Destination Address Research Articles

Transactions Using the Cod (Cash on Delivery) Payment Method: Consumer Protection Legal Perspective

The widespread use of e-commerce services by the public shows that buying and selling activities that were previously carried out conventionally have become activities that can be accessed only via smartphones, laptops/computers with an internet network. However, it is not uncommon for consumers to object because goods purchased using the cash on delivery or COD payment method do not match the order when they arrive at the delivery destination. This illustrates that one side of the consumer is the party that is seriously disadvantaged. Meanwhile, business actors still make a profit from selling the goods they make. Based on the problems above, the problem formulation is how to legally protect consumers for losses that can be suffered in transactions via COD and what measures can be taken by consumers for losses suffered in transactions via COD. This research method uses normative legal research. The approach used is the statutory and regulatory analysis approach which is used to answer the problems that have been previously formulated. The analysis technique is carried out qualitatively by describing the issues and then organizing them systematically and connecting them with the legal materials that have been found. Cash on Delivery (COD) means pay on delivery is a payment method that is in great demand in e-commerce. As the name suggests, this payment method allows buyers to make payments in cash when the order arrives at the destination address. Trading by e-commerce actually has a legal basis for ordinary trade. Or in other words, e-commerce is conventional trade that is special because the role of media and electronic devices is very dominant. Transactions using the COD payment method were initially present to facilitate online buying and selling transactions. However, this mechanism also has the potential to cause significant losses for consumers. Enforcement of consumer rights is a necessity in order to ensure legal certainty to provide protection to consumers, including in transactions that use the COD payment method as regulated in Article 4 of the Consumer Protection Law. There are various reasons for goods being returned by consumers who have used COD payments such as products. damaged, non-functioning products, insufficient products, incomplete orders, inappropriate products, and counterfeit products. For disputes that arise due to the COD system, there is a method that has been determined by each marketplace to submit an objection or request a return of goods to the business actor by attaching proof that the goods received do not meet consumer expectations. Meanwhile, consumers who feel their rights have been violated can complain and process their case legally at the Consumer Dispute Settlement Agency (BPSK) or through court.

Design and Implementation of Optimized PCI Express Physical Layer for High-Speed and Low-Latency Data Transfer

The PCIe (Peripheral Component Interconnect Express) Protocol is crucial for establishing high-speed data communication between computer peripherals, such as graphics cards and network cards etc. This communication protocol is transmitting data in packet format, with each packet containing both data and destination address and other essential information for accurate data delivery. This paper focused on Physical Layer to achieve High-Speed Data Transmission by reducing delay parameter. To minimize disturbances and enhance reliability, the physical layer uses scrambling technique and an 8b – 10b encoding technique is used for synchronization and error detection. Additionally, SIPO and PISO converts data format to improve efficiency and accuracy. The design is implemented using the Cadence compiler targeting 45nm process technology. This design is delay efficient resulting in path delay of 5.0ns and the operating frequency of 200MHz, power consumption of 1.2mw and an area of 1999µm².

Secure digital wallet by using QR code: mapping of mobile payment in partially connected environment

Mobile payment is rising attention worldwide to pay for items from sender to receiver. QR (Quick Response) code technology relies on scan-and-pay techniques, does not require specific hardware, and allows a sender to easily scan the destination address of the payment directly from the receiver’s smartphone. Existing QR (Quick Response) Code-based payment solutions require full internet connectivity for transactions. Sometimes, the user does not have internet for mobile payment. To resolve this issue an innovative hybrid method is proposed which uses web and mobile-based applications for E-payment and transactions using QR (Quick Response) Code in a partially connected environment. Online senders can pay by scanning the QR code provided by the offline receiver. A prototype of the proposed model has been developed as Cloud Sarafa System (CSS) which offers a flexible solution. A Prototype of the proposed model tested via use cases and test cases. Data was collected from 350 participants to evaluate the performance report against the prototype of the proposed model which endorsed positive.

