Transaction Lots Research Articles

Menyusun Display Barang dengan Data Mining Assosiation Rule Menggunakan Rapid Miner Algoritma FP-GROWTH

A cosmetic cheerful shop located in the Marelan area of Medan city is a shop that sells women's cosmetic equipment. The owner of a cheerful cosmetics shop is very disciplined in recording sales and purchases of goods. Every transaction is always recorded and stored in the Microsoft Excel application. Meanwhile, the Ceria Cosmetics store has been running since 2015 and has recorded lots of transactions, both sales and purchases. From 2015 until now the data has been increasing, and so far this data has only been a record and stored in a folder on the store's computer. From the piles of transaction data at the cheerful cosmetics store, the authors took the idea of research to utilize this pile of data. One of the applications of information technology that can be used to utilize the pile of data is the data mining technique. By using data mining, a pile of data from a cheerful cosmetic store can be used to find association patterns. And the application of data mining with association rules can use the FP-Growth algorithm. The FP-Growth algorithm can be used as an alternative to determine the most frequently occurring data set (frequent itemset) in a data set. Later, the combination patterns obtained in this study can be used to arrange the layout of goods (cosmetics) at the Ceria Cosmetics store in Medan Marelan.

An adapted Black Widow Optimization Algorithm for Financial Portfolio Optimization Problem with cardinalty and budget constraints

Financial Portfolio Optimization Problem (FPOP) is a cornerstone in quantitative investing and financial engineering, focusing on optimizing assets allocation to balance risk and expected return, a concept evolving since Harry Markowitz’s 1952 Mean-Variance model. This paper introduces a novel meta-heuristic approach based on the Black Widow Algorithm for Portfolio Optimization (BWAPO) to solve the FPOP. The new method addresses three versions of the portfolio optimization problems: the unconstrained version, the equality cardinality-constrained version, and the inequality cardinality-constrained version. New features are introduced for the BWAPO to adapt better to the problem, including (1) mating attraction and (2) differential evolution mutation strategy. The proposed BWAPO is evaluated against other metaheuristic approaches used in portfolio optimization from literature, and its performance demonstrates its effectiveness through comparative studies on benchmark datasets using multiple performance metrics, particularly in the unconstrained Mean-Variance portfolio optimization version. Additionally, when encountering cardinality constraint, the proposed approach yields competitive results, especially noticeable with smaller datasets. This leads to a focused examination of the outcomes arising from equality versus inequality cardinality constraints, intending to determine which constraint type is more effective in producing portfolios with higher returns. The paper also presents a comprehensive mathematical model that integrates real-world constraints such as transaction costs, transaction lots, and a dollar-denominated budget, in addition to cardinality and bounding constraints. The model assesses both equality/inequality cardinality constraint versions of the problem, revealing that the inequality constraint tends to offer a wider range of feasible solutions with increased return potential.

THE MODIFIED MEAN ABSOLUTE DEVIATION INTEGER LINEAR PROGRAMMING MODEL FOR GLOBAL PORTFOLIO ASSET ALLOCATION

This study develops a practical yet robust Mean Absolute Deviation (MAD) Mixed-Integer Linear Programming (MILP) model for a global investment portfolio tailored to the constraints faced by Malaysian retail investors, such as transactional fees and foreign currency exchange spreads, to provide more accurate estimations of portfolio returns. The MAD ILP model is modified to address these factors, aiming to enhance utility and efficiency. The study utilizes a Maybank 12-month fixed deposit cash account and ten selected Exchange-Traded Funds (ETFs) from iShares, Vanguard, and State Street Global Advisors for global portfolio construction. Forecasting techniques were utilized to generate expected returns for the ETFs and foreign currency exchange spreads. Based on the MAD model proposed by Konno and Wijayanayake (2001), the study introduces three modifications: incorporating transaction cost elements specific to Malaysian investors, including foreign currency exchange spreads in return calculations, and transforming the model from mixed-integer to pure integer model to accommodate minimum transaction lot constraint. Verification and validation exercises demonstrate the model’s ability to replicate real-world portfolio construction and reliable simulations. The model offers a practical tool for self-ascribed investors aiming to optimize global investment portfolios while considering unique constraints and transaction costs.

