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2022 ◽  
Vol 25 (1) ◽  
pp. 1-26
Author(s):  
Fabio Pagani ◽  
Davide Balzarotti

Despite a considerable number of approaches that have been proposed to protect computer systems, cyber-criminal activities are on the rise and forensic analysis of compromised machines and seized devices is becoming essential in computer security. This article focuses on memory forensics, a branch of digital forensics that extract artifacts from the volatile memory. In particular, this article looks at a key ingredient required by memory forensics frameworks: a precise model of the OS kernel under analysis, also known as profile . By using the information stored in the profile, memory forensics tools are able to bridge the semantic gap and interpret raw bytes to extract evidences from a memory dump. A big problem with profile-based solutions is that custom profiles must be created for each and every system under analysis. This is especially problematic for Linux systems, because profiles are not generic : they are strictly tied to a specific kernel version and to the configuration used to build the kernel. Failing to create a valid profile means that an analyst cannot unleash the true power of memory forensics and is limited to primitive carving strategies. For this reason, in this article we present a novel approach that combines source code and binary analysis techniques to automatically generate a profile from a memory dump, without relying on any non-public information. Our experiments show that this is a viable solution and that profiles reconstructed by our framework can be used to run many plugins, which are essential for a successful forensics investigation.


2022 ◽  
Vol 4 (3) ◽  
pp. 880-894
Author(s):  
Ana Marfuah ◽  
Kusuma Chandra Kirana ◽  
Didik Subiyanto

This research aims to determine the effect of competence and work ethic on work performance with motivation as a moderating variable. In this study using a population of all employees of PT. Sapta Sentosa Jaya Abadi Muko-Muko with a total of 70 respondents, the sampling technique used saturated sampling with questionnaires which were distributed to all employees of PT. Sapta Sentosa Jaya Abadi Muko-Muko. This research is a quantitative research. Data analysis techniques used in this research are descriptive analysis, multiple regression analysis, and Moderate Regression Analysis (MRA). The results of this study indicate that the competence variable has a positive and significant effect on work performance, the work ethic variable has a positive and significant effect on work performance, the motivation variable has a positive and significant effect on work performance, the motivation variable can moderate competence on work performance, The motivation variable cannot moderate work ethic on work performance Keywords: Motivation, Competence, Work Ethic, Work Performance


2022 ◽  
Vol 4 (4) ◽  
Author(s):  
Suriyani BB ◽  
Suci Amalya Widiastuti

This study aims to determine and describe optimizing public services online at the regional office of the Ministry of the Law and Human Rights in Southeast Sulawesi, this study uses descriptive qualitative methods to 5 informants determined by snowball sampling technique, data analysis techniques consist of data collection, data reduction, presentation data, drawing conclusions/verification, the data obtained were analyzed qualitatively and described in descriptive form. The results of this study indicate that public services carried out online at the regional office of the Ministry of Law and Human Rights in Southeast Sulawesi are very good, this can be seen from the implementation of services with standard operating procedures that apply during the pandemic and the handling that is in accordance with what has been determined at the regional office of the Ministry of Law and Human Rights by upholding the values of professionalism, accountability, synergy, transparency, and innovation. Based on the research, one form of research on optimizing public services is the existence of a digital-based service system that makes it easier for the public to receive services, supporting facilities, and infrastructure, as well as services provided quickly and responsively at the region of the Ministry of Law and Human Rights in Southeast Sulawesi.