Decentralized Anonymous IoT Data Sharing with Key-Private Proxy Re-Encryption

Secure and scalable data sharing is one of the main concerns of the Internet of Things (IoT) ecosystem. In this paper, we introduce a novel blockchain-based data-sharing construction designed to ensure full anonymity for both the users and the data. To share the encrypted IoT data stored on the cloud, users generate tokens, prove their ownership using zk-SNARKs, and target the destination address anonymously. To tackle the privacy concerns arising from uploading the data to the cloud, we use key-private re-encryption and share only the necessary information with the proxy. As the first time in the literature, we have integrated a token-based blockchain and a key private proxy re-encryption to achieve a fully anonymous data sharing scheme. Furthermore, we provide security proof of our proposed scheme is secure against existential forgery under chosen-plaintext attacks, under eDBDH assumption in the random oracle model.

SPC-Indexed Indirect Branch Hardware Cache Redirecting Technique in Binary Translation

In the domain of process virtual machine (PVM) binary translation, the difference in address space layout between the guest program and the translated program requires the recalculation of jump instruction targets, resulting in suboptimal execution efficiency. This paper presents a novel method called SPC-Indexed Indirect Branch Hardware Cache Redirecting (SPCIC) technique. SPCIC utilizes specialized branch instruction to represent indirect branches from guest programs while frequently-used target addresses are cached in a customized hardware mapping table. When translating an indirect branch, SPCIC queries the jump target cache first to achieve a fast redirection unless the destination address is not cached. Besides, SPCIC merely falls back to the software-based remapping approach when the query fails, improving the translation efficiency to the greatest extent. SPCIC is implemented on the QEMU platform to accelerate the translation of ARM payloads into RISC-V. Experiments are carried on SPEC2006 to demonstrate the effectiveness of SPCIC for reducing the runtime overhead of indirect branch translation. The experimental results indicate up to 11% average improvement and 35% maximum improvement are obtained on the selected benchmark.

Enhancing predictive models for illicit activities in the Bitcoin transaction network using advanced graph analytical techniques

The Elliptic dataset compiles a comprehensive history of Bitcoin transactions, integrating both anti-money laundering (AML) tags and distinct graph network features. Given the nature of the Bitcoin transaction networka complex, weakly interconnected structureleveraging graph analysis techniques for its study holds immense potential, especially in the realm of detecting illicit activities like hacking, drug trades, gambling, and more. A detailed examination of the Elliptic dataset, encompassing transaction amounts, frequencies, source and destination addresses, sheds light on the inherent structure and peculiarities of the Bitcoin transaction ecosystem. By conceptualizing this transactional landscape as a graph, a slew of analytical attributes emerge: node degree distribution, community architecture, centrality measures, and so forth. Such attributes pave the way for the creation of predictive models that can pinpoint and prognosticate potential unlawful trade actions. Several computational models have been employed on the Elliptic dataset, such as Logistic Regression (LR), Random Forest (RF), Multilayer Perceptrons (MLP), and Graph Convolutional Networks (GCN). The authors of this particular study delve into augmentations of the GCN model, juxtaposing the efficacy of the original GCN model against their enhanced algorithm within the context of the Elliptic dataset.

A deep learning technique to detect distributed denial of service attacks in software-defined networks

Software-Defined Network (SDN) is an established networking paradigm that separates the control plane from the data plane. It has central network control, and programmability facilities, therefore SDN can improve network flexibility, management, performance, and scalability. The programmability and control centralization of SDN have improved network functions but also exposed it to security challenges such as Distributed Denial of Service (DDoS) attacks that target both control and data planes. This paper proposes an effective detection technique against DDoS attack in SDN control plane and data plane. For the control plane, the technique detects DDoS attacks through a Deep Learning (DL) model using new features extracted from traffic statistics. A DL method (AE-BGRU) for DDoS detection uses Autoencoder (AE) with Bidirectional Gated Recurrent Unit (BGRU). The proposed features for the control plane include unknown IP destination address, packets inter-arrival time, Transport layer protocol (TLP) header, and Type of service (ToS) header. For the data plane, the technique tracks the switch's average arrival bit rate with an unknown destination address in the data plane. Then, the technique detects DDoS attacks through a DL-based model which also uses AE with BGRU. The proposed features in the data plane include the switch's stored capacity, the average rate of packets with unknown destination addresses, the IP Options header, and the average number of flows. The dataset is generated from feature extraction and computations from normal and attack packets and used with the classifier. Also, additional Machine Learning (ML) methods are used to enhance the detection process. If the model detects an attack, the technique mitigates DDoS effects by updating the user's trust value and blocking suspicious senders based on the trust value. The experimental results proved that compared to related techniques, the suggested method had a higher accuracy and lower false alarm rate.