An uncertain bi-objective mean-entropy model for portfolio selection with realistic factors

In the imprecise investment environment, there are many indeterminate factors impacting security returns. This paper introduces a portfolio optimization problem where cross-entropy is utilized to control portfolio risk within the framework of uncertainty theory and presents an uncertain bi-objective mean-entropy portfolio selection model. To be more realistic, some realistic factors such as minimum transaction lots, dividend factors and tax factors are also considered. By introducing a risk preference coefficient, the bi-objective model is converted into a single-objective model and some equivalents are discussed. Additionally, a hybrid intelligent algorithm integrating a genetic algorithm with uncertain estimation is designed to solve the proposed model. Finally, a case study is executed to confirm the practicability of the model and the performance of the algorithm, and an empirical analysis based on the proposed model and the uncertain mean–variance model is developed to illustrate the advantage of the uncertain mean-entropy model in practical investment.

Variations Between Physical Banking and Internet Banking Usage amid COVID-19 Pandemic

The usage of banking functions through Internet is comfortable and time saving process, since the usage rates of different banking functions through Internet banking mechanism are very low. The present study aims to evaluate the variations between physical banking and internet banking and explores the problems faced by banking customers in using internet banking amid the COVID-19 pandemic. The primary data for the present study were collected from banking customers, who were identified on a random basis from three different areas of the Union Territory of Jammu and Kashmir. The total sample size was 1,200, comprising a breakup of 400 for each of the sampling areas of central Kashmir, south Kashmir and north Kashmir. Internet banking adoption is changing the physical usage of non-financial products and financial products worldwide. Today, a click of the mouse and mobile banking offer a lot of transactions regarding electronic non-financial products and electronic financial products. Still, the adoption rates of these products are very low. The present study has examined the situation of electronic banking adoption amid the COVID-19 pandemic, and hence, it is found that maximum number of customers are non-users of electronic non-financial products and electronic financial products. Amid the pandemic, the reason for non-usage of technology banking by a majority of customers was lack of awareness, technological barriers and security concerns. They also used physical banking activities and did not follow social distancing as suggested by the Government of India during March 2020. Therefore, it is the basic responsibility of the banking industry to motivate their customers and address their concerns regarding the usage of electronic non-financial products and electronic financial products, as the maximum number of banking customers are non-users of electronic non-financial products and electronic financial products. If the banking industry will address the concerns of banking customers regarding the usage of technology banking, then only a country like India with a huge population can have technological banking and environment-friendly banking and can face situations like the COVID-19 pandemic in future.

GIS-Based Business Permit Monitoring with SMS Notification

Nowadays, processing a business license undergo a lot of situations to be done. It takes a lot of time, effort and patience for able to acquire the needs of a particular. There are a lot of transactions and requirements to comply before having what you need. In Addition, dealing a lot of customers in an office that can cause overcrowded and noise disturbance. Also, one of the factor for processing a business license is a period of human adulthood, Senior citizen are in need of assistance by their relatives for filing their personal data and business information. Although there are a priority lane for them but still it can cause delay for others. Therefore, in order to gather business license in a fastest and easy way, developing a research study for the areas around Sagay City, Negros Occidental: Geographic Information System (GIS)-Based Business Permit Monitoring with SMS Notification. Its main purpose is to process big enterprise permits in easy and fastest way and also renew permits that is already expired through online using internet and mobile phones, laptop and PCs. Through the use of Business Permit Monitoring it helps the staff of Sagay City Licensing Deparment (SCLD) to track Personal records and Business records of every individual who is already registered. Also, through the use of GIS it helps the staff and users to identify the location of every businesses and find which one is already expired by the use of color-marker. For SMS Notification, its task is to send notification to businesses that is already expired.

