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Journal of Information Systems Engineering and Business Intelligence

JISEBI
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Published by Universitas Airlangga

ISSN : - EISSN : - DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal ini menerima makalah ilmiah dengan fokus pada Rekayasa Sistem Informasi ( Information System Engineering) dan Sistem Bisnis Cerdas (Business Intelligence) Rekayasa Sistem Informasi ( Information System Engineering) adalah Pendekatan multidisiplin terhadap aktifitas yang berkaitan dengan pengembangan dan pengelolaan sistem informasi dalam pencapaian tujuan organisasi. ruang lingkup makalah ilmiah Information Systems Engineering meliputi (namun tidak terbatas): -Pengembangan, pengelolaan, serta pemanfaatan Sistem Informasi. -Tata Kelola Organisasi, -Enterprise Resource Planning, -Enterprise Architecture Planning, -Knowledge Management. Sistem Bisnis Cerdas (Business Intelligence) Mengkaji teknik untuk melakukan transformasi data mentah menjadi informasi yang berguna dalam pengambilan keputusan. mengidentifikasi peluang baru serta mengimplementasikan strategi bisnis berdasarkan informasi yang diolah dari data sehingga menciptakan keunggulan kompetitif. ruang lingkup makalah ilmiah Business Intelligence meliputi (namun tidak terbatas): -Data mining, -Text mining, -Data warehouse, -Online Analytical Processing, -Artificial Intelligence, -Decision Support System.

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Articles 11 Documents

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Search results for , issue "Vol. 5 No. 2 (2019): October" : 11 Documents clear

Graph Database Schema for Multimodal Transportation in Semarang Panji Wisnu Wirawan; Djalal Er Riyanto; Dinar Mutiara Kusumo Nugraheni; Yasmin Yasmin
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Semarang has broad area that cannot be covered entirely by single transportation mode. To reach a specific location, people often use more than one public transportation mode. Apart from Bus Rapid Transit, another exist namely angkot or city transportation. Multimodal traveler information is then required to help passenger searching for a route. Several studies of multimodal traveler information system has been conducted, however the data model for multimodal transportation did not conceived in detail.Objective: Proposes a database of multimodal transportation design using graph data model by taking Semarang as a case study.Method: We create our model in oriented entity-relationship diagram (O-ERD) and map this O-ERD to the graph database schema.Result: We develop our data model in graph database schema and we implement the model using Neo4J graph database for validation purpose. Our model consist of three graph node label namely Shelter, Angkot Stopper, and Closer Place. To validate our model, we execute a search query using the Cypher query to look for location with closer place to it.Conclusion: Our data model was successfully developed and implemented. Searching transportation route in the implementation of our model has been conducted using cypher query. It can successfully display all possible paths and routes. Our query can distinguish between one mode of transportation with another.Keywords: Graph database, Multimodal transportation, Neo4j, Cypher

Fertilizer Production Planning Optimization Using Particle Swarm Optimization-Genetic Algorithm Dinita Rahmalia; Teguh Herlambang; Thomy Eko Saputro
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: The applications of constrained optimization have been developed in many problems. One of them is production planning. Production planning is the important part for controlling the cost spent by the company.Objective: This research identifies about production planning optimization and algorithm to solve it in approaching. Production planning model is linear programming model with constraints : production, worker, and inventory.Methods: In this paper, we use heurisitic Particle Swarm Optimization-Genetic Algorithm (PSOGA) for solving production planning optimization. PSOGA is the algorithm combining Particle Swarm Optimization (PSO) and mutation operator of Genetic Algorithm (GA) to improve optimal solution resulted by PSO. Three simulations using three different mutation probabilies : 0, 0.01 and 0.7 are applied to PSOGA. Futhermore, some mutation probabilities in PSOGA will be simulated and percent of improvement will be computed.Results: From the simulations, PSOGA can improve optimal solution of PSO and the position of improvement is also determined by mutation probability. The small mutation probability gives smaller chance to the particle to explore and form new solution so that the position of improvement of small mutation probability is in middle of iteration. The large mutation probability gives larger chance to the particle to explore and form new solution so that the position of improvement of large mutation probability is in early of iteration.Conclusion: Overall, the simulations show that PSOGA can improve optimal solution resulted by PSO and therefore it can give optimal cost spent by the company for the planning.Keywords: Constrained Optimization, Genetic Algorithm, Linear Programming, Particle Swarm Optimization, Production Planning

