<p>Perangkat Internet of Things (IoT) merupakan perangkat cerdas yang memiliki interkoneksi dengan jaringan internet global. Investigasi kasus yang menyangkut perangkat IoT akan menjadi tantangan tersendiri bagi investigator forensik. Keberagaman jenis perangkat dan teknologi akan memunculkan tantangan baru bagi investigator forensik. Dalam penelitian ini dititikberatkan forensik di level internal device perangkat IoT. Belum banyak bahkan belum penulis temukan penelitian sejenis yang fokus dalam analisis forensik perangkat IoT pada level device. Penelitian yang sudah dilakukan sebelumnya lebih banyak pada level jaringan dan level cloud server perangkat IoT. Pada penelitian ini dibangun environment perangkat IoT berupa prototype smart home sebagai media penelitian dan kajian tentang forensik level device. Pada penelitian ini digunakan analisis model forensik yang meliputi collection, examination, analysis, dan reporting dalam investigasi forensik untuk menemukan bukti digital. Penelitian ini berhasil mengungkap benar-benar ada serangan berupa injeksi malware terhadap perangkat IoT yang memiliki sistem operasi Raspbian, Fedberry dan Ubuntu Mate. Pengungkapan fakta kasus mengalami kesulitan pada perangkat IoT yang memiliki sistem operasi Kali Linux. Ditemukan 1 IP Address komputer penyerang yang diduga kuat menanamkan malware dan mengganggu sistem kerja perangkat IoT.</p><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The Internet of Things (IoT) is an smart device that has interconnection with global internet networks. Investigating cases involving IoT devices will be a challenge for forensic investigators. The diversity of types of equipment and technology will create new challenges for forensic investigators. In this study focused on forensics at the IoT device's internal device level, there have not been many similar research that focuses on forensic analysis of IoT devices at the device level. Previous research has been done more at the network level and cloud level of IoT device's. In this study an IoT environment was built a smart home prototype as a object for research and studies on forensic level devices. This study, using forensic model analysis which includes collection, examination, analysis, and reporting in finding digital evidence. This study successfully revealed that there was really an attack in the form of malware injection against IoT devices that have Raspbian, Fedberry and Ubuntu Mate operating systems. Disclosure of the fact that the case has difficulties with IoT devices that have the Kali Linux operating system. Found 1 IP Address of an attacker's computer that is allegedly strongly infusing malware and interfering with the work system of IoT devices.</em></p><p><em><strong><br /></strong></em></p>
Social media in providing freedom of access to information has a rapid effect on tourist destinations in Indonesia. A tweet may also contain information or conditions about tourist destinations that they will or have visited, such as visitor experiences in traveling, visitors' opinions of tourist attractions, and other tourist attractions. The condition of tourism globally, especially in the Gunungkidul area after the Covid-19 pandemic, has experienced a significant decline. This condition motivated researchers to conduct research with the aim of contributing to post-Covid-19 tourism development, in particular by conducting a sentiment analysis of comments by tourists visiting tourist areas in Gunungkidul Regency. Sentiment analysis is the process of using text analytics to derive various data sources from the internet and various social media platforms. Comment data obtained through social media Twitter. This classification is used to find out how comments about tourist attractions in Gunungkidul are. Lexicon based and pivoting are methods used to classify public opinion into three classes, namely positive, negative and neutral sentiments. This method is used to classify the results of community comment data written on the form of community satisfaction with tourism in Gunungkidul. This study aims to find out how people's opinions regarding tourism in Gunungkidul during the Covid-19 pandemic took place. The results of this study are used to determine the classification of community commentary data so that services can be easily developed through comments given by the public. The results of the sentiment analysis show that there are 51% positive emotion categories, 1% negative and 48% neutral.
Utilization of decision support systems as a tool for decision makering that integrates directly with computer in providing information and solutions. This research implements the method of SMART (Simple Multi-Attribute Rating Technique), to calculate the criteria that become the benchmark for determination of the type of plant is appropriate based on the content soil. In building a Decision Support System using six criteria, namely hummus, regosol, alluvial, grumusol, andosol, and nitrogen. Testing the decision support factors to determine the type of plant-based on the soil as measured by McCall’s quality using 3 aspects of measurement. From the results 15 respondents obtained for the aspect of correctness with a value of 71.33%, the aspect of reliability with a value of 71.33%, reliability aspect with a value of 67.1%, and aspects of usability with a value of 48.27%. Overall, the test results from the 3 test aspects results obtained are 62.37%, which indicates this system has a good category and is worth to use.
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