Operational planning of integrated urban freight logistics combining passenger and freight flows through mathematical programming

Recently, more environmentally friendly urban logistics (UL) services have emerged based on the integration of freight deliveries into passenger bus networks to perform UL activities within cities. The aim is to reduce the number of combustion powered vehicles operating within cities, thus improving the city quality of life in terms of pollution, noise, traffic congestion etc. This paper addresses the operational planning of an UL service where freight is dropped by clients at bus hubs located outside the city center, transported by buses to one of their stops located in the city center, and delivered to the destination address by a last mile operator (LMO). To support the operational planning of the service covering the entire logistics process (from the reception of freight delivery requests until the delivery of the requests on their destination), five operational objectives are considered and, for each objective, an Integer Linear Programming (ILP) model is proposed. The objectives cover the perspectives of the bus network operator and of the LMO and some objectives address the robustness of the operational planning solutions to failures. Additionally, five operational planning cases of practical interest where two of the previous objectives are lexicographically optimized are also addressed including a description of how they are solved with the proposed ILP models. We demonstrate the merits of the different operational planning methods with different generated instances whose characteristics allow the assessment of the impact of different parameters on the results obtained by the proposed models when solved with a standard solver.

Algoritma Hopfield dalam menentukan rute tercepat untuk pendistribusian telur kepada konsumen

ENJ Poultry Shop is a business that operates in the field of egg distribution. The main problem faced is determining delivery routes, which are still less effective. The focus of this research is optimization to determine the fastest route through implementing the Hopfield algorithm in the application. With the Hopfield algorithm, it is hoped that it can provide a solution for finding the shortest route to distribute eggs to consumers. This research is quantitative, where the analysis is carried out by comparing the results of manual calculations with the results of calculations using the application. Data collection was carried out at a number of locations, which were used as delivery destination addresses. The Hopfield algorithm is applied by determining the delivery point to be addressed, then measuring each delivery distance so that an estimate of the distance at each point is obtained. After obtaining all the data, it is continued with calculations using the Hopfield algorithm. Based on the research results, it can be concluded that the implementation of the application works better, resulting in the fastest distance and time in determining the egg delivery route. By optimizing distribution time, it is possible to increase marketing and provide consumer satisfaction.

User Profiling Behaviour and Activity of Persistent Surveillance of User Activity in Complex Networks

The objective of this paper is to study the behaviour of multiple user activity on network traffic. The traditional approach of using the source IP address as a tracking identifier does not work when used to identify mobile users. Insider misuse has become a significant issue for organizations. Traditional information security has focused on threats from outside rather than employees. A wide range of concepts has been undertaken to develop approaches to detecting the insider. Recent efforts to address this problem by exclusively not relying on web browsing behaviour, collecting data from routers, and predicting human psychology (when a router receives a packet, the router checks its routing table to determine if the table lists the destination address in the header. If the table does not contain the destination address, the router forwards the packet to another router that is listed in its routing table). This paper builds the concept of tracking behaviour-based identification of multiple user activity on a router. Here we find out the traffic of HTTP or HTTPS Protocol and the Results are promising. find out as the result we are capable of tracking human psychology.

