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All Journal Jurnal Ekonomi : Journal of Economic JIK Jurnal Ilmu Komputer Jurnal Pengabdian Masyarakat AbdiMas Jurnal Nasional Komputasi dan Teknologi Informasi Aptisi Transactions on Technopreneurship (ATT) Jurnal Mantik JUKI : Jurnal Komputer dan Informatika Jurnal Teknologi Informatika dan Komputer Indexia Jurnal Eurekamatika IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Media Abdimas Nusantara Journal of Multidisciplinary Science
Binastya Anggara Sekti
Universitas Esa Unggul
Religion Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Public Health Social Sciences Transportation Other

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Analisis Dan Perancangan Keamanan Frontend Dalam Aplikasi Web: XSS dan CSRF Vincent Laurensius Hambaya; Qori Halimatul Hidayah; Nixon Erzed; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Definitely Secure Bank (DSB) is a web application designed to model digital bank financial transactions. In the early stages of development, this DSB application has several security vulnerabilities, including Cross-Site Scripting (XSS) attacks with a non-persistent type on the web help page and Cross-Site Request Forgery (CSRF) attacks on the financial transaction process. In the DSB application and other modern web applications, the most common vulnerabilities encountered are vulnerabilities to XSS and CSRF attacks. XSS attacks occur when someone successfully injects malicious javascript scripts into a web page, which can be executed from the user's browser. While CSRF attacks are attacks to trick users into sending unwanted requests to trusted websites. This study aims to analyze frontend security vulnerabilities on DSB and implement solutions to prevent them. The analysis is carried out by identifying vulnerable points in the application and evaluating their potential for exploitation. The proposed solution to prevent XSS attacks is to apply input sanitation to all user-entered data on the help page. Input sanitation will clean data from malicious scripts before being processed by the system. To prevent CSRF attacks, the proposed solution is to use CSRF tokens when making transactions on DSB. A CSRF token is an encrypted random value that is added to each HTTP request and verified by the server. Implementing these solutions can improve DSB security and prevent exploitation of XSS and CSRF attack vulnerabilities.
Implementasi Deep Learning dalam Pendeteksian Dini Penyakit Alzhaimer Imam Mulyana; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Alzheimer's Disease (AD), is a neurodegenerative condition that develops slowly and generally occurs in older people. The aim of this research is to optimize Deep Learning models so that they can process complex brain imaging data efficiently. The method used involves the use of a CNN (Convolutional Neural Network) network which is trained with a dataset of brain MRI images that have been processed and divided into subsets for training, validation and testing. The data used was taken from the Kaggle platform and processed using augmentation techniques with `ImageDataGenerator`. The research results show that the implemented model is able to achieve high accuracy in detecting structural and functional changes in the brain related to Alzheimer's. The loss and accuracy curves monitored during the training process show a positive trend, with accuracy reaching over 96% in just seven epochs. The main conclusion of this research is that Deep Learning technology has great potential in early detection of Alzheimer's disease, enabling earlier and more effective interventions to prevent or slow the progression of this disease, as well as improving the quality of life of individuals at risk.
Implementasi Business Intelligence dalam Meningkatkan Pembuatan Dashboard dailytracker pada PT.XYZ Ricky Rivandy A’oetpah; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Business intelligence (BI) is a technology infrastructure that analyzes data and generates reports to help managers make decisions. PT XYZ is a company engaged in insurance, which has many employees, especially in the IT and Operations divisions. Problems arise when a lot of employee daily work report data is not decomposed and cannot be analyzed by managers to make a decision. The purpose of this research is to optimize employee daily work report data with business intelligence methods in data visualization so that it can be easily analyzed and can be used as decision-making material for managers. The methods used in the research include analyzing user needs, designing business intelligence systems, implementing business intelligence systems, and testing as well as conducting qualitative methods in the form of interviews as user satisfaction surveys. The results of the application of business intelligence on the dailytracker dashboard at PT XYZ are feasible to use according to employees and managers. And the managers also gave a good response to the strategy implemented which is very informative in displaying data and can assist in analyzing data to make decisions within the company.
Optimalisasi E-Commerce: Rekomendasi Terkomputerisasi Dan Keputusan Pelanggan Melalui Metode SUS Julius Jerry Nolasco; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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The focus of this study is on the development of strategies to optimize E-Commerce performance by enhancing information systems. It highlights recommendation methods, automated calculations, and customer decision-making using the System Usability Scale (SUS) technique. The main objective is to improve the recommendation system, increase information management efficiency, and enhance user satisfaction within an E-Commerce setting. The methods employed include creating a recommendation system based on a product information management model utilizing the K-means algorithm, implementing technology suitability models in accounting information systems, and assessing with a hybrid SUS. Data collection will be crucial in supporting the research's goals. The findings will pinpoint areas for enhancing product recommendation relevance, showcasing user satisfaction, and displaying decision-making effectiveness on the E-Commerce platform. The conclusion stresses the significance of technological integration in shaping the E-Commerce business model and its potential to enrich the online shopping experience. The research proposes that novel marketing strategies in the digital economy era can heighten the competitiveness of E-Commerce companies. This investigation makes a substantial contribution to comprehending and crafting efficient E-Commerce information systems, with vital implications for enhancing business performance and delivering customer value in an ever-changing digital landscape.
