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Siti Maesaroh
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Journal Collabits
Published by Universitas Mercu Buana
ISSN : 30628601     EISSN : 30466709     DOI : http://dx.doi.org/10.22441/collabits
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Journal Collabits adalah jurnal yang membahas strategi keamanan cyber untuk meningkatkan kinerja dan keandalan dalam implementasi teknologi kecerdasan buatan (AI), kecerdasan bisnis (BI), dan sains data, yang di kelola oleh Fakultas Ilmu Komputer (FASILKOM) terdiri dari dua prodi yaitu Teknik Informatika (TI dan Prodi Sistem Informasi (SI). Dengan pertumbuhan pesat dalam penggunaan teknologi ini, keamanan cyber menjadi semakin penting dalam menjaga integritas, kerahasiaan, dan ketersediaan data. Tulisan ini mengeksplorasi berbagai pendekatan, alat, dan praktik terbaik dalam mengamankan sistem AI, BI, dan sains data, termasuk deteksi ancaman, enkripsi data, manajemen akses, dan pemulihan bencana. Jurnal ini juga menganalisis dampak kebijakan keamanan cyber pada inovasi teknologi dan memberikan rekomendasi untuk meningkatkan keamanan dalam ekosistem digital yang terus berkembang
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 10 Documents
 1 
Search results for , issue "Vol 1, No 3 (2024)" : 10 Documents clear
The Role And Evolution Of Computer Technology In Military Strategy: A Perspective From The World War II Era To The Contemporary Cyber Warfare Era Maesaroh, Siti; Isneni, Syilmi; Adventius.P.H, Nathanael Aurick
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.27315

Abstract

Computer technology has become a crucial element in military strategy from the World War II era to the contemporary Cyber War era. During World War II, early computers were used to crack enemy encryption codes and optimize the trajectories of artillery projectiles. As development progressed, electronic computers emerged, providing faster and greater computing capabilities. In the Cold War era, computers were used in war simulations and the development of missile defense systems. Then, with the advent of the Cyber War era, computer technology became central to military operations, used in cyber monitoring and defense, intelligence analysis, and network operations. The transformation of computer technology from mainframe computers to global networks has changed the landscape of modern warfare, enabling the development of sophisticated cyber weapons and tactics. In this context, this article reviews the use and transformation of computer technology in military strategy from World War II to contemporary Cyber Warfare, highlighting the key role of computers in shaping the dynamics of modern warfare.
Pengembangan Aplikasi Website Pembelajaran untuk Solusi Persamaan Non-Linear Menggunakan Metode Numerik Newton-Raphson dengan Library React.js Prasha, Achmad Ardani; Mutiara, Sabrina Laila; Arfan, Muhammad; Widyatamaka, Erland; Yusuf, Mohamad
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.28141

Abstract

Studi ini berfokus pada pembuatan aplikasi web edukatif yang dirancang untuk meningkatkan pemahaman dan penerapan metode Newton-Raphson, metode numerik dalam menyelesaikan persamaan non-linear. Aplikasi ini dibangun menggunakan React.js, yang memungkinkan antarmuka pengguna yang responsif dan interaktif. Metode Newton-Raphson, yang dikenal karena efisiensinya dalam menemukan akar persamaan non-linear, diimplementasikan dalam aplikasi ini untuk memberikan solusi yang cepat dan akurat. Fitur utama dari aplikasi ini mencakup visualisasi numerik dari proses iterasi, serta tutorial dan dokumentasi komprehensif tentang penggunaan metode Newton-Raphson. Aplikasi ini dievaluasi dengan menguji berbagai persamaan non-linear, yang menunjukkan efektivitasnya dalam meningkatkan pemahaman konseptual dan keterampilan praktis pengguna. Pengembangan di masa depan akan difokuskan pada integrasi metode numerik tambahan dan peningkatan performa aplikasi untuk pengalaman belajar yang optimal.Kata kunci: Newton-Raphson, Persamaan Non-linear, Iterasi, Aplikasi Web, React.js, Metode Numerik
Implementasi Teknologi Enkripsi dalam Perancangan Chatbot Berbasis Gemini AI untuk Keamanan Data Manan, Abdullah Al; Wicaksono, Fajar Satrio; Mulana, Jericho Rayhan; Mustopa, Bagus Banil; Yusuf, Mohammad
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.28459

