The objectives of this paper are to analyze the implementation and architecture of the Internet of Things (IoT) from previous studies, specifically in the world of higher education; offer recommendations for future research, as well as strengthen the theory of IoT architecture that already exists in higher education. This study employed a systematic literature review (SLR) with data collection utilizing Funnel Diagrams to select articles based on their relevance to the research question. The three publisher databases (Scopus, Emerald, and EBSCO) and index journals were utilized in the search for articles. A total of 1,200 articles were gathered from these three sources, with distributions of up to 800 in Scopus, 150 in Emerald, and 250 in EBSCO. The findings demonstrate that the existing IoT architecture has a more sophisticated model than the fundamental idea, which has three layers, implying that using IoT in education may have a significant influence on user convenience. This is due to the increasingly complicated requirements of higher education's many business procedures. This study serves as an inspiration and reference for future research for higher education institutions that include the Internet of Things in their implementation to build an efficient teaching and learning environment.
This study aims to determine how artificial intelligence's role in increasing marketing activities' effectiveness in automatic personalization. Some of the factors that can influence humans using social media are what they like, where they comment, and their type in the search fields on their social media. The method used in this research is a comparative descriptive method, namely describing or explaining and validating a phenomenon under study, then comparing it with other social media that has a different system. Some of the variables or objects studied in this paper are the user's habits in using social media and the artificial intelligence found on several social media that reacts with their users' habits. This study shows how artificial intelligence can increase the effectiveness of marketing activities on social media and produce comparable data between artificial intelligence technologies found in several social media, which shows that artificial intelligence is proven to increase marketing activities' effectiveness. It is done on social media.
This research aims to determine agriculture as the leading sector for regional competitive advantage in the Garut Regency. The method used was Location Quotient, Shift-Share Analysis, and Klassen Typology to classify the sectors and determine the structural pattern of economic development in the Garut Regency. The findings of Location Quotient indicate that agriculture is the leading sector in Garut Regency. The shift-share calculation shows that agriculture has the highest national share and the most significant growth change but has a negative value on proportional shift (industry mix) and differential shift (competitive effect). Based on the Klassen typology, the agricultural sector is in Quadrant II, the developed but depressed industry. The results showed that the agriculture, forestry, and fisheries sector in Garut Regency has a competitive advantage, but it has not been supported structurally in West Java Province.
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