Pengembangan Kompetensi Siswa dalam Pembelajaran dengan Menggunakan Metode Game-Based Learning Nicholas Patrick Varian; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Learning in classrooms is often seen as dull and lacking interaction, leading students to lose interest in understanding the material. To combat this, new teaching methods have been introduced, including interactive learning through games. Despite games' potential to boost motivation and engagement, further research is needed to understand Game-Based Learning's (GBL) specific impact on learning experiences, competency development, and student achievements. This study employs a quantitative approach, collecting data via surveys and tests on students using GBL. Hypotheses are tested through statistical analysis. Results reveal GBL's positive influence on students' learning experiences, with increased motivation, engagement, and comprehension of material. GBL also enhances students' competencies and improves learning outcomes. Thus, GBL emerges as an effective method for enhancing learning experiences, developing student competencies, and boosting academic achievements. Integrating GBL into educational curricula is crucial for improving learning quality and student outcomes.
Analisis Performa Dan Optimasi Bandwidth Jaringan Wifi Di Lingkungan Kampus Angga Novita Prasetyo Ningrum; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

WiFi networks have become critical components in supporting academic and administrative activities in higher education institutions. Esa Unggul University, as a growing educational institution, faces challenges in ensuring the quality and reliability of its WiFi network as the number of users and bandwidth requirements increase. This study analyses the performance and optimises the bandwidth of the WiFi network in the Esa Unggul University environment. Through a qualitative approach with a case study, this research collects data through in-depth interviews, direct observations, and technical measurements. Analysis is conducted on access speed, connection stability, and bandwidth capacity in various campus areas. The research results identify several critical points affecting network performance and propose optimisation strategies that include infrastructure upgrades, configuration adjustments, and implementation of effective bandwidth management. The findings and recommendations from this study are expected to improve the quality of internet service at Esa Unggul University, better support academic and administrative activities, and provide valuable insights for other higher education institutions in managing their WiFi network infrastructure.
Penerapan Radio Frequency Identification (RFID) Untuk Efisiensi Inventaris Pada Toko Minimal Irma Tiara; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Minimal is a local Indonesian fashion brand which is famous for its minimalist and modern designs. Minimal's main store is located at Kota Kasablanka Mall, LG Floor, Jl. Casablanca Raya Kav. 88, South Jakarta. Problems arise from inefficient inventory management, such as stock inaccuracies, difficulties in product tracking, and the length of the inventory process. This has a negative impact on the store, including lost potential sales and decreased customer satisfaction. At a minimum, we also don't have an integrated system to manage inventory in real-time across all branches. The aim of this research is to implement an RFID (Radio Frequency Identification) system to increase inventory management efficiency and improve customer service. RFID is a technology that uses radio waves to identify and track objects automatically. Research methods include needs analysis, system design, RFID implementation, and performance evaluation. The results of implementing the RFID system at Minimal stores show a significant increase in inventory accuracy by 98%, a reduction in inventory time by 75%, and an increase in customer satisfaction by 30%.
Studi Literatur: Optimalisasi Pembelajaran Pemrograman dengan Sistem Berbasis AI Rizky Nur Azizah; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Artificial intelligence (AI) has opened up new opportunities in various fields, including education. AI makes it possible to optimize the teaching-learning process in the context of programming learning, which is often considered challenging by many students. This research aims to explore the potential for optimizing programming learning through the implementation of an AI-based online learning system. The method used is a literature study, which involves researching various sources that discuss the use of AI in education, particularly in the context of programming learning. The literature approach includes analyzing and synthesizing data from journals, books, and conference articles that discuss AI techniques such as machine learning, recommendation systems, and real-time feedback. The results show that using AI in online learning platforms can increase student engagement, accelerate feedback, and improve personalization of learning materials. However, there are some challenges when implementing these systems, such as the need for adequate technological infrastructure and teacher training. In conclusion, although AI has a lot of potential to optimize programming learning, effective implementation requires technical and pedagogical considerations. According to this study, further research is needed to overcome implementation barriers and assess the long-term effects of using AI in programming education.
