Businesses nowadays may save a significant amount of money by using technological solutions. It is impossible to deny this when considering the expenses of acquiring and training new personnel. When faced with such difficulties, technology is virtually always able to assist. Business Intelligence/Machine Learning (BI/ML) is an essential tool in today's decision-making process because of the many issues it has created for contemporary business decision-making. A comparative study of regression models, including linear regression, random forests, and gradient boosting, could unravel their effectiveness in predictive analytics within BI. Machine learning contribution in businesses is vital as it has a strong link with business intelligence, and it helps business decision-making in businesses. Without machine learning, business intelligence is not practical while making decisions, as business owners can't make decisions effectively. This paper will comprehensively review the noteworthy contributions of Machine Learning and its Impact on Business Intelligence. Further, it will discuss the challenges and opportunities of machine learning in business intelligence. Finally, the paper will discuss future correspondence about machine learning in businesses.

The work highlights exploring the usage of blockchain technology for enhancing traceability in agricultural supply chain management. The aim is to develop a secure and transparent system, which improves the easy tracking and tracing of agricultural products from the point of origin until it reaches the end consumer. Currently, Blockchain is a technology, which provides security in various fields of transactions. The work utilizes to improve supply chain efficiency, increase transparency and accountability, and enhance consumer trust in the agricultural products. The system will utilize smart contracts to automate processes and ensure compliance with regulations and standards, which improves supply chain efficiency. Smart contracts enable agreement between two parties present in the supply chain. Further, the financial transactions can be improved with the help of block chain. Additional, the work will also provide recommendations for companies and organizations looking to implement blockchain-based results in their supply chain management. The work implements an application using ganache, solidity and truffle. Ethereum block chain is used as primary infrastructure for the application. Smart contracts generated using solidity is deployed into Ethereum network using truffle. The deployment of the application in agricultural sectors improves the accountability in the field of the supply chain. The deployment in a wider range will avoid manipulation of the data.
Agricultural supply chain tracing website involves the use of several tools and technologies, including Ganache, Solidity, and Truffle. The system uses the Ethereum blockchain as the underlying infrastructure to store and manage supply chain data securely and transparently. The smart contracts in the supply chain tracing system are generated using Solidity and deployed to the Ethereum network using Truffle. 

The rise in popularity of ride-sharing services and ride-booking systems has created new opportunities and challenges for security and safety. A useful system for passenger safety assistance using machine learning and mobile applications is missing from the existing work. This paper develops a data set regarding suspicious activity detection using a questionnaire. This paper selects a suitable machine learning model for suspicious activity prediction during a transport ride by examining support vector classifiers (SVC), random forest, MLP classifiers, decision trees, KNN, logistic regression, and Gaussian naive Bayes classifiers. The results showed that the SVC is most suitable, with 97% accuracy, for classifying suspicious activity predictions during transport riding. This paper provides a passenger safety mobile application with passenger and driver verification, application rating, suspicious activity prediction, suggestions regarding safety, location mapping, and trip booking features. The application evaluation results based on users’ comments showed that more than 55 percent of users supported the application's usability and effectiveness nature.

The rise of environmental awareness globally has influenced the clothing industry, prompting the emergence of sustainable fashion as a response to the negative impacts of fast fashion. Despite its positive intentions, sustainable fashion holds a modest 7% of the global market, with fast fashion dominating at 93%. In Indonesia, a growing environmental consciousness has led to an increase in sustainable fashion businesses. An analysis using Porter's five forces model and the Delphi technique for sustainable fashion in Jabodetabek indicates that the current competitive power of sustainable fashion in the broader industry is relatively low. While the competitive landscape is secure and not overly saturated, attention is needed for factors like increasing competitors, significant product differentiation, and high capital requirements, posing notable competitive threats. Key parameters, including the number of buyers and the threat of substitute products, also warrant scrutiny. Challenges persist, such as consumer confusion regarding the pricing of sustainable versus conventional products. Interestingly, the threat from suppliers in the sustainable fashion sector is low, indicating a relatively stable relationship. Despite challenges, the growing awareness of environmental issues in Indonesia presents an opportunity for sustainable fashion businesses to enhance their competitive standing and expand their market share for a more environmentally friendly future. To strengthen the position of sustainable fashion in Indonesia, the focus should be on brand differentiation through storytelling and a unique identity. Innovate products for quality and durability to counter fast fashion trends. Launch educational campaigns, collaborate with like-minded partners, and adopt transparent supply chain practices. Implement competitive pricing, engage customers through loyalty programs, and contribute to the local community, establishing a strong presence in the growing market for sustainable fashion.

Block chain is a computerized data set containing data (like records of monetary exchanges) that can be at the same time utilized and shared inside an enormous decentralized, openly open organization. Block chain development has been a prominent occurrence of changing the statutes of wellbeing in money related trades and information exchange. It offers an extraordinary development for data integration with security. Block chain relies upon the norms of understanding, decentralization, and cryptography for following the trust in trades. In any case, block chain security issues have continued to agitate various affiliations and early adopters. It is sure that, even the grounded block chain new organizations experience burdens in block chain security. Without a doubt, block chain innovation has seen a far-reaching adaption lately. Aside from beginning adaption into digital currencies, today it is being utilized in medical care, land, shrewd contacts, and so forth.  The ill-advised execution of innovation has been the reason for some block chain block protection concern, which can put the block chain vulnerable and can permit the aggressors to play out a few noxious exercises. To address the secrecy to the sensitive information in the Block chain organization, a proposed method namely progressive secure key administration for Block-Chain Technology with Lagrange Interpolation (PKABCLI) has been presented in this paper.

The relocation of the country's capital has a significant impact on the economy of the surrounding cities and caused rapid population growth and at the same time does not improve the city's environmental and planning capabilities. Data from the Central Statistics Agency shows that in the ten years from 2010 to 2020, the population of Balikpapan City increased by around 130,739 people and poverty in Balikpapan City in 2019 reached 15,780 people and in 2020 it reached 17,020 people. as many as 688,318 people. The increase in the number of poor people is caused by many factors, starting from inflation, Human Development Index (HDI), education, labor, unemployment rate, Gross Regional Domestic Product (GRDP), and average per capita expenditure. Dynamic systems have two main elements, namely Causal Loop Diagrams (CLD) and Stock Flow Diagrams (SFD). This research aims to determine the impact of moving the capital city from Jakarta to Nusantara on poverty levels in Balikpapan. The results obtained are based on the research graph, namely that moving the country's capital has a significant effect on the poverty level in the Balikpapan city, moving the country's capital resulted in population mobilization and an insignificant increase in the number of births. Along with increasing opportunities and employment opportunities. Minimize this condition, several efforts can be made, namely by carrying out campaigns on the use of contraceptives and family planning programs to reduce birth rates, especially for people who are classified as poor, as well as providing training and expanding job opportunities for local workers.