Abstract

Perkembangan teknologi informasi dan komunikasi telah mendorong inovasi seperti penggunaan chatbot, yang kini semakin populer dalam berbagai bidang. Namun, seiring meningkatnya penggunaan chatbot, isu keamanan data menjadi semakin krusial. Penelitian ini berfokus pada implementasi teknologi enkripsi dalam perancangan chatbot berbasis Gemini AI untuk meningkatkan keamanan data pengguna. Algoritma enkripsi yang digunakan adalah Advanced Encryption Standard (AES) dengan panjang kunci 256-bit. Proses enkripsi melibatkan inisialisasi kunci, enkripsi teks, dan dekripsi teks. Penelitian ini merancang aplikasi berbasis web menggunakan kerangka kerja Flask dan layanan Google Generative AI. Data pengguna dienkripsi dan disimpan dalam database, kemudian didekripsi saat dibutuhkan. Hasil penelitian menunjukkan bahwa penggunaan AES-256 memberikan tingkat keamanan yang tinggi tanpa mengurangi kinerja sistem secara signifikan. Implementasi enkripsi ini diharapkan dapat menjadi panduan praktis bagi pengembang untuk meningkatkan keamanan chatbot mereka.
Design of a Web-Based Human Resource Monitoring Information System on PT Putra Pratama Jaya Mandiri Dini, Siti; Supriyanti, Dedeh; Ananda, Zahra
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.30256

Abstract

PT Putra Pratama Jaya Mandiri was established in 2011 located Jl. Bhayangkara 1 No. 1 Paku Jaya, North Serpong, South Tangerang. PT Putra Pratama Jaya Mandiri is a company engaged in Interior Services which has 2 branch offices located in Tangerang and Bali with a total number of employees of 275 employees. Human resource data management or employee management that is currently running is not running well because it is still done using Microsoft excel so that there are still some problems, namely the absence of a system that is used as a container to collect employee work data reports every day so that HR must collect one by one to find out the results of employee work that has been done every month,  There is no application used to support the optimization of employee data (new, resign, mutation, promotion and retirement) specifically in data storage, data security has not been well maintained because it can still be seen by many people. This research produces a web-based employee data system that can help HR in managing employee data (new, resign, mutation, promotion and retirement). In addition, it helps employees inform the results of work reports that have been done so that OM, HR and division heads can control the results of employee work every day. This system is created using the PHP programming language and Mysql database. This research uses the RAD method as system development and blackbox testing for system testing.
Design of Maintenance Service System With Helpdesk It Support Case Smk Bina Am Ma'mur Pratama, Amri; Padeli, Padeli; Ramadhan, Muhamad Khisbaeni
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.30257

Abstract

SMK Bina Amma'mur has a section in charge of taking care of computers ranging from computer hardware repair and computer software repair, namely the IT helpdesk section. Currently, the process of informing computer repairs that are currently running is still carried out by means of teachers or staff asking for help from the Information Technology department by meeting directly to check problems that occur on computers or laptops, then the IT helpdesk will send a team of technicians to solve the reported problems, if it has been completed, it will be reported back to the IT helpdesk to note that computer repair requests have been made. After checking the problem that occurs on the computer or laptop then the IT department will record the problem in the general ledger and will notify the teacher or staff when it has been resolved via whatsapp media. However, the handling of problems that are running is still not good because the process of recording repair results is still manual so that it affects the performance of the IT department. This can have a negative impact, namely there are problems recording data repeatedly, the process of searching for computer repair data takes a long time because you have to search one by one for repair request data in books, there are often errors in making reports so that the reports made are not the same as the computer repair process. This research resulted in an IT helpdesk system that aims to help the IT department manage IT helpdesk data better. This research uses the PIECES analysis method, design using UML and blackbox testing system. The IT Helpdesk system is created using PHP programming language and MySQL database.
Implementation of The Naive Bayes Algorithm on Online Game Addiction and Its Impact on Students Akbar, Shafrizal Fadillah; Angwarmasse, Thanel Richard
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.27301

Abstract

This research aims to implement the Naive Bayes algorithm in analyzing online game addiction and its impact on individuals. Online gaming addiction has become a global phenomenon with significant psychological, social, and academic implications. For this reason, an effective analytical tool is needed to identify the factors that contribute to this addiction and its impact. The Naive Bayes algorithm was chosen because of its ability to carry out classification based on probability, which is very suitable for handling complex and diverse data. This research collects data from questionnaires that cover demographic aspects, frequency of play, duration of play, and perceived impact. The analysis results show that the Naive Bayes algorithm has quite high accuracy in classifying individuals who are addicted to online games. In addition, this study identified several key factors that are closely related to addiction, such as age, gender, and motivation to play. The most prominent impacts of this addiction include decreased academic performance, disturbed sleep patterns, and problems with social relationships. With the implementation of the Naive Bayes algorithm, it is hoped that it can contribute to prevention and early intervention efforts against online game addiction. This research also opens up opportunities for further development in the use of other machine-learning techniques for digital behavior analysis.
Comparative Analysis of Performance Between KNN and C5.0 Algorithms in Lung Cancer Disease Detection Maesaroh, Siti; Fatcha, Ibka Anhar; Ramadhan, Fikri
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.27285