Counseling on Transportation Logistics Curriculum Level III Jabodetabek Region

Logistics transportation manages and provides transportation facilities and infrastructure for smooth logistics distribution. Logistics activities or freight forwarding services refer to the management and distribution of logistics goods obtained from users, stored in logistics warehouses, sorted shipments, and transported and sent to the destination address. Logistics activities have an important role in a business company, but the important role of logistics transportation is also major in distributing goods. This activity aims to produce graduates of experts who are reliable and best in transportation and logistics and have a reputation for ready-to-use labor. The methods used are lectures, discussions, and questions and answers. The implementation of the training activities of the participants was no obstacle in conducting counseling, and the internet connection was not interrupted. In support of infrastructure, facilities are adequate, namely the availability of laptops or personal computers from participants so that all participants can take part in counseling optimally

The Effect of Orientation Strategy on Logistics Performance with Supply Chain Integration as a Mediation Variable

Ports have a big role in the logistics system. Because at the port various logistics activities occur such as transportation activities, loading, and unloading of goods, inspection, storage, and so on. So the performance of the port plays an important role in the speed of delivery of logistics goods. Furthermore, for the transportation of logistics goods, trucking is one of the options that can be chosen to deliver goods from the port to the customer. The process of shipping logistics goods by trucking begins with the pick-up of goods at the port by a predetermined truck. After that, the truck will take the goods to the destination address specified by the customer. This study aims to examine how the influence of supply chain orientation on logistics performance through supply chain integration as an intervening variable, a research study was conducted on manufacturing companies engaged in consumer goods processing services that use coal transportation services. The research method used in this study is quantitative using data collection techniques, observation, surveys, and primary data analysis. The survey is conducted by giving questionnaires or interviews to respondents to collect data on the variables studied. The research sample was 135 samples as owners or managers in manufacturing companies engaged in consumer goods processing services that use goods transportation services at the port of Central Java. Research analysis tools using AMOS 22.00 software with the SEM (Structural Equation Modeling) method. The results showed that there was a significant influence of supply chain orientation on logistics performance with a p-value of 0.036 and a CR value of 2.092 (can receive H1). There is a significant positive influence of supply chain orientation on supply chain integration with a p-value of 0.009 and a CR value of 2.625 (can accept H2). There is a significant effect of supply chain integration on logistics performance with a p-value of 0.015 and a CR value of 2.441 (can accept H3).

IMPLEMENTASI KOMUNIKASI DATA MENGGUNAKAN PROTOKOL RF24NETWORK PADA SISTEM PEMANTAUAN KONDISI RUANGAN BERBASIS JARINGAN SENSOR NIRKABEL

Wireless Sensor Network (WSN) is an infrastructure consisting of a number of sensor nodes that are distributed in certain environments and coordinated using a wireless network. WSN can be implemented using the nRF24L01 module. One protocol that supports the nRF24L01 module is the RF24 protocol. But for the implementation of monitoring the vast room conditions this protocol has the disadvantage of using a single-hop mechanism. So that for a large area range, multi-hop mechanism is needed. The RF24Network protocol is a protocol designed to meet the needs of RF24-based multi-hop mechanisms, users simply build a header that contains the correct destination address and the network will forward it to the destination node. In accordance with the above problems, the authors implement sensor nodes using Arduino Nano as Microcontroller, nRF24L01 for communication media and DHT11 to acquire sensor data. From the implementation results obtained network performance for monitoring the condition of the room with the level of accuracy of data transmission and delay as follows. Single-hop data transmission mechanism without barrier distance 3-12 meters 100% accuracy, 15 meters 70%, 18 meters 40%, 21 meters 0% with a total average delay of 145 ms, with a distance barrier of 3-9 meters 100% accuracy , 12 meters 60%, 15 meters 30%, 18 meters 0% with a total average delay of 276 ms. The multi-hop mechanism of data transmission accuracy reaches 100% with average delay (1 hop without barrier 110 ms with a total distance of 24 meters, with a barrier of 270 ms with a total distance of 18 meters. 2 hops without barrier 270 ms with a total distance of 36 meters , with a 350 ms barrier with a total distance of 27 meters, 3 hops without a 280 ms barrier with a total distance of 48 meters, with a barrier of 260 ms with a total distance of 36 meters)..

