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Utilization of Business Intelligence in Sales Information Systems
Get PDFBusiness intelligence is one of the concepts that can facilitate the process of processing data of a company which will later become the basis for the decision-making process of the sales process. Distributor company needs an information system that can help the company in managing and analyzing data and can make sales and profit predictions in the future. This study aims to create an information system that can visualize data analysis and the results of forecasting sales data by avocado fruit distributor companies. In this study, we will apply the concept of Business Intelligence using Power BI Desktop which is equipped with sales prediction analysis on the sales information system. The data processing process in this study uses the process of integrating Excel tools with Power BI Desktop. The dataset of sales in this study was obtained from the Kaggle site and the software development in this study using the SDLC (system development life cycle) waterfall development method. In this study, we found that the development of business intelligence in the sales information system provides convenience that can be felt by distributors, namely in terms of revenue and time. In this case, forecasting is done with the forecast feature in Power BI Desktop with a confidence interval of 95%
Operational Supply Chain Risk Management on Apparel Industry Based on Supply Chain Operation Reference (SCOR)
Get PDFThe occurrence of uncertainty requires proper handling to avoid the adverse effects called risk. Risk tends to arise in the supply chain process called supply chain risk. The purpose of this research is to identify the possible level of risk that occurs and has the potential to disrupt supply chain activities, determine priority risk sources based on Supply Chain Operation References (SCOR). The object of this research is the apparel industry, which is a company engaged in fashion and apparel production. This study uses a qualitative and quantitative approach, the value of the instrument is assessed based on the results of the Aggregate Risk Potential (ARP) calculation in the House of Risk method phase 1. The results showed that there were 39 correlations between risk events and risk agents, with 22 correlations with a high scale and 1 correlation with a low scale, and 15 correlations on a medium scale
Rainfall prediction in Blora regency using mamdani's fuzzy inference system
Get PDFIn the case study of weather prediction, there are several tests that have been carried out by several figures using the fuzzy method, such as the Tsukamoto fuzzy, Adaptive Neuro Fuzzy Inference System (ANFIS), Time Series, and Sugeno. And each method has its own advantages and disadvantages. For example, the Tsukamoto fuzzy has a weakness, this method does not follow the rules strictly, the composition of the rules where the output is always crisp even though the input is fuzzy, ANFIS has the disadvantage of requiring a large amount of data. which is used as a reference for calculating data patterns and the number of intervals when calculating data patterns and Sugeno has the disadvantage of having less stable accuracy results even though some tests have been able to get fairly accurate results. In research on the implementation of the Mamdani fuzzy inference system method using the climatological dataset of Blora Regency to predict rainfall, it can be concluded as follows: (1) The fuzzy logic of the Mamdani method can be used to predict the level of rainfall in the city of Blora by taking into account the factors that affect the weather, including temperature, wind speed, humidity, duration of irradiation and rainfall. (2) Fuzzy logic for prediction with uncertain input values is able to produce crisp output because fuzzy logic has tolerance for inaccurate data. (3) The results of the accuracy of calculations using the Mamdani fuzzy inference system method to predict rainfall in Blora Regency are 66%
Improved logistics service quality for goods quality delivery services of companies using analytical hierarchy process
Get PDFLogistics plays a role in the smooth transaction between companies because it is a facilitator of buying and selling goods and services to fulfill the supply orders of consumer companies. This study aims to analyze how the impact of improved Logistic Service Quality (LSQ) for quality of goods delivery services by using LSQ dimensions from previous research. Sample data is obtained through the dissemination of questionnaires which are then processed quantitatively with convergent validity and reliability tests. Data processing with a sample count of 61 respondents. The results of this study show that there is the main dimension of logistic service quality in improving the quality of service, namely ordering condition, time, and information quality. Each comparison factor is tested for consistency using the Analytical Hierarchy Process (AHP), each of the main criteria has a consistency value of less than 0.1 so that the main criteria tested have a consistent comparison matrix and can be the basis of decision making for companies in choosing alternative criteria priorities
Usefulness factors to predict the continuance intention using mobile payment, case study: GO-Pay, OVO, Dana
Get PDFThe advancement of information technology continues to grow in line with the increasing years. The benefits gained from the advancement of information technology make all aspects of human life today can not be separated from information technology and also ikut encouragethe emergence ofinnovations in thedevelopment of informationtechnology, sepertinya payment is no longer conventionally nal but with mobile payment. This study aims to find out what useful factors influence the continuation of the intention to use mobile payment in the go-pay, OVO, and DANA case studies. Analysis of factors that influenced this study include: Computer Self Efficacy (CSE), Enjoyment (E), Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Confirmation (CON), Perceived Value (PV), Technical System Quality (TSQ), Satisfaction (SAT),and Continuance Intention (CI). This study uses random sampling techniques by collecting data utilizing google form containing 45 statements using five Likert-scale distributed online. The sample used in this study was 117 respondents. The statistical analysis techniques used in this study are Structural Equation Modeling (SEM) and use SMARTPLS 3.0 application as a tool to analyze the data. The results obtained are that Computer-Self Efficacy (CSE), Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) has no significant effect on Continuance Intention (CI). While Satisfaction (SAT), has a significant influence on Continuance Intention (CI)
Analysis of earthquake forecasting using random forest
Get PDFThe subject of forecasting earthquakes is an intriguing one to investigate. As a natural calamity, earthquakes continue to be devastating, not just to the economy but also to the lives of individuals. This gave rise to the concept of creating an early warning system against seismic catastrophes to minimize deaths. Researchers have been making earthquake forecasts and seismic hazard ratings of a location for a few years now. In this work, we attempt to forecast earthquakes before they occur using p-arrival data, which includes information on disaster arrival time and amplitude height from the arrival station. Several studies on earthquake prediction have been carried out so far and have developed and used the Random Forest method and one of the Machine Learning. According to [1], the process of predicting earthquakes has been studied for a long time, but there is still uncertainty due to the diversity and complexity of the earthquake phenomenon itself. According to [2], conducting a random forest prediction model to identify the structural safety status of buildings damaged by the earthquake is probabilistic. An earthquake's latitude, longitude, magnitude, and depth may be predicted using the random forest algorithm. A random forest with multioutput technique is employed, with variables being each station's recorded value and geographic position. This study's predictions were accurate to within 63 percent
Laptop selection decision support system according to buyer criteria with the simple additive weighting method
Get PDFAlong with the development of increasingly modern times, so that all activities require gadgets, including laptops. However, it is often found among prospective laptop buyers who are still confused in determining a laptop to suit their needs, for that purpose the purpose of this study is to help people who want to buy a laptop when choosing or who are looking for a laptop to get the right one for their needs. To achieve this goal, a decision support system is needed. The Decision Support System that will be used is the SAW (Simple Additive Weighting) method because this method can filter out several existing alternatives and based on predetermined criteria so that later you get the best alternative. By using this SAW method, a matrix normalization process is needed, the weight value of each attribute, and finally a ranking process that will determine the optimal alternative. The results obtained in this study are to be able to provide laptop advice to prospective buyers based on the specifications of the prospective buyers' needs and with a 100% accuracy level based on calculations from the decision support system
A combination of TDM and KSAM to determine initial feasible solution of transportation problems
Get PDFIn case of the Transportation Problem (TP), it was found that TP had equal the smallest so that the existing methods will be generated two or more IFS values. The newly developed algorithm is generated through a combination of Total Difference Method (TDM) and Karagul-Sahin Approximation Method (KSAM) algorithm, is capable to determine the initial feasible solution of TP. Based on the numerical illustration of TP example to evaluate the performance of the new proposed algorithm. The computational performances have been compared to the existing methods (TDM1 and KSAM) and the results shown this algorithm achieved better performance than the existing methods for TP example
Decision support system for choosing the best tourist attractions using simple additive weighting (SAW) method
Get PDFEvery year, various regions in Indonesia always have many tourists both local and foreign so as to provide benefits for the government and the surrounding local community. However, due to the Covid-19 pandemic, the tourism sector has slumped. Therefore, to revive the tourism sector in the new normal due to Covid-19, there needs to be various considerations. One of them, namely decision support system for choosing tourist attractions with facilities that meet health protocol standards in the new normal/adaptation of new habits. In this study, a case was raised with the aim of choosing the best tourist attractions in Kendal Regency, Central Java with several criteria determined, especially regarding facilities that comply with health protocols. The calculation in this study was done by Simple Additive Weighting (SAW) method. The research was conducted by determining alternatives, criteria, and weight values on each criterion. Then the calculation of the value of preferences and stamps to get the best alternative. From the calculations that have been done, the result of the best tourist attractions in Kendal is Tirto Arum Baru with a preference value of 0.766. However, due to the dynamic nature of the criteria and weight data, it is possible that at any time the selected data may change
Factors affecting interest in utilization and use of online shop (study on shopee customers)
Get PDFThe development of information technology has led to the emergence of various e-commerce services. One of them is engaged in the mobile marketplace, namely Shopee. Shopee as a mobile marketplace is always faced with competitors. Therefore, this study aims to determine the factors that influence the interest in the use and use of the online shop, especially the Shopee application. In this study, the UTAUT2 framework was used, where this framework is a framework that is often used to determine user intentions and behavior in using technology or applications. The UTAUT2 framework has seven main constructs and in this study one construct is added, namely trust. The results of this study indicate that the UTAUT2 framework with additional trust constructs has a positive regression weight for all UTAUT2 constructs and additional trust constructs except for the effort expectancy and hedonic motivation constructs. This shows that all UTAUT2 constructs and additional trust constructs have a positive effect on the intention to use the Shopee application when shopping online except for the effort expectancy and hedonic motivation constructs. Intention to use also has a positive effect on user behavior to use the Shopee application when shopping online