hitung:-
write("UAS: "),read(Uas),
write("UTS: "),read(Uts),
write("Tugas: "),read(Tugas),
write("Presensi: "),read(Presensi),
Nilai is ((Uas*40)+(Uts*30)+(Tugas*20)+(Presensi*10))/100,
write(Nilai),nl,
( Nilai >= 80,write("Grade A");
Nilai >= 65,write("Grade B");
Nilai >= 55,write("Grade C");
Nilai >= 40,write("Grade D");
write("Grade E")
)
.
iden(n01,andi).
iden(n02,budi).
iden(n03,ina).
iden(n04,ina).
item(i01,anggur).
item(i02,jeruk).
item(i03,donut).
warna(w01,merah).
warna(w02,hijau).
warna(w03,coklat).
warna(w04,kuning).
rasa(r01,manis).
rasa(r02,masam).
menyukai(n01,i01,w01,r01).
menyukai(n02,i01,w02,r02).
menyukai(n03,i02,w04,r02).
menyukai(n04,i03,w03,r01).
manis1(Nama):-
iden(No,Nama),rasa(Ra,manis),
menyukai(No,_,_,Ra).
Cybersecurity has become a pervasive issue affecting all aspects of our digital lives, from financial institutions to healthcare systems (Prince, 2018). It encompasses technical, organizational, and executive measures to protect electronic information and communication systems from unauthorized access and misuse (Mijwil, 2023). The healthcare sector is particularly vulnerable to cybercrime due to its valuable data and weak defenses, with potential breaches impacting patient safety and trust (Coventry & Branley, 2018). To address these challenges, artificial intelligence, specifically machine learning and deep learning techniques, plays a significant role in predicting and understanding malicious software behavior (Mijwil, 2023). Researchers and practitioners from academia, government, and industry are developing emerging technologies and methodologies to mitigate various cyberthreats (Hsu et al., 2015). As cybersecurity becomes integral to patient safety and overall digital security, a holistic approach involving changes to human behavior, technology, and processes is necessary (Coventry & Branley, 2018).
Reference:
The Internet of Things (IoT) is a rapidly evolving paradigm that connects physical objects to the internet, enabling seamless integration and communication between devices and humans (Carretero & García Sánchez, 2013). IoT combines sensor, embedded, computing, and communication technologies to provide ubiquitous services (Narasimha Swamy & Kota, 2020). This interconnected network of devices aims to improve various aspects of daily life, including energy efficiency, healthcare, and comfort (Carretero & García Sánchez, 2013). The IoT architecture encompasses multiple layers and technologies, such as fog computing, wireless sensor networks, and data analytics (Din et al., 2019). However, the widespread adoption of IoT faces challenges in energy efficiency, scalability, interoperability, and security (Narasimha Swamy & Kota, 2020). As IoT continues to evolve, it is expected to transform the real world into intelligent virtual objects, unifying everything under a common infrastructure (Madakam et al., 2015). This technological advancement promises to revolutionize various industries and improve the overall quality of life.
Reference:
Expert systems in agriculture, particularly viticulture, have shown significant potential for improving crop management and decision-making. As an example Expert systems for Grape. These systems can capitalize on heterogeneous knowledge and predict grape maturity with high accuracy (Perrot et al., 2015). They aim to elevate average worker performance to expert levels in various agricultural domains (McKinion & Lemmon, 1985). Specific applications include diagnosing pests, diseases, and disorders in apple crops (Kemp et al., 1989), which could be adapted for grapevines. Recent advancements integrate computer vision and machine learning techniques for viticulture, addressing challenges such as harvest yield estimation, vineyard management, grape disease detection, and quality evaluation (Seng et al., 2018). The development of specialized databases, like GrapeCS-ML, facilitates research in smart vineyard technologies, including color-based berry detection for different cultivars (Seng et al., 2018). These innovations promise to enhance sustainability and efficiency in the wine industry through improved prediction and management capabilities.
Reference:
Expert systems are artificial intelligence applications designed to emulate human expert decision-making in specific domains (Á. Rocha & S. Anwar, 2019; T. Todorov & J. Stoinov, 2019). These systems solve complex problems by reasoning through knowledge bases, often represented as if-then rules (Á. Rocha & S. Anwar, 2019). They are applied in various fields, including milk quality monitoring and animal health (T. Todorov & J. Stoinov, 2019), as well as information management, organizational models, and software systems (Á. Rocha & Lima, 2018). As technology advances, expert systems are evolving to demonstrate superb decision-making skills and conform to social norms for expertise, behaving more like human experts (Papageorgiou, 2021). This development has implications for various fields, including bioinformatics, and raises questions about the concept of "expert generalist" (Papageorgiou, 2021). The continued research and development of expert systems contribute to their growing capabilities and applications across diverse domains.
Reference:
To excel in cybersecurity, a field that is constantly evolving and expanding, you should focus on a blend of education, practical skills, staying updated with the latest trends, and networking. I want to be good at Cyber Security, what should I do?
Here are some steps to guide you:
Starting a career in cybersecurity requires a mix of technical knowledge, practical experience, and continuous learning. It's a challenging yet rewarding field with a high demand for skilled professionals.