Hardware Trojan Mitigation Technique in Network-on-Chip (NoC)

Due to globalization in the semiconductor industry, malevolent modifications made in the hardware circuitry, known as hardware Trojans (HTs), have rendered the security of the chip very critical. Over the years, many methods have been proposed to detect and mitigate these HTs in general integrated circuits. However, insufficient effort has been made for hardware Trojans (HTs) in the network-on-chip. In this study, we implement a countermeasure to congeal the network-on-chip hardware design in order to prevent changes from being made to the network-on-chip design. We propose a collaborative method which uses flit integrity and dynamic flit permutation to eliminate the hardware Trojan inserted into the router of the NoC by a disloyal employee or a third-party vendor corporation. The proposed method increases the number of received packets by up to 10% more compared to existing techniques, which contain HTs in the destination address of the flit. Compared to the runtime HT mitigation method, the proposed scheme also decreases the average latency for the hardware Trojan inserted in the flit’s header, tail, and destination field up to 14.7%, 8%, and 3%, respectively.

A bibliometric analysis of research on tourism content marketing: Background knowledge and thematic evolution

Content marketing is becoming an important trend in the tourism industry and is attracting the attention of many stakeholders. Previous studies have sporadically highlighted only some content marketing aspects, but none comprehensively described the topic. To fill this gap, this study adopts a comprehensive approach by combining two bibliometric co-citation and co-keyword analysis methods of 659 articles on content marketing in travel sectors. The co-citation results indicate that tourism content marketing research has been concentrated on the themes of (1) the impact of electronic word of mouth (eWOM) and word of mouth (WOM) on business performance; (2) the role of social media, user-generated content (UGC) and destination image formulation; (3) the impact of eWOM and UGC on the decision-making process; as well as (4) opportunities and challenges. Additionally, based on the co-keyword analysis, hot research topics are explored, including online review implementation; UGC implementation; communication and information search; customer behavior prediction model; the decision-making process; and issues related to user experience, quality, and management. Among these, UGC implementation is the most likely trend that researchers can develop in the future. In addition, the influence of other types of UGC (e.g., user-generated travel videos) is a promising avenue for future research. This study will help researchers understand the role and influence of tourism content marketing. Furthermore, tourism marketers can use content marketing to restore destination image and address last-minute booking issues after the COVID-19 pandemic.

Sistem otkrivanja anomalija u mreži na bazi NetFLow protokola primenom mašinskog/dubokog učenja

Introduction/purpose: Anomaly detection-based Network Intrusion Detection Systems (NIDSs) have emerged as a valuable tool, particularly in military fields, for protecting networks against cyberattacks, specifically focusing on Netflow data, to identify normal and abnormal patterns. This study investigates the effectiveness of anomaly-based machine learning (ML) and deep learning (DL) models in NIDSs using the publicly available NF-UQ-NIDS dataset, which utilizes Netflow data, with the aim of enhancing network protection. Methods: The authors Sarhan, M., Layeghy, S., Moustafa, N. and Portmann, M. in the conference paper Big Data Technologies and Applications, in 2021, involve a preprocessing step where 8 features are selected for the training phase out of the 12 available features. Notably, the IP source and destination addresses, as well as their associated ports, are specifically excluded. The novelty of this paper lies in the preprocessing of the excluded features and their inclusion in the training phase, employing various classification ML and DL algorithms such as ExtraTrees, ANN, simple CNN, and VGG16 for binary classification. Results: The performance of the classification models is evaluated using metrics such as accuracy, recall, etc., which provide a comprehensive analysis of the obtained results. The results show that the ExtraTrees ML model outperforms all other models when using our preprocessing features, achieving a classification accuracy of 99.09%, compared to 97.25% in the reference dataset. Conclusion: The study demonstrates the effectiveness of anomalybased ML and DL models in NIDSs using Netflow data.

DoS Attack Detection Mechanism in Wireless Sensor Networks

Wireless sensor networks (WSNs) are not like traditional networks in terms of their characteristics. Unlike WSN, in classic networks, networking mechanisms have decision-making power with reference to the management of an incoming packet only based on its internet protocol (IP) destination address. Assailant nodes can activate a denial of service (DoS) attack after entering the network. This research work focuses on tracing these collusive nodes by applying a trust-based scheme. The trust-based scheme includes measuring the degree of trust among all nodes. Nodes with minimum trust are designated as malicious nodes. Trust is measured based on the overall packets transferred during the time slot allotted. The node forwarding maximal packets and exploiting minimal assists will be tagged as malicious. The nascent architecture was deployed in NS2, and the outcomes were analysed based on particular performance metrics. To calculate trust, the overall packets forwarded by nodes in the allotted slot were considered. The node that transmits the largest number of packets and uses negligible assets was declared a vindictive node. This task implementation presents the approach in the NS2 software and analyses the results based on certain metrics.