Faktor-Faktor yang Mempengaruhi Generasi Milenial dan Z Terjebak Pinjaman Online

Online loans are a type of fintech development, service providers provide loans through technology. People make a lot of online loan transactions. The millennial and z generations are the largest online loan takers. Various factors cause the millennial and z generations to get trapped in online loans. Apart from that, online loans can be detrimental to the millennial and z generations if they are trapped in illegal online loans. This research aims to analyze the factors that influence the millennial and Z generations to take online loans. This type of research method is qualitative research in the form of literature study by collecting library data and reading to manage research materials. The data source is secondary data obtained from various writings such as published articles, websites, books and literature from the OJK and other financial institutions. The results of the discussion in this article are that the millennial and z generations are stuck with online loans, influenced by lifestyle factors and financial literacy. A hedonic lifestyle makes the millennial and z generations trapped in online loans. Low financial literacy can mean that the millennial and z generations don't know how to manage their finances, making them trapped in online loans.

Survey on Government Fund Allocation Using Blockchain

Abstract: Governments have a lot of responsibilities, which involves a lot of money transactions for various projects, employees, and farmer schemes. Corruption is a big problem as it's hard to track and can slow progress. We can solve this by using blockchain technology. Blockchain is a list of records that are linked and secured using cryptography. Each record contains transaction data, a timestamp, and a cryptographic hash of the previous record. We use security algorithms like AES encryption and decryption to protect the data. This project proposes a system to track government funds using key pair generation, metadata file decryption, and data verification algorithms.

Sistem Informasi Pengelolaan Kas Kecil Pendapatan Barang Masuk dan Keluar pada PT. Universal Carpet and Rugs Berbasis Web

PT. Universal Carpet and Rugs is a company engaged in the carpet textile industry. This company carries out quite a lot of transactions involving petty cash in its company activities and until now the process of managing petty cash is still carried out manually by the finance department by recording every petty cash transaction which causes frequent data loss or human errors which can cause losses. on the company. From the description of the problems that occurred, a Web-Based Petty Cash Management Information System was designed and built at PT. Universal Carpet and Rugs with a proposed budget request process, budget realization process and budget realization data collection process added from an analysis of the system that is already running and is expected to be able solve existing problems. The methods used in completing this final project are observation methods, interview methods, and literature study methods. While the system modeling uses the Unified Modeling Language (UML) method using the PHP programming language, while the software / tools used are MySQL as the database. This Petty Cash Information System can be a solution that can be used to work on the cash management process that runs at PT. Universal Carpet and Rugs.

Cardless Transaction in ATM

Abstract: A lot of financial transactions are carried out using automated teller machines, or ATMs. However, ATM frauds, such as card skimming and PIN theft, continue to be a major concern for both customers and financial institutions. Face detection technology has come to light as a promising solution to increase the security of ATM transactions. Face detection technology can authenticate users by precisely identifying them based on their facial features, adding yet another level of security to ATM transaction processes. This research paper provides an overview of the use of face detection technology in ATM transactions and highlights how it has the potential to improve security by reducing fraud and unauthorised access.

Optimization of tips selection on the IOTA tangle for securing blockchain-based IoT transactions

Data integrity and security protection are needed in the Internet of Things. IOTA technology with a Directed Acyclic Graph (DAG) structure is a solution to realize secure and scalable data transactions. Recent research IOTA is still faced with the issue of being vulnerable to splitting attacks and left-behind transactions. The splitting attack causes the network to confirm conflict transactions. Then, left-behind transactions cause the network to generate transactions that will not be confirmed. The selection tip weighted random walk (WRW) algorithm uses the Markov Chain Monte Carlo (MCMC) to overcome these two issues by applying the appropriate bias parameter (α). However, when the α is too large, it will produce a lot of left-behind transactions. Determining the optimal value of α is still an important research topic today. An E-IOTA study that gives several α values statically with random selection but can still produce more left-behind transactions than pure WRW. This paper proposes an optimization of the tip selection algorithm (DA-IOTA) to determine the optimal alpha (α) using an approach to dynamically determine each WRW step. The experimental results show that DA-IOTA produces fewer left-behind transactions than MCMC (WRW) and E-IOTA which use α parameters statically.