Abstract

Lung cancer is a disease characterized by the growth of abnormal cells in the lungs that can spread to other parts of the body. In practice, medical teams will usually evaluate a patient's symptoms conventionally, which is highly inefficient and time-consuming, especially if there are a large number of patients. This manual evaluation process can cause delays in diagnosis and treatment, and increase the risk of errors. Therefore, this research will discuss lung cancer detection using the K-Nearest Neighbors (KNN) algorithm and the C5.0 algorithm in order to solve the problems previously described. The use of the K-Nearest Neighbors (KNN) algorithm and the C5.0 algorithm was chosen because these two algorithms have the ability to process complex data and produce accurate models. The results of this study will show a comparison of which performance is much better used to accurately detect lung cancer based on the amount of training data available, and it can be known that the lung cancer detection process can be done more quickly and efficiently, using the K-Nearest Neighbors (KNN) or C5.0 algorithm to improve diagnosis accuracy. The results show that the KNN algorithm is superior to the C5.0 algorithm specifically for lung cancer detection.
Clinic Management System Saputra, Gilas Adi; Budiarto, Sabar; Pramadhan, Rivaldiansyah; Rivai, Adriean Baihaqi; Athalla, Raffi Zaidan
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.31197

Abstract

A Clinic Management System (CMS) is a web-based application designed to streamline the management of clinic operations, including patient registration, appointment scheduling, medical records, and billing. The system utilizes PHP for server-side scripting, allowing for dynamic content creation and seamless interaction with the database. MySQL is used as a relational database management system (RDBMS) to securely store and manage patient, appointment, and medical record data. Visual Studio Code (VS Code) serves as the primary integrated development environment (IDE) for building and debugging applications, offering features such as syntax highlighting and version control integration. This CMS aims to increase efficiency, reduce administrative errors, and improve the overall experience for patients and healthcare providers.
Design Of Web-Based Customer Menu Ordering Information System Case Study: Coffee Luck Coffee Shop Abdurohman, Dudun; Saputra, Eggi Firman; Munahar, Harris
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.30262

Abstract

Technological developments make it easier for users to carry out all tasks such as food and beverage ordering process. One of the technologies used is a computer. Computer is one of the machines in charge to help human work so that the job can be done quickly.  Kedai COFFEE LUCK is one of the places engaged in the culinary that is located in Jl. Ks. Tubun No. 86, RT. 004/RW. 003, Koang Jaya, Pasar Baru, Karawaci, Tangerang City, Banten 15112. Currently the food and beverage ordering process at COFFEE LUCK Store still uses paper for the recording of its order transactions. Conventional system like this is less effective, which raises the problem that the food ordering paper often disappear because the paper ordering only stored in the cashier table, took a long time to build a food ordering report because it must recap the booking paper in one by one, there is still a difference in the amount of payment with the amount of food ordering due to calculation errors. Based on the problems that occur at this time, in need of food and beverage ordering system that can help the cashier in managing the food and beverage order data. This research uses Object Oriented Analysis (OOA) analysis methods and system design using Unified Modelling Language (UML) tools. Collection through observation stages, interviews with stakeholders and library studies. This food and beverage ordering system is made using the PHP programming language and Mysql database. This research resulted in a Web-based customer menu ordering system with the aim to increase time efficiency in managing food and beverage order data and to reduce the difference in payment and booking amounts.
Neural Network Classification to Determine the Likelihood of Diabetes Using Python Programming Language Hidayah, Rafif Syari; Istanto, Yudha Andika
Journal Collabits Vol 1, No 3 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i3.27300

Abstract

Diabetes is a global health problem that affects millions of people worldwide. Predicting a person's risk of developing diabetes can be an important first step in disease prevention and management. In this study, we propose the development of a predictive model for diabetes using Neural Network (NN) technique with implementation using Python. The data used in this study consists of clinical information that includes factors such as pregnancy, glucose, blood pressure, skin thickness, insulin, BMI, diabetes pedigree function, and age. The model development process involves data pre-processing, selection of relevant features, model training, and performance evaluation using appropriate metrics. The experimental results show that the developed NN model has a good ability in predicting diabetes risk. The main contribution of this research is the use of NN techniques and Python coding in the development of predictive models for diabetes, which can provide useful guidance for medical practitioners in supporting disease prevention and management efforts. Future studies can extend this research by considering additional factors and improving the accuracy of the model by using more complex approaches. Keywords: Diabetes, Prediction, Neural Network, Python coding, Predictive model, Model development, Data pre-processing, Performance evaluation, Disease prevention, Disease management

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