PENCARIAN RUTE TERPENDEK PADA APLIKASI OJEK SAMPAH DENGAN MENGGUNAKAN ALGORITMA DJIKSTRA

Currently there is a transportation service at the Sorong Raya Garbage Bank. Customers for transport services are increasing day by day and this makes it difficult for drivers because they have to determine short routes every day. If the driver does not know the exact address and determines the shortest route, this will result in inefficient use of time and wasted fuel. This can also have an impact on the services provided to customers so they are not optimal because they are late or not on time. Based on the existing problems, a solution is given in the form of an application that aims to determine the shortest or closest route between each address that will be visited by the garbage collection car, this is to support the effectiveness of waste collection by providing information to the driver in the form of the shortest path to be traversed. Applications are made using the Dijkstra algorithm approach for mobile applications on the Android platform. The application is equipped with a description of the trip, estimated travel time, and alternative routes to each address. The result of the application made is that the application can implement the Djikstra algorithm which can be applied and succeeds in determining the shortest distance for the process of transporting garbage to residents' homes based on the initial address input from the driver to the pick-up destination address.

Jual Beli Online Dengan Menggunakan Sistem Cash On Delivery Di Kelurahan Kalangan di Tinjuan Kompilasi Hukum Ekonomi Syariah

The problem in this study is how the practice of buying and selling online with the cash on delivery system is seen from the compilation of sharia economic law. This research is field research with a qualitative approach, the primary data source is from couriers and buyers while secondary data comes from documents related to this research, then data collection techniques through observation, interviews and documentation and data analysis techniques use descriptive qualitative. The results of this study explain that in buying and selling online, khiyar must be formed which has been implemented or carried out by sellers and buyers, namely Khiyar Disgrace and Khiyar Terms. It's the same as buyers who suffer losses because the goods they ordered are damaged, so they may return, and Khiyar. This condition applies if the conditions put forward by the seller have conditions to be allowed to return if they are not in accordance. Review of Compilation of Sharia Economic Laws regarding khiyar rights in buying and selling online in the COD system, the law is permissible, where it has been categorized as a type of buying and selling Bai'i As Salam. And the payment can also be made later when the goods ordered arrive at the destination address. Based on this, the explanation in the Compilation of Sharia Economic Law. Furthermore, it is not included in buying and selling transactions which are prohibited in Islam as explained in the previous chapter.

A secure cross-layer architecture for reactive routing in vehicle to vehicle (V2V) communications

Vehicular communication is one of the essential technologies for increasing road safety, traffic efficiency, and comfort for pedestrians and drivers. In this context, the internet of vehicles is an emerging paradigm. However, with advances in vehicular communication, security threats have also emerged. Several vulnerabilities exist in vehicular communications, including Denial of Service (DoS), black hole attacks, and fabrication attacks. A malicious attack alters the packet information in a fabrication attack, causing congestion and high delays in the vehicular network. We propose two algorithms to protect the routing protocols in a vehicle-to-vehicle scenario against several attacks that target confidentiality, authentication, privacy, and integrity. The first algorithm detects the malicious behavior of each vehicle by calculating the percentage of modified destination addresses. If it exceeds a predetermined threshold, this vehicle is classified as malicious. Otherwise, it is a normal vehicle. The second algorithm detects malicious modifications based on the Signal to Interference Ratio (SIR) by monitoring the SIR value, adjusting the distance, altering the power received, and changing the transmitted power value. We performed simulations using the SUMO 0.22 simulator and Network Simulator (NS). The results obtained show an improvement in End-to-End (E2E) delay, Packet Delivery Ratio (PDR), and reduced overhead.