Harmonisasi Kewenangan Bank Indonesia dan Otoritas Jasa Keuangan Terkait Penerapan Regulatory Sandbox dalam Inovasi Berbasis Fintech di Indonesia

The progress of technological innovation in the era of globalization was so quickly. The digital technologi gives special colour in the financial business sector. During the pandemic, a lot of people switch use online transactions because of the implementation of restrictions community activities system applicate by the government. Behind the high growth graph, it turns out that in practice financial tecnology (fintech) are reaping various polemics in the community. The lack of knowledge of digital financial literacy has resulted in many citizens being entangled in the dynamics of illegal fintech lending cases. The fintech requires Bank Indonesia and the Financial Services Authority carry out intensive supervision of the legality of digital financial innovation companies through the Regulatory Sandbox mechanism. This article uses normative legal research as a reference basis in determining legal procedures related to the polemic of Fintech-based innovation companies in Indonesia. The analytical method used is qualitative and described descriptively. The results of this study are to find out the harmonization of BI and OJK authorities through the implementation of the Regulatory Sandbox mechanism by establishing PBI No.19 /12 /PBI /2017 and POJK No. 13/ POJK.02/ 2018 as the legal basis for the legalization of fintech innovations before they are widely circulated in the community.

Mean-Variance Programming Framework in Markowitz Modeling

For mathematical frameworks in place, which are applied to portfolio optimization problems, the majority come in the form of risk minimization – relative to the return parameter. When it comes to the quadratic programming framework, in relation to Markowitz, its associated challenges have been countered when considerations are made to recent trends in algorithmic scholarly investigations. In particular, a linear risk function has been introduced, especially in response to the need to address problems of portfolio selection, given real constraints. In this study, the main aim is to address the problem of portfolio selection in relation to minimum transaction lots. Also, the paper focuses on an improved search model that is applied to active constrained, whereby solutions are developed for the integer programming algorithm. The proposed model is that which focuses on the relaxed problem’s solution initially, before establishing solutions that are deemed closer to the continuous solutions..

Aplikasi Penerimaan dan Pengeluaran Kas (ARILUKAS) Menggunakan SDLC Waterfall

Educational institutions are one of the institutions that have a lot of financial transactions in their daily activities, for example new student registration fees, payment of school fees and even grants from the government. Assa'adatul Mahmudiyah, which is our research site, is one of the educational institutions that also has a lot of cash flow transactions. However, problems arise when these transactions are still recorded manually in books or simple spreadsheet files. These problems include rewriting when making reports, calculating and checking funds manually on cash balances and so on. Therefore, making a cash flow application is an alternative to this problem. Data was collected by observing the research site, reference the literature and conducting interviews with the cash manager. While the waterfall method the researchers took as a software development method. With this cash flow application, it can speed up users in making reports and reduce errors when recording cash in and cash out
 Index Terms— Cash flow application, Cash in and cash out, Waterfall

Multi-period uncertain portfolio optimization model with minimum transaction lots and dynamic risk preference

An accurate variable description of security returns is necessary to establish a valid portfolio optimization model. It is usually assumed to be a random variable when the historical data of security returns are sufficient. However, when historical data are too limited to estimate its probability distribution, uncertain variables are employed to characterize security returns to be effective. This paper focuses on a multi-period portfolio optimization problem in uncertain environment with the consideration of minimum transaction lots. Different from the previous multi-period work assuming the total available wealth in the end of the investment horizon is consistently in an exponential format, our study provides a simplified additive format of the total wealth, which may make the process of experimental calculation concise, since it is a linear function of decision variables. Besides, we consider the investor’s dynamic risk preference along the whole investment horizon. With these realistic constraints derived from the complex financial markets, we build a multi-period mean-VaR (value-at-risk) model with the objective of maximizing the terminal wealth under the risk control over the whole investment. Genetic algorithm is used to solve the proposed model, and two numerical examples are given to illustrate the effectiveness of the proposed approach.