2022 ◽  
Vol 4 (3) ◽  
pp. 585-594
Author(s):  
Umi Latifah ◽  
Burhanudin AY ◽  
Istiqomah Istiqomah

This study aims to analyze the digital marketing strategy of the Hajj and Umrah bureau in recruiting pilgrims before and during the pandemic, as well to find out the differences in digital marketing strategies. The object of research at PT. Amanau Izzah Zamzam Sakinah Surakarta. The research method with qualitative uses primary data and secondary data. Research informants are leaders, marketing staff, digital marketing staff. Data collection techniques with interviews, observation, and documentation. Data analysis techniques through data reduction, data presentation, and drawing conclusions. The result is that the digital marketing strategies used before the pandemic were websites, Facebook, Instagram, Pinterest and WhatsApp. during a pandemic, focus on digital marketing such as websites, Facebook, and WhatsApp. The difference in the focus of the three social media is seen from the large number of registrants from the website, Facebook, and WhatsApp so that currently they are maximizing it


2022 ◽  
Vol 6 (2) ◽  
pp. 66
Author(s):  
Apriliana Ika Kusumanisita ◽  
Lathiefa Rusli ◽  
Raditya Iqbal Anugrah

This study aims to examine customer decisions in investing in BMT. The theory used to predict customer decisions in investing is the theory of reasoned action. The research method used is quantitative research with data analysis techniques Structural Equation Modeling (SEM). The results showed that the sharia system, product knowledge, religiosity, attitudes, risk perception, image, and investment intentions affected investment decisions.


2022 ◽  
Vol 12 (4) ◽  
pp. 450-466
Author(s):  
. Hamzah Nurdin ◽  
. Sukanto ◽  
. Yunisvita

Purpose: this study aims to examine the community's decision to migrate between regions in the Jabodetabek area using the KRL Commuterline public transportation and analyse regional criteria based on regional development based on Oriented Development Transit, where these criteria become integration with community movements in migrating to an area.Methods: secondary data is used to fnd the number of people in migrating obtained from pt. Kai Indonesia. While to complete and explain each variable to be studied using primary data with several questions through a questionnaire submitted to 398 people who migrate between regions using logistic regression analysis techniques in their measurements. While to analyze the criteria for regional development in each region using an assessment approach from the Institute for Transportation and Development Policy. With qualitative analysis techniques and to assist in this research, a spatial approach is used which is used to display a picture of the distribution of migration.Results: (1) Regional development in each part of the Jabodetabek area is in the silver standard category which indicates that the regional development project has almost met the performance targets that have been conceptualized by the Institute for Transportation and Development Policy. (2) People in making decisions to migrate between regions will be affected by the variables of distance, travel costs, gender, travel time, migration destination and regional development, while age and transit distance cannot provide a large enough influence on people's movements in migrating.Conclusions and Relevance: the results of the study prove that regional development in the Jabodetabek area tends to be a non-metropolitan area where people who move prefer areas that are integrated with public facilities that lead to the destination rather than towards the metropolitan area, this is evidenced by the standard silver criteria obtained in the area in Jabodetabek.


2022 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Marianna Lepelaar ◽  
Adam Wahby ◽  
Martha Rossouw ◽  
Linda Nikitin ◽  
Kanewa Tibble ◽  
...  

Big data analytics can be used by smart cities to improve their citizens’ liveability, health, and wellbeing. Social surveys and also social media can be employed to engage with their communities, and these can require sophisticated analysis techniques. This research was focused on carrying out a sentiment analysis from social surveys. Data analysis techniques using RStudio and Python were applied to several open-source datasets, which included the 2018 Social Indicators Survey dataset published by the City of Melbourne (CoM) and the Casey Next short survey 2016 dataset published by the City of Casey (CoC). The qualitative nature of the CoC dataset responses could produce rich insights using sentiment analysis, unlike the quantitative CoM dataset. RStudio analysis created word cloud visualizations and bar charts for sentiment values. These were then used to inform social media analysis via the Twitter application programming interface. The R codes were all integrated within a Shiny application to create a set of user-friendly interactive web apps that generate sentiment analysis both from the historic survey data and more immediately from the Twitter feeds. The web apps were embedded within a website that provides a customisable solution to estimate sentiment for key issues. Global sentiment was also compared between the social media approach and the 2016 survey dataset analysis and showed some correlation, although there are caveats on the use of social media for sentiment analysis. Further refinement of the methodology is required to improve the social media app and to calibrate it against analysis of recent survey data.


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