four criteria has good performance, as indicated by the accuracy, precision, recall, and f-measure values of 95%, 94%, 97%, and 95%, respectively.
Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia Fauzan, Ammar; Rahayu, Dania Gusmi; Handayani, Annisa; Tahyudin, Imam; Saputra, Dhanar Intan Surya; Purwadi, Purwadi
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.7572

Abstract

The market of Fast-Moving Consumer Goods (FMCG) companies in Indonesia is enormous. Unilever has 400 brands in more than 190 countries, making it a global business that is as influential in the consumer product market as it is in Indonesia. Sales forecasting at this company is very useful for planning expenses and the company's total costs on the business strategy. This study uses trend moment method to forecast the sales and earnings of Unilever Indonesia companies at the end of the year. This article aims to test the performance of the trend moment method calculation on the prediction of net sales and profits in FMCG companies. At the end of the analysis process, it can be concluded that forecasting using trend moment method is going very well. This indicator of success is shown by the error level of MAPE, which is below 10%.
Delivery Route Estimation on a Web-Based Restaurant Delivery System Using Greedy Algorithm Wando, Carmelita Margaretha Jawa; Dzikria, Intan
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.7611

Abstract

Food delivery application services have been significantly developed in Indonesia. However, several areas have not received application services like this. Orders made by several restaurants still use social media such as Whatsapp, Facebook, and cell phones. Traditional ordering does not have sufficient means to calculate the cost of delivery of orders resulting in cost-efficiency problems. In addition, order delivery routes are a problem for couriers who have to deliver several orders at once. This research builds a web-based restaurant delivery system by applying a greedy algorithm to optimize routes and shipping costs. The results of this study indicate that the greedy algorithm can determine the best route for couriers to make deliveries so that shipping costs become lower. This research contributes as one proof of the application of the greedy algorithm to business problems and restaurants may use the resulting system to increase the effectiveness of order delivery.
A Child Growth and Development Evaluation Using Weighted Product Method Januantoro, Ardy; Mandita, Fridy
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.7613

Abstract

Child development is one of the factors that must be considered in improving a country's education. The level of maturity of human resources is able to maximize starting from childhood. The guidebook of the Ministry of Education and Culture of the Republic of Indonesia (Kemendikbud RI) in 2018 contained six indicators to assess children's learning ability, namely: 1) Moral, 2) Social, 3) Language, 4) Cognitive, 5) Motor, and 6) Art. This study implements these indicators to evaluate children's growth and development. The evaluation method uses the Weighted Product Method (WPM). WPM provides a ranking of the result of the evaluation. In addition, WPM also has an assessment of Beneficial and non-beneficial as a more relevant assessment between indicators. Data were collected by questionnaire at kindergarten schools with the respondents' age average of 5-6 years. The results will be calculated with indicators criteria weights given. The test results recommended for students between 0.65 to 0.62 are as follows: Mahmud, Diko, Cindy, Denny, and Riko. The kindergarten manager can use these recommendations to increase the student's aptitude.
The Utilization of Information System for Crime Rate Modelling in Surabaya Using K-means Supangat, Supangat; Sholiq, M. Mudhafiq
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.7676

Abstract

This study aims to model the crime rate in the city of Surabaya using the k-means clustering method. The data used is crime data that occurred in Surabaya in previous years, which includes the type of crime, location of crime, and crime rate. The k-means clustering method is used to classify crime data in the Surabaya area for 2020-2022 consisting of cluster 3, namely areas with moderate crime rates covering 6 sub-districts (1,260 cases), cluster 1 with areas with high crime rates, namely 12 sub-districts with 2,363 cases, and cluster 2 areas with low crime rates consisting of 13 districts with 2,178 cases based on data on the number of crimes. The geospatial visualization system is used to visually display modeling results, making it easier for interested parties to identify the location of a crime. The results of this study are expected to provide useful information for interested parties, such as the police and the community, in taking preventive action regarding crime rates in Surabaya.

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