Publications

Abstract

Insurance company are certainly has a rich of data from their business process. One of the data is related to business process sales. From this sales data can be used to analyze the condition of a company whether the condition of the company is in a good condition or not. The purpose of this research is to develop a technique to analyze this data from the company. The method used to implement the data analysis in this paper is to design a data warehouse. Use ninestep methodology as the method for design data warehouse and Pentaho as a tool for ETL (Extract, Transform, Load), OLAP analysis and reporting data, the results of this research concluded that the implementation of data warehouse for perform data analysis and reporting better and more effective.

Abstract

As the airline company in Indonesia which is the one of domestic leading airlines, Sriwijya Air has been created the electronic voucher called e-voucher Sriwijaya Air for loyal customers. The e-voucher is used as a flight ticket payment instead of cash payment to buy a ticket. The e-voucher consists of some attributes such as destination, flown date, and flight class. Particularly, a marketing manager needs to review the utilization of e-voucher when a ticket has been approved in every year. The proposed solution is to redeploy existing OLTP database into data warehouse. The data warehouse already developed using nine-step Kimball's methodology. All data will be analyzed using OLAP to present a report in a visual form such as dashboard. Furthermore, airlines company can produce an analysis report using business intelligence.

Abstract

Sarcasm detection is an important task in natural language processing (NLP). Sarcasm flips the polarity of a sentence and will affect the accuracy of sentiment analysis task. Recent researches incorporate machine learning and deep learning methods to detect sarcasm. Sarcasm can be detected by the occurrence of context disparity. This feature can be detected by observing the similarity score of each word in the sentence. Word embedding vector is used to calculate word similarity score. In this work, the word similarity score is incorporated as an augmented feature in the deep learning model. Three augmenting schemes in deep learning models are observed. Results show that in general, a word similarity score boosts the performance of the classifier. The accuracy of 85.625% with F-Measure of 84.884% was achieved at its best.

Abstract

Data clustering is a well-known data mining approach that usually used to minimizes the intra distance but maximizes inter distance of each data center. The cluster problem has been proved to be an NP-hard problem. In this paper, a hybrid algorithm based on Whole optimization algorithm (WOA) and Crow search algorithm (CSA) is proposed, namely HWCA. The HWCA algorithm has the advantages of the search strategy of the WOA and CSA. In addition to, there are two operators used to improve the quality of solution, namely hybrid individual operator and enhance diversity operator. The hybrid individual operator is used to exchanges individuals from the WOA and CSA systems by using the roulette wheel approach. In other hand, the HWCA performs enhance diversity operator to improve the quality of each system. More over, the HWCA is incorporated with center optimization strategy to enhance diversity of each system. In the performance evaluation, the proposed MPGO algorithm was comparison WOA and CSA algorithm with six well-known UCI benchmarks. The results show that the proposed algorithm has a higher measure of accuracy rate with comparison algorithms.

Abstract

Bank XYZ is a bank in Bandung that gets profit from customers who borrow money. According to Bank Indonesia (BI) standars, if a bank has a non performing loan (NPL) or a value above 5% so the bank suffers losses. In this case, the bank must have a strategy to reduce this value to be stable. Bank XYZ concern about performance of collectors because the collector is the core of the bank. The solution for this case study is using business intelligence carried on the data warehouse and OLAP development. So this paper describes how important the selection of data that can help managers to make decision so that performance can be better.

Abstract

Reporting using query script mostly takes the long process. It makes the company is too late to provide the strategy decision. This also results inefficient way because the updating and changing SQL query to be adjusted for matching the requirements of decision makers. So, this paper describes how to implement the data warehouse technology to create the fastest way to make a report based on the requirements without customize the SQL query and just read the required data only. With Kimball methodology, data could be reported in various forms and the decision makers could take the best decision in eProcurement System.

Abstract

As the one of Indonesian association of construction service companies, the association ensure to recommend and record every construction service company (their members) to works according to valid Indonesian law and constitution. The problem in this association, as the job is to give detailed reports to government, investor either domestic or international, and every institutions that need information such as market needs, resource developments, and improvement of construction technologies, is to create queries for every data from tables in MySQL to create reports quickly, efficiently, and automatic. Example of reporting needs are: In what month construction project done at the most within 1 year; Project duration, project cost, and experience at the most for each construction company; or amount of projects based on source of funds (APBN, APBD, LOAN PEMERINTAH, BUMN, or SWASTA) for each construction companies. Recommended solution is using Data Warehouse where it has structured storage and can analyze data with OLAP that has capability to process and visualize data at high speed. To construct the Data Warehouse, the design used Kimball Method so this association company will have capability to generate report according to every instances' needs.

