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A Systematic Literature Review on the Application of the Philosophy of Science in Addressing Online Gambling Threats : Cybersecurity and Ethical Technology Integration Danang Danang; Siswanto Siswanto; Greget Widhiati
Jurnal Sains dan Ilmu Terapan Vol. 7 No. 2 (2024): Jurnal Sains dan Ilmu Terapan
Publisher : Politeknik Kampar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59061/jsit.v7i2.920

Abstract

This study aims to explore the application of the philosophy of science in developing an ethical, effective, and inclusive cybersecurity model to address the growing threat of online gambling. Using the Systematic Literature Review (SLR) method, 54 articles from reputable databases such as Scopus, IEEE Xplore, SpringerLink, and ScienceDirect were analyzed in-depth. The analysis focused on methodological validity, thematic relevance, contributions to security model development, source credibility, data accessibility, and quality of presented analysis. The results reveal that online gambling platforms leverage technologies such as blockchain, artificial intelligence (AI), and encryption to obscure illegal activities, complicating detection and prevention efforts. As a response, the philosophy of science provides a theoretical foundation to integrate ethical values such as privacy, transparency, and fairness into the development of cybersecurity technologies. Technologies like zero-trust architecture, federated learning, and big data analytics were identified as key tools for building proactive security systems. Furthermore, multistakeholder collaboration among governments, industries, academia, and society is recommended to establish adaptive regulations that foster robust digital security.
Systematic Literature Review on the Application of Blockchain in Enhancing Server Security: Research Methods for Mitigating Ransomware and Malware Attacks Danang Danang; Maya Utami Dewi; Widya Aryani
International Journal of Computer Technology and Science Vol. 1 No. 4 (2024): October: International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i4.186

Abstract

This study aims to explore the application of blockchain in enhancing server security to mitigate ransomware and malware attacks in critical infrastructures such as healthcare, finance, and government sectors. Using a systematic literature review (SLR) approach, the research collects articles from four major databases (IEEE Xplore, Scopus, ScienceDirect, and SpringerLink) published between 2020 and 2024. The search focuses on keywords related to blockchain, server security, ransomware, malware, and attack mitigation. The results indicate that blockchain enhances data integrity, transaction security, and strengthens access control to protect sensitive data. Moreover, integrating blockchain with intrusion detection systems (IDS) and using smart contracts accelerates threat detection and response, allowing for automatic blocking and data recovery from attacks. This technology reduces reliance on manual intervention and increases operational efficiency. However, the main challenges in its implementation include high implementation costs, scalability, and technical complexity. Nevertheless, blockchain offers significant solutions for mitigating ransomware and malware attacks while enhancing the reliability and efficiency of systems. In conclusion, blockchain provides an effective solution for server security and cyber threat mitigation, although challenges related to cost and scalability need to be addressed. Further research is required to develop more efficient blockchain protocols and integrate them with other technologies to enhance threat detection and response speed.
Sistem Monitoring Gas, Suhu dan Kelembapan Ruangan Berbasis IoT: (Studi Kasus Apotek Waras Barokah) Aldo Raditya Pangestu; Danang Danang; Iman Saufik Suasana; Sulartopo Sulartopo; Nuris Dwi Setiawan
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1422