Relevance Feedback using Genetic Algorithm on Information Retrieval for Indonesian Language Documents Salman Dziyaul Azmi; Retno Kusumaningrum
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: The Rapid growth of technological developments in Indonesia had resulted in a growing amount of information. Therefore, a new information retrieval environment is necessary for finding documents that are in accordance with the user’s information needs.Objective: The purpose of this study is to uncover the differences between using Relevance Feedback (RF) with genetic algorithm and standard information retrieval systems without relevance feedback for the Indonesian language documents.Methods: The standard Information Retrieval (IR) System uses Sastrawi stemmer and Vector Space Model, while Genetic Algorithm-based (GA-based) relevance feedback uses Roulette-wheel selection and crossover recombination. The evaluation metrics are Mean Average Precision (MAP) and average recall based on user judgments.Results: By using two Indonesian language document datasets, namely abstract thesis and news dataset, the results show 15.2% and 28.6% increase in the corresponding MAP values for both datasets as opposed to the standard Information Retrieval System. A respective 7.1% and 10.5% improvement on the recall value at 10th position was also observed for both datasets. The best obtained genetic algorithm parameters for abstract thesis datasets were a population size of 20 with 0.7 crossover probability and 0.2 mutation probability, while for news dataset, the best obtained genetic algorithm parameters were a population size of 10 with 0.5 crossover probability and 0.2 mutation probability.Conclusion: Genetic Algorithm-based relevance feedback increases both values of MAP and average recall at 10th position of retrieved document. Generally, the best genetic algorithm parameters are as follows, mutation probability is 0.2, whereas the size of population size and crossover probability depends on the size of dataset and length of the query.Keywords: Genetic Algorithm, Information Retrieval, Indonesian language document, Mean Average Precision, Relevance Feedback

One-Pot Synthesis of Requirements Elicitation for Operational BI (OBI) System: in the Context of the Modern Business Environment A.D.N. Sarma
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Requirement elicitation is the first step for any project. The available BI requirement elicitation approaches are focused more towards: the top pyramid of the management, less focus on the business aspect of an organization, historical in nature, emphasis on data mining and data warehousing aspects, no clear separation between requirements, and lack of proper linkage between the requirements. The demand of BI shifts towards the operational front for last couple of years. The use of Operational BI is gaining more popularity among industry and business communities because of increased demand of real time BI. It provides a powerful analysis of both operational and business information in current time for all levels of the users in the organization.Objective: In the modern business environment, the business operates on networks that demands multi-level decision-making capabilities as compared to the traditional business approaches. Operational BI is one of the business information systems that support the modern business environment and provides timely decision-making information to all the users in the organization. The requirement elicitation methodology for Operational BI system is found open for research. A new approach for requirement elicitation for an Operational BI system is presented in this paper, which highly suits to the organizations in the modern business environment.Methods: A top down technique is employed in the proposed requirements methodology that focuses on the business context of an organization. The proposed requirement elicitation approach is highly suited for the organizations that operate in the modern business environment. This approach overcomes several limitations in the existing BI requirement approaches. A case study is presented to support the proposed requirement elicitation approach for OBI system.Conclusion: This approach has several advantages like fast development, clear definition, classification of various types of requirements and proper linkage between the requirements without any loss or missing of gathering requirements. Finally, it is to conclude that the proposed approach acts as a one-pot synthesis of requirements elicitation for Operational BI system.Keywords: Business Context, Business, Intelligence, Business Networks, Protocols, Modern Business, Environment, Operational Business, Intelligence Requirement, Elicitation, Requirement, Methodology

Process Discovery of Business Processes Using Temporal Causal Relation Yutika Amelia Effendi; Nania Nuzulita
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Nowadays, enterprise computing manages business processes which has grown up rapidly. This situation triggers the production of a massive event log. One type of event log is double timestamp event log. The double timestamp has a start time and complete time of each activity executed in the business process. It also has a close relationship with temporal causal relation. The temporal causal relation is a pattern of event log that occurs from each activity performed in the process.Objective: In this paper, seven types of temporal causal relation between activities were presented as an extended version of relations used in the double timestamp event log. Since the event log was not always executed sequentially, therefore using temporal causal relation, the event log was divided into several small groups to determine the relations of activities and to mine the business process.Methods: In these experiments, the temporal causal relation based on time interval which were presented in Gantt chart also determined whether each case could be classified as sequential or parallel relations. Then to obtain the business process, each temporal causal relation was combined into one business process based on the timestamp of activity in the event log.Results: The experimental results, which were implemented in two real-life event logs, showed that using temporal causal relation and double timestamp event log could discover business process models.Conclusion: Considering the findings, this study concludes that business process models and their sequential and parallel AND, OR, XOR relations can be discovered by using temporal causal relation and double timestamp event log.Keywords:Business Process, Process Discovery, Process Mining, Temporal Causal Relation, Double Timestamp Event Log

Untethering the Queue based on Multi Channel Access (MCA) Technology at Hospital Radiology Section Dharma Dyatmika; Oka Sudana; Gusti Agung A. Putri
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Information technology is developing rapidly over time, but there are many companies do not make use of it to support their operational activities. One example is the queue system in the Radiology Section of Sanglah Hospital, which operates the conventional queue system.Objective: The problem occurs in this queue system is inefficient waiting time because the patients must come early and wait in line in the hospital waiting rooms. Many patients thereafter decide going home first or doing other activities. Another problem is it triggers double costs of transