Sinkron : jurnal dan penelitian teknik informatika
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Comparative Study: Preemptive Shortest Job First and Round Robin Algorithms
No full textAbstract: Operating system is a software acting as an interface between computer hardware and user. Operating system is known as a resource manager. The main responsibility of operating system is to handle resources of computer system. Scheduling is a key concept in computer multitasking and multiprocessing operating system design by switching the CPU among process. Shortest job first (SJF) and round robin are two wellknown algorithms in CPU processing. For shortest job first, this algorithm can be preemptived. In preemptive shortest job first, when a new process coming in, the process can be interupted. Where with round robin algorithm there will be time slices, context switching, or also called quantum, between process. In this journal we wil discuss comparative study between preemptive shortest job first and round robin algorithms. Three comparative studies will be discussed to understand these two algorithms more deeply. For all comparative study, the average waiting time and average turnaround time is more for round robin algorithm. In the first comparative study, we get average waiting time 52% more. For average turnaround time, 30% more. In second comparative analysis, we get 52 % average waiting time more and we get 35 % average turnaround time more. For third comparative analysis, average waiting time we get 50% more and for average turnaround time, we get 28% more. Thus it is concluded in our comparative study for these kind of data the preemptive shortest job first is more efficient then the round robin algorithm.
Keywords: comparative study, premptive shortest job first algorithm, round robin algorithm, turn around time, average waiting time, time slic
Technology Acceptance Model to Factors Customer Switching on Online Shopping Technology: Literature Review
No full textCustomer loyalty is a phenomenon that is the center of attention of an organization or company because it greatly influences the continuity and development of the organization. Customers are said to be loyal if they have affection for a company's products or services. So that loyal customers will express this affection by saying positive things about the company's products or services to friends, relatives and co-workers. However, if customers feel uncomfortable with a company's products and services, there is a possibility that customers will switch from loyal to disloyal. This is usually called customer switching. This research is based on a systematic review of the influence of usability and ease of use of online shopping applications as well as the factors causing customers to switch from online shopping applications to mobile retail applications. Three phases are used in this study's systematic literature review (SLR). The factors that were discovered were categorized using three main themes. Interconnected among these three elements are perceived utility, perceived ease of use, and behavioral intention to use. This study also found that when TAM is added as a new component to gauge the intention to adopt an online shopping application, "trust, ease, and information quality" are the most important factors. By carefully identifying the effects of online shopping application on business management, this research contributes theory. The findings assist online shopping application service providers in formulating sensible plans for foreseeing and enhancing clients' intentions to use online shopping applications
Analysis of Multi-Node QoS in Shrimp Pond Monitoring System with Fog Computing
No full textMost of Indonesia’s territory consists of oceans, presenting a significant potential for developing the fisheries sector. Shrimp is among Indonesia’s flagship commodities with substantial export potential. Internationally, Indonesia holds the fourth position as the largest exporter of frozen shrimp globally. However, shrimp cultivation faces various challenges, including declining water quality due to factors such as water sources and weather, which can adversely affect harvest yields. To preempt potential failures, employing smart devices and technology in shrimp cultivation offers an effective and efficient solution for monitoring and management. This study aims to analyze water quality monitoring in ponds considering the speed of data transmission from end devices to fog using Quality of Service (QoS) parameters like delay/latency, throughput, and packet loss. Data transmission tests were conducted at data rates of 5 Mbps and 10 Mbps, with a bandwidth of 1500 Mbps. The study involves three sensors—water temperature, pH, and salinity—placed in shrimp ponds. Test results showed a decrease in throughput by 1.54% at the sensor node and 2.99% at the sink node when packet data delivery encountered barriers like obstacles. There was a 74.13% increase in latency when the delivery distance extended to 35 meters. The achievable delivery range with low latency was up to 10 meters with barriers and 25 meters without. Thus, latency and throughput values vary depending on the presence of barriers and transmission distance. Barriers tend to increase latency and decrease throughput
Information Security Evaluation of Data Centre Architecture Using COBIT 5
No full textPusat Teknologi Informasi dan Pangkalan Data (Pustipanda) UIN Jakarta is an institution in charge of managing all information systems and data management for UIN Jakarta. However, security issues are still one of the problems faced by Pustipanda today, such as data leaks, and websites that are often problematic. This research aims to assess the level of information security at the UIN Jakarta Pustipanda data centre using the COBIT 5 framework. Information security is very important in supporting organizational operations, especially facing cyber threats in the data centre environment. The research approach included document analysis, observation, and interviews with stakeholders at Pustipanda UIN Jakarta. Identification of information security weaknesses, assessment of compliance with security standards, and design of appropriate solutions are the subject of the research. It is hoped that the results will provide a comprehensive picture of information security in the data centre as well as concrete recommendations for improvement. The results of the research include an understanding of the status of information security at Pustipanda UIN Jakarta, as well as guidelines for improving information security in accordance with COBIT 5 principles. These efforts aim to reduce risk and protect the integrity, confidentiality, and availability of data in the data centre environmen
EYE-R : Augmented Reality as Mobile Based Helper Application for Colorblinds
No full textThe ability to identify color is a basic ability for a human to live easily. Unfortunately not all humans have normal sight, there are some humans who have an eye disorder called color blindness. Color blindness is an eye disorder that affects color perception of the affected person in everyday life, therefore the person that has color blindness needs a device to help them to identify some colors. In the medical world, the usage of Augmented Reality is still limited for education for medical practitioners, so the application of AR as a tool to help patients is still considered to be minimal. Augmented Reality as a Mobile Based Colorblind Helper Research aims to find out how effective a color detection system using AR as a tool to help the colorblinds identify color in an application called “EYE-R”. The research method employed in the research and development of this application is the Waterfall method that involves the stages of Requirements, Design, Programming, Testing, and Implementation. The main feature of “EYE-R” is chosen using a survey which is Real Time Color Detection which is developed using the Unity engine and implemented using Android. The research results show that the majority of users can operate the Real Time Color Detection system accurately. The user satisfaction results recorded using USE Questionnaire shows that the EYE-R Real Time Color Detection system really helps users’ daily lives and can be used very well
Optimizing Automotive Manufacturing Systems through TOGAF Modelling
No full textThe objective of this research is to examine the viability of implementing the Open Group Architecture Framework to enhance the efficiency and performance of automotive manufacturing systems. The automotive industry remains confronted with challenges pertaining to the enhancement of manufacturing processes, the reduction of product development time, and the adjustment to swift technological progressions. The primary obstacles encountered in implementing process innovation, the complexity of the IT infrastructure, and the absence of system integration constitute the most significant challenges. The primary aim of this study is to present a resolution through the application of the TOGAF framework. By implementing this strategy, system synchronization will be enhanced, IT infrastructure will be simplified, and process innovation will be able to respond to market fluctuations more rapidly. The existing business processes are streamlined and consistent with the strategic progress of vehicle manufacturing firms. Nonetheless, business processes involving architectural applications continue to diverge from market demands and fail to align with evolving business requirements. In the context of automotive manufacturing, the TOGAF modeling methodology will be applied to analyze the data architecture, application architecture, strategic elements, and information technology infrastructure. Advise stakeholders in the automotive industry, facilitating the integration of TOGAF principles into endeavors to redesign systems. This will reduce the attainment of innovation, adaptability, and efficiency, all of which are critical for sustaining competitiveness in a dynamic marketplace. By applying TOGAF principles to the automotive manufacturing system, Enterprise Architecture can support ever more complex business requirements
K-Medoids Algorithm to Clustering COVID-19 Patients with Various Age Levels at Hospitals in Yogyakarta Province