Abstract

As an online digital music content provider, company PT ABC has a portal that contains songs that can be streamed by customers. The music director has been using global trend, i.e. radio top music charts to produce favorite song list. This study will utilize data warehouse and business intelligence for PT ABC's marketing and sales strategy, e.g. to improve its service to customers, to increase number of active users and the duration of streaming per user. OLTP data suggested for the data warehouse is the existing streaming transactions, which will be used to analyze customers' most preferred songs. The proposed method to design the data warehouse is using 9-steps from Kimball. The selected process for the data warehouse is customers' streaming and downloading process, with dimensions of location, time and song, with fact less table of the streaming itself. The result of analysis will be customers' most preferred play list based on several parameters, such as customers' locations, streaming hours or days and genre of songs.

Abstract

XYZ company is an online travel company that provides services for booking hotel and flight. As the companies grow fast, they need fast report to help the management create a decision for developing their product. They need this report to help them decide what the action they need to do based on the data they have for compete with fellow rival in online travel company. This data warehouse development has purpose to help provide a big picture of XYZ company's customers behavior through data in report generated. The data warehouse development uses some steps designed by Kimball. Information generated will be presented in dashboard or report. The data warehouse is expected to be able to provide quick and accurate information for management to choose best decision on next product development based on customer behavior.

Abstract

In this increasingly modern world, marketing is a very interesting job. If more products are purchased by customers then the salary received is also higher. One of important issue in PT. XYZ is how to choose which products are now being sought/searched by the customer. The goal of this paper is to create a system and report that can help marketing to choose which product suitable to be offered to customer. This paper proposes a data warehouse development through methodology designed by Kimball and Ross. Furthermore, the data can be analyzed using OLAP and then displayed on the dashboard. With this business solution, PT. XYZ can process and choose what kind of products are suitable for customer relatively faster. The result shows that the system can choose which products are suitable to be offered to customer from the dashboard display.

Abstract

Electronic ticket (eticket) provider services are growing fast in Indonesia, making the competition between companies increasingly intense. Moreover, most of them have the same service or feature for serving their customers. To get back the feedback of their customers, many companies use social media (Facebook and Twitter) for marketing activity or communicating directly with their customers. The development of current technology allows the company to take data from social media. Thus, many companies take social media data for analyses. This study proposed developing a data warehouse to analyze data in social media such as likes, comments, and sentiment. Since the sentiment is not provided directly from social media data, this study uses lexicon based classification to categorize the sentiment of users' comments. This data warehouse provides business intelligence to see the performance of the company based on their social media data. The data warehouse is built using three travel companies in Indonesia. As a result, this data warehouse provides the comparison of the performance based on the social media data.

Abstract

Nowadays, most universities have a lot of different ways in considering graduation eligibility for their students. The consideration can use the data which is generated by system online analytical processing (OLTP). However the OLTP system has a limitation to report intuitively. The aim of this research is to create the system using data warehouse which able to see the progress of performance student and the course failed in each term. This system is expected able to predict student's graduation eligibility. Research method of this research consists some steps to implement data warehouse and then is followed by generating the report and on-line analytical processing (OLAP) analysis. Evaluation is done by benchmarking current system with the proposed system. The result shows the system can provide data for the graduation eligibility.

Abstract

The Constitutional Court of The Republic of Indonesia is an institution which has authority to judge and examine constitutions. In this institution, each component has responsibility to manage their own finance and budgeting. Based on this case, they need a solution to summarize the amount and absorption of the budget in every component. This paper proposes a solution to design a data warehouse model to process and analyse the down payment administration data. The nine steps design methodology for developing data warehouse is implemented in this work. This paper aims to bring some benefit for The Constitutional Court, especially in form of information about down payment absorption for every component each year. The result is presented in form of pdf report and informative dashboard using data warehouse tools.

Abstract

The problem with telecommunications companies today is that transactional data is more extensive than existing source tables. This makes business reporting less efficient and overwhelms query processing results in data warehouses so that they do not meet business requirements. The fast and complex evolution of the digital world must be scalable to the data warehouse process, so that the authors implement it in the data warehouse using massive parallel processing (MPP) with the Greenplum database, so that business users can get reports faster and more optimally. This case study explains how the MPP system implements and measures the performance of the Greenplum database by performing complex queries in the data warehouse with parallel processing. Therefore, this case study analyzes whether the use of MPP systems can measure the scalability of throughput and the response time in the data warehouse so that system performance in the Greenplum database remains stable for daily, weekly, and monthly operations.

Abstract

Currently, social media are commonly used by business organizations to get many advantages. Through social media, business gets feedback from their customer by giving them a room for sharing opinion or comment. This kind of customer engagement became a tool of marketing and promotion. This research proposes investigating the customer engagement by analysis the comments on social media (Facebook and Twitter) in transport online. This study investigates by mining the comments of fan page Facebook and tweet of Twitter in three transports online in Indonesia; Gojek, Grab, and Uber using the API service which is provided both of social media. The data comments are classified into some categories, positive, negative, and neutral sentiment using TF-IDF. The result shows that the category "Feedback system by driver" and "Feedback system by user" have the most comments for three means of transports online, while category "Service quality for driver" has the smallest comments. The study also reveals that the most comments are complaining. This feedback of social media can be used to evaluate the performance of these business transport online.

Abstract

As a big hotel which has many branches in Indonesia, a hotel should need the express report for business development in order to take decision. This paper proposes data warehouse for supporting business in XYZ hotel to get better information about customers data of each branches for taking decision. The data warehouse development consists nine step methodology designed by Kimball and Ross. Furthermore, the data is able to be presented in dashboard or report corresponding to the user to simplify the data presentation, The data warehouse is used to integrate the data sources needed to provide quick and accurate information.

Abstract

Currently, the capability to present reports or data accurately, fast and insightfully is highly required for the company to make data-driven decision. This paper is intended to solve the problem in one company which serves more than sixteen professional companies in South East Asia area. This report is useful to make decisions in this company. The method chosen to develop the data warehouse along with its analytics and reports is Kimball methodology which has been introduced since the mid-1980s and has been used by a lot of prior researchers. As the data can be displayed in various form as it needed, the stakeholder can make the data-driven decision which benefits this company to perform better in the market.

Abstract

As the main public company in telecommunication and broadband business in Indonesia, PT XYZ has always tried to ensure adequate wifi access service to meet the needs of broadband consumers. This wifi service, called wifi-id, uses an Authentication, Authorization, Accounting (AAA) server by collaborating with the other network providers. This study was based on the need of PT. XYZ to present reports or data quickly when needed, especially when PT. XYZ needs to reconcile the total monthly customer usage with business partners in order to do billing revenue sharing partnership. The problem arises because the script of CDR (called data record), which represents the use of broadband consumers, is stored in the form of CSV file only. It makes it difficult to make a report of customer access which is needed by PT. XYZ. The suggested solution is to move the existing data into a more structured storage in data warehouse. Data warehouse development was done through a nine-step methodology designed by Kimball and Ross. Furthermore, the data can be analyzed using OLAP to present the data in a visual form such as report or dashboard. With this solution, PT. XYZ can process and present the report relatively faster. Additionally, PT. XYZ will also get more benefit from the data stored in the form of information.

Abstract

The accreditation aims assuring the quality the quality of the institution education. The institution needs the comprehensive documents for giving the information accurately before reviewed by assessor. Therefore, academic documents should be stored effectively to ease fulfilling the requirement of accreditation. However, the data are generally derived from various sources, various types, not structured and dispersed. This paper proposes designing a data warehouse to integrate all various data to prepare a good academic document for accreditation in a university. The data warehouse is built using nine steps that was introduced by Kimball. This method is applied to produce a data warehouse based on the accreditation assessment focusing in academic part. The data warehouse shows that it can analyse the data to prepare the accreditation assessment documents.

Abstract

This article discusses the analysis of customer loyalty using three data mining methods: C4. 5, Naive Bayes, and Nearest Neighbor Algorithms and real-world empirical data. The data contain ten attributes related to the customer loyalty and are obtained from a national multimedia company in Indonesia. The dataset contains 2269 records. The study also evaluates the effects of the size of the training data to the accuracy of the classification. The results suggest that C4. 5 algorithm produces highest classification accuracy at the order of 81% followed by the methods of Naive Bayes 76% and Nearest Neighbor 55%. In addition, the numerical evaluation also suggests that the proportion of 80% is optimal for the training set.