Peningkatan Efisiensi dan Keamanan parkir kendaraan dengan Integrasi KTM berbasis IoT Fathur Andre Fadilah; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The research carried out includes analysis of the manual parking system previously used on campus and evaluation of the implementation of an IoT-based parking system with KTM integration. This research aims to solve problems caused by manual systems such as long queues, inaccurate recording and high security risks. By integrating IoT technology, this system is expected to increase work efficiency and parking safety. The research method used is a qualitative approach where information is collected through in-depth interviews, field observations and document analysis. Interviews were conducted with students, administrative staff and parking attendants. Field observations observe directly how this system is implemented and functions in field conditions. Document analysis is used to complement the information obtained from interviews and observations. The data collected shows that the IoT-based parking system with KTM integration significantly reduces the time needed to search for a parking space and speeds up entry and exit from the parking space. Users, including students, administrative staff, and parking attendants, are very positive about the system. They believe this system will facilitate access and increase the efficiency and safety of campus parking. The research results show that the IoT-based parking system with KTM integration has succeeded in increasing operational efficiency and parking safety at Esa Unggul University. The conclusion of this research is that the implementation of an IoT-based parking system integrated with KTM at Esa Unggul University has had a significant positive impact on parking efficiency and safety. The study also identified opportunities for further development, such as integration with digital payment systems and analysis of parking data to improve capacity planning.
Implementasi Artificial Intelligence dalam Meningkatkan Cyber Security: Analisis ancaman dan Pencegahan Lim Jong Su; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

In today's digital age, cyber threats are becoming more complex and sophisticated.The aim of this study is to analyze the role of artificial intelligence (AI) in improving cybersecurity through threat detection and prevention. By integrating AI techniques such as machine learning and deep learning, cybersecurity systems can detect suspicious behavior patterns and identify threats in real-time.A comprehensive literature review was conducted to explore different AI approaches applied in this field, including anomaly detection analytics, threat intelligence, and automated response. The use of artificial intelligence can significantly improve the accuracy of threat detection and cyber incident response. Moreover, case studies of several organizations that have used AI for cybersecurity have shown increased effectiveness and efficiency in dealing with cyberattacks. However, there are still challenges to overcome, such as: B. Limited training data, interpretability of AI models, and the need for qualified experts. Although AI has great potential to improve cybersecurity, collaboration between technology and human expertise remains crucial to address growing threats.Thus, not only is cybersecurity improving, but there is also an increasing need to develop artificial intelligence (AI) systems that take cybersecurity threats into account in order to attack the security of information systems.
Co-Authors Ady Sutjahyono Agung Mulyo Widodo Agung Mulyo Widodo Ahmad, Ahluddin Saiful Alfiana, Rita Alivia Yulfitri Andri Kurnia Maulana Angga Novita Prasetyo Ningrum Annisa Fitria Antara, Nyoman Putra Anton Nurfendi Arfian, Muhammad Hadi Aulia Ilham Zukri Badie Uddin Bere, Emilianto Sefri BUDI TJAHJONO Darlan, Muhamad Davies Tandianto Dita Chandra Samsiya Dwi Rio Aryanto Euis Sadeli Evi Martaseli Fathur Andre Fadilah Fatwa Arrevi Fatwa Arriva Freddy Harris, Freddy Gusti, Aldo Prima Hani Dewi Ariessanti Hasanah, Diannur Haziro Ulfa Hendry Gunawan Hendry Gunawan Ibnu Hadi Ichwani, arief Ilham Adi Maulana Ilham Banuaji Imam Mulyana Irma Tiara Irsyad Taufiq Ilham Supardi Iwan Setiawan Julius Jerry Nolasco Kalagi, Richard Kevin Maruli Krisogonus Wiero Baba Kaju Lim Jong Su Lisasih, Nin Yasmine Lista Meria Mahatma, Yudi Mohamad Iqbal Ajie Laksono Mohammad Norman Gaza Laksono Muhammad Kaisar Stevan Priadi Nicholas Patrick Varian Nixon Erzed Nixon Erzed Nixon Erzed Nizirwan Anwar Prabowo, Ary Putri Adella Cahyaningtyas Putri Jelita Syifa Eraydya Rafli Al Ihsan Rahaman, Mosiur Rahmahani, Adhining Prabawati Ramadhan, Akmil Maulana Ricky Rivandy A’oetpah Rizki Dwi Sanjaya Rizky Nur Azizah Shefia Anggraeni Siti Nur Kholifah Suherman, Reza Bintang Tri Ismardiko Tri Ismardiko Widyawan Ulum, Muhamad Bahrul Ummanah Ummanah Vanessa, Delivia Vincent Laurensius Hambaya Wahyudi, Endik Wasahua, Idris Widodo, Agung Mulyo Widodo, Agung Mulyo Yanathifal Salsabila Anggraeni Yulhendri Yulhendri Zhafira Anindya Tiaraputri