Abstract

Maintaining optimal environmental conditions in pharmacies is crucial for preserving the quality of pharmaceutical products and ensuring the well-being of staff and patients. This study presents the development of a real-time environmental monitoring system based on Internet of Things (IoT) technology, specifically implemented at Apotek Waras Barokah. The system is equipped with a DHT22 sensor to measure ambient temperature and humidity, as well as an MQ-135 sensor to detect harmful gases such as ammonia, carbon monoxide, and carbon dioxide. These sensors are integrated with the NodeMCU ESP8266 microcontroller, which transmits data via WiFi to the Blynk platform for continuous observation. In addition, the system incorporates an automatic notification feature through the Telegram application to promptly alert users when critical thresholds are exceeded. Two fans are activated through relay modules to stabilize room conditions when necessary, while real-time data is also displayed locally using an LCD I2C. Test results indicate that the system performs reliably in detecting environmental anomalies and provides responsive control actions. This research contributes an efficient and scalable prototype that supports safer pharmaceutical storage and has the potential to be adopted in various healthcare settings.
Hybrid Zero Trust Container Based Model for Proactive Service Continuity under Intelligent DDoS Attacks in Cloud Environment Danang Danang; Eko Siswanto; Nuris Dwi Setiawan; Priyo Wibowo
International Journal of Computer Technology and Science Vol. 2 No. 3 (2025): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v2i3.291

Abstract

Growth rapid computing cloud, especially on academic, government, and service platforms. public, has trigger improvement frequency and complexity Distributed Denial of Service (DDoS) attacks. Intelligent DDoS attacks AI based capable copy pattern Then cross user valid, so that difficult detected and mitigated. The majority approach mitigation moment This nature reactive, no scalable, and tends to sacrifice availability service for authorized users. Research​ This aiming develop architecture proactive and adaptive defense​ For ensure continuity service during attack ongoing. Security model proposed hybrid​ integrating Zero Trust Architecture (ZTA), adaptive bandwidth control, and isolation service container -based. Architecture consists of from three layer Main: (1) ZTA Policy Engine which performs verification identity and assessment behavior through tokens and policies intelligent; (2) Adaptive Bandwidth Load Balancer which automatically dynamic separate and arrange Then cross based on reputation and level trust ; and (3) Containerized Service Cluster which groups request to in different containers For user trusted and not known . Components addition such as blockchain -based smart contracts are used For recording request and verification access , as well as lightweight AI module used for profiling then cross in real-time. Simulation results show that this model succeed increase availability service for user trusted during attack , press false positive rate , as well as optimize allocation source power. Integration of zero trust policies with intelligence Then cross and segmentation service in real-time forming framework effective and scalable defense​ to modern DDoS threats . In conclusion , the study This contributes a robust , adaptive , and modular architectural model for maintain continuity cloud services in condition network at risk .
Hybrid CNN GRU Framework for Early Detection and Adaptive Mitigation of DDoS Attacks in SDN using Image Based Traffic Analysis Danang Danang; Indra Ava Dianta; Agustinus Budi Santoso; Siti Kholifah
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.292

Abstract

The threat of Distributed Denial of Service (DDoS) is increasing develop along with increasing use of the Internet of Things (IoT) and Software-Defined Networking (SDN) architecture . Although SDN provides convenience in management network , properties its centralized control make it prone to to flooding attacks that can paralyze controller performance . Detection method conventional , such as approach statistics and machine learning, still own limitations in matter accuracy , high false positive rate , and dependence on extracted features manually . To overcome problem said , research This propose a hybrid deep learning based DDoS detection and mitigation model that combines Convolutional Neural Network (CNN) to extraction feature spatial from RGB and Gated Recurrent Unit (GRU) images for understand temporal correlation between traffic data network . System tested through network test-bed Mininet based with Ryu/Floodlight controller, using simulation DDoS attacks (Hping3, LOIC) and normal traffic (video streaming, HTTP server). Traffic data cross recorded in PCAP format, processed become RGB image measuring 200×200 pixels, and labeled based on type traffic . Evaluation results with metric accuracy , precision, recall, F1-score, and MCC show that the CNN–GRU model has performance more superior compared to baseline approaches such as CNN-only, GRU-only, as well as classical ML methods such as SVM and Random Forest. In addition , the system capable apply mitigation adaptive through automatic flow rule creation on edge switches. Findings This confirm that effective deep learning- based spatial -temporal hybrid approach in increase detection early and response DDoS attacks on SDN networks adaptive and real-time.  
Federated Hybrid CNN GRU and COBCO Optimized Elman Neural Network for Real Time DDoS Detection in Cloud Edge Environments Danang Danang; Maya Utami Dewi; Greget Widhiati
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 2 No. 2 (2025): June : International Journal of Electrical Engineering, Mathematics and Compute
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v2i2.293