Survey of big data programming frameworks

Advances in ICT today has made data more voluminous and multifarious and its being transferred at high speed. Applications in cloud like Yahoo weather, Facebook photo gallery, and Google search index are changing the IT landscape in a profound way. Reasons for these trend includes scientific organizations solving big problems related to high performance computing workloads, diverse public services being digitized; mobile devices, global positioning systems, sensors, social media, medical imaging, financial transaction logs and lots of them are all sources of massive data generating large sets of complex data. These applications are evolving to be data-intensive, processing very large volumes of data hence, require dynamically scalable, virtualized resources to handle them. This paper compared several of these big data programming frameworks used in data-intensive processes. Area of strengths and weaknesses of these frameworks were highlighted with the intention that future framework will harness all positives from this study for a better system.Keywords: Big Data, Framework, Hadoop, Analytics, Workload, Resource Allocation

A Bitcoin payment network with reduced transaction fees and confirmation times

The high transaction fees and confirmation times made Bitcoin unfeasible for many applications when the payments are in small amounts and require instant approval. As a result, many other cryptocurrencies were introduced for addressing these issues, but the Bitcoin network is still the most widely used payment system. Without doubt, to benefit from its network of users, there is a need for novel solutions that can successfully address the problems about high transaction fees and transaction verification times. Recently, payment network ideas have been introduced including the Lightning Network (LN) which exploits off-chain bidirectional payment channels between parties. As off-chain links can be configured to perform aggregated transactions at certain intervals without writing to blockchain, this would not only reduce the transaction fees but also decrease the verification times significantly. Nevertheless, LN still deploys relay nodes which charge fees and its growth leads certain nodes to become monopolies which defeat the very purpose of decentralization. Despite the thought that LN will provide a “scale-free network mechanism” along with high decentralization, how to form such a network among multiple parties is never studied before. Therefore, in this paper, by exploiting the LN, we offer to form a purely decentralized payment network which will allow Bitcoin to handle a lot of transactions with enough capacity. The idea is to form a network of retailers (i.e., nodes) which do business with Bitcoin by connecting them through off-chain links (i.e., payment channels) based on the business needs. The problem is initially modeled as a network optimization but since scalability would be a concern the next steps follow a heuristic approach where certain links are pruned to force evenly distributed payment flows while minimizing the total investments made to create initial off-chain links. The evaluations demonstrate the extent of scalability of the network along with the trade-offs between the distribution of flows and the initial flow capacities of the nodes.

Robust covariance estimators for mean-variance portfolio optimization with transaction lots

This study presents an improvement to the mean-variance portfolio optimization model, by considering both the integer transaction lots and a robust estimator of the covariance matrices. Four robust estimators were tested, namely the Minimum Covariance Determinant, the S, the MM, and the Orthogonalized Gnanadesikan–Kettenring estimator. These integer optimization problems were solved using genetic algorithms. We introduce the lot turnover measure, a modified portfolio turnover, and the Robust Sharpe Ratio as the measure of portfolio performance. Based on the simulation studies and the empirical results, this study shows that the robust estimators outperform the classical MLE when data contain outliers and when the lots have moderate sizes, e.g. 500 shares or less per lot.

Antecedents of Blockchain Technology Adoption Intentions in the Supply Chain

Supply chain involves a lot of transactions among the stakeholders. Blockchain technology will make a revolutionary change the way how transactions are being carried out. Blockchain removes all the disadvantages which are related to trust among stakeholders and gives better visibility and transparency. The present study explores factors that affect blockchain technology adoption in the supply chain. The current study is based on the extended unified theory of acceptance and use of technology (UTAUT2) with trust model. Data was collected from 363 supply chain practitioners from India. The results of the present study indicate that behavioural intentions are positively and significantly influenced by performance expectancy, effort expectancy, hedonic motivation, price value, and trust. The study also lists out various aspects for future research regarding the implementation of blockchain in supply chain management.

An Approach Based on Active Constraint Strategy for Solving The Portfolio Optimization Problem

The mathematical model of portfolio optimization has been largely written in terms of minimizing the risk, given the return. The difficulty of this model is to deal with the quadratic programming model due to Markowitz. This situation has been overcome by the recent progress in algorithmic research, and the introduction of linear risk function. This paper deals with the portfolio selection problem with minimum transaction lots. A neighbourhood search algorithm based on active constrained strategy is proposed to solve the mixed integer programming model. The algorithm starts from the solution of the relaxed problem to find a solution which is close to the continuous solution.