No full textCOVID-19 causes a wide spectrum of symptoms, such as mild upper respiratory infection or life-threatening sepsis. From 20.2% of cases of COVID-19 progressed to severe disease with a mortality rate of 3.1% where 60%-90% of patients with comorbidities were hospitalized. The purpose of this study was to find out that cluster analysis using K-Medoids can distinguish COVID-19 patients at various age levels which analytical method has sensitivity and specificity values in analyzing clustering in COVID-19 patients. This study uses a cohort retrospective design conducted at five hospitals in Yogyakarta Province. The study used patient medical record data from March 2020 – September 2021 with a total of 916 patient data that met the inclusion criteria. Cluster analysis will be carried out using Google Colaboratory with the Python programming language. The clustering results are divided into 2 cluster groups where cluster 1 consists of 558 patients and cluster 2 consists of 358 patients with various age levels. The test resulted in 2 clusters with a DBI value of 5,191631. The results of statistical tests showed that there was a significant relationship (p-value = 0,023) between age, recovery rate, and patient mortality. From the test results, it can be seen that ages 50 to 59 years are suspected of COVID-1
A Review on AMRR and Improved Round Robin Algorithms: Comparative Study
No full textRound Robin Algorithm is a dominant algorithm in real time system. Improved round robin and average max round robin, which is also called AMRR are two types with a breakthrough. Improved round robin is an algorithm where if the remaining burst time of the process is less than the quantum, then the running process will continue to be executed. Afterwards the next iteration will be executed as its turn. So, each iteration will have a vary of quantum. It is called a dynamic time quantum. Different with improved round robin, in AMRR, in every iteration, the quantum will be calculated. So, for every iteration, the quantum might be different, depending upon the quantum calculation of the rest burst time. The first stage of this algorithm is to calculate the average of the existing burst times. Then this average is added with the maximum existing burst time. This addition then will be divided, then we get the quantum. This calculation will be executed again after the iteration finish. Based on our analysis, with quantum 10 in these two algorithms. It is can be shown that the improved round robin is less efficient than AMRR, because its average turnaround time and average waiting time is lower. The average turnaround time is 17.25 ms for AMRR compared to 23.25 ms in improved round robin. And the average turnaround time is 9 ms for AMRR compared to 15 ms in improved round robin
Fine-Grained Analysis of Coral Instance Segmentation using YOLOv8 Models
No full textWithin the geographical boundaries of Indonesia, coral reefs flourish as intricate ecosystems bustling with a variety of marine creatures that play a crucial role, in preserving biodiversity. However this delicate harmony faces threats from climate change and human activities, leading to the risk of species loss. Despite growing awareness surrounding these challenges effectively and swiftly monitoring conditions remains a task. Existing methods for assessing corals often fall short due to requiring extensive specialist knowledge, lacking large-scale coverage, and being costly to implement. To tackle these obstacles this research suggests an approach for automated reef monitoring using instance segmentation with a YOLOv8 model. Leveraging YOLOv8 segmentation capabilities enables efficient analysis of corals. A systematic process is employed involving data collection, preparation (including techniques like Histogram Equalization), training the model on a reef dataset, model evaluation and enhancing the segmentation mask. The outcomes reveal the YOLOv8m Pp model with 96.7% precision 95.9% recall rate and a mean Average Precision (mAP50) score of 98.2%. This study demonstrates the potential of YOLOv8 to accurately segment instances for monitoring reefs in Indonesia, hence facilitating improved conservation strategies
Application of Data Mining using the K-Means Method for Visitor Grouping
No full textGrouping amusement ride visitor data is an important process that aims to identify certain patterns of visitors, enabling management to adjust marketing strategies and improve their services more effectively. This process begins with a data selection stage where relevant visitor data is collected and prepared for analysis. The next stage is data pre-processing, which involves cleaning the data from noise or irrelevant data, as well as ensuring the data is in a format suitable for analysis. After that, the data mining model design is carried out by selecting the most appropriate method for grouping visitor data. The next stage is testing and evaluating the model to verify its accuracy and effectiveness. The results of model testing show that visitor data can be categorized into three groups: C1 with 50 data, C2 with 20 data, and C3 with 48 data. The results of the model evaluation confirm that the designed model succeeded in classifying data with perfect accuracy, namely 100%. This success shows that the model is highly effective in identifying and segmenting visitor patterns, providing valuable insights for strategic decision making in service improvement and marketing. This success also opens up opportunities for the application of similar methods to other datasets in an effort to improve visitor experience and operational efficiency