Abstract

Improvement amount Distributed Denial of Service (DDoS) attacks in cloud infrastructure and edge computing demands solution adaptive, distributed, and efficient detection in a way computing. Research This propose an optimized Federated Learning (FL) based DDoS detection model using Centroid Opposition-Based Bacterial Colony Optimization (COBCO) to training the Elman Neural Network (ENN). The proposed architecture consists of of two components Main: on the edge node side, a hybrid Convolutional Neural Network–Gated Recurrent Unit (CNN–GRU) model is used to extraction feature local from traffic data network, while on the server side, model parameters from each node are collected and used for training an optimized ENN with COBCO. Approach This aim increase accuracy detection at a time maintain efficiency local data communication and privacy. In progress experimental, model tested use three benchmark datasets: NSL-KDD, CICIDS2017, and CICDDoS2019. The preprocessing process includes feature encoding categorical, normalization numeric, class balancing using SMOTE, as well as validation cross (k-fold). Initial results show that combination of FL, CNN–GRU, and COBCO–ENN produces improvement significant in accuracy and time convergence compared to approach conventional such as PSO, GA, and non- federative models. In addition, the proposed model capable maintain performance detection tall although executed in edge environment with limitations source Power.  Study This give contribution important in development system scalable, privacy-preserving, and adaptive intelligent DDoS detection to dynamics Then cross modern network. Integration of FL and COBCO in ENN training shows potential big for used in implementation real in cloud-edge infrastructure. In addition, the proposed model demonstrates strong scalability and adaptability, making it highly suitable for dynamic and evolving network environments.
Sistem Pendeteksi Bencana Kebakaran Menggunakan ESP32 Dan Arduino Berbasis WEB: Studi Kasus Di Toko Citra Berkah Karangawen Demak Muhammad Ainun Najib; Sulartopo Sulartopo; Dani Sasmoko; Danang Danang; Iman Saufik Suasana
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 1 (2024): Februari: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i1.62

Abstract

Fire is a threat to human safety, property and the environment. With the increasingly rapid development and progress of development, the risk of fires is increasing. Shophouses or shophouses are places that are prone to fires. The increasingly dense population and the construction of office buildings have created a vulnerability in the event of a fire. Preventive efforts must be carried out by each individual and work unit, so that casualties from fire incidents can be minimized. Fires can cause moral, material and even human life losses. Fires that hit public facilities, of course, cause losses to many people. Shophouse fires often occur suddenly due to short circuits, gas explosions or due to sparks from cigarettes/matches. The research carried out this time focuses on creating a fire detection system using ESP32 and Arduino. The system uses three sensors, namely a temperature sensor, a gas sensor and a fire sensor. Temperature sensors are useful for monitoring room temperature conditions, fire sensors are useful for detecting the presence of fire in a fire disaster and gas sensors are useful for detecting the presence of smoke that appears as a result of a fire disaster. This system uses an ESP32 microcontroller and uses the Arduino IDE application. The results of the fire detection system are expected to reduce the occurrence of fire accidents and also losses caused by fire accidents.
Transformasi Proyek Melalui Keajaiban Kecerdasan Buatan: Mengeksplorasi Potensi AI Dalam Project Management Sulartopo Sulartopo; Siti Kholifah; Danang Danang; Joseph Teguh Santoso
Jurnal Publikasi Ilmu Manajemen Vol. 2 No. 2 (2023): Juni: Jurnal Publikasi Ilmu Manajemen
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupiman.v2i2.2477

Abstract

The aim of this research is to discuss the potential of applying AI to improve PM activities and how project managers can objectively comment on issues of responsibility in taking action, accountability in decision making and the still important need for human reasoning. In the context of project management, AI has introduced new methods and techniques that enable project managers to work more quickly and efficiently. However, the unique complexity of projects can become a bottleneck in automating complex activities. The novelty of this research lies in its focus on exploring potential applications of artificial intelligence in project management. This study captures and discusses state-of-the-art research regarding AI applications in PM, providing strong evidence to highlight the benefits of AI techniques in providing intelligent solutions by learning from previous data even with incompleteness and uncertainty in an automated, efficient and reliable manner. The method used in this research is a literature review on the application of artificial intelligence in project management. Related research in the project management domain was collected to prepare a database for review. Then, the current use of AI in real-time projects and enterprises is evaluated for a more in-depth analysis. The research results show that AI has the potential to significantly improve project management processes in developing planning phases, conducting project charters, and integrated change control. The potential application of AI to enhance PM activities can objectively comment on issues of responsibility in taking action, accountability in decision making, and the critical need for human reasoning. AI is anticipated to categorize, measure and forecast potential risks associated with project performance and their relevant impacts, to carry out reliable investigations and analysis in advance regarding broad aspects of project management.
Kajian Wellness Tourism Dari Perspektif Sosial Budaya Zellius Ragiliawan; Hanif Assabib Rosyid; Rizky Ni'ma Febriani; Budi Santoso; Danang Danang
Jurnal Bengawan Solo Pusat Kajian Penelitian dan Pengembangan Daerah Kota Surakarta Vol. 2 No. 1 (2023): Juni : Jurnal Bengawan Solo
Publisher : Badan Riset dan Inovasi Daerah Kota Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58684/jbs.v2i1.32

Abstract

The city of Surakarta with an area of 46.72 km2 is known as a city of arts and culture which presents many historical places, various arts and culture, traditions, religion and various craft creations combined with tourism activities. Referring to the information provided by the Culture and Tourism Office of the City of Surakarta, there are several historical tours in the City of Surakarta, namely the Loji Gandrung Building and the Vastenburg Fort. In these places we can trace the history that has occurred in the city of Surakarta. Besides that, Surakarta City also offers other tourist destinations. Other tourist destinations in Surakarta City, namely culinary tourism, batik village tours, cultural tourism, nature tourism, religious tourism, and many others.
BLACK BOX APPROACH TO MONITORING CONTAINER MICROSERVICES IN FOG COMPUTING Danang Danang; Nuris Dwi Setiawan; Indra Ava Adianta
Journal of Technology Informatics and Engineering Vol. 1 No. 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.141

Abstract

In recent years IoT has developed very rapidly. IoT devices are used to monitor and control physical objects to transform the physical world into intelligent spaces with computing and communication capabilities. Compared to cloud computing, fog computing is used to support latency-sensitive applications at the edge of the network which allows client requests to be processed faster. This study aims to propose a monitoring framework for containerized black box microservices in a fog computing environment to evaluate CPU overhead, as well as to determine the operating status, service characteristics, and dependencies of each container. This study proposes a monitoring framework to integrate computing resource usage and run-time information from service interactions using a black box approach that seeks to integrate service-level information and computing resource information into the same framework. The proposed framework is limited to observing information monitoring after the server receives a request. This study uses JMeter to simulate user actions, which send requests to the server, and this research assumes the user knows the IP address of the server. For container monitoring methods in fog computing, all are indirect monitoring methods. The results of this study indicate that the proposed framework can provide operational data for visualization that can help system administrators evaluate the status of running containers using a black box approach. System administrators do not need to understand and modify target microservices to gather service characteristics from containerized microservices. Regarding future research, it is suggested to expand the exploration of modified system information, and that part of the container management tool code can be pre-tried so that the framework proposed in this study can provide real-time quantitative indexes for the load balancing algorithm to help optimize the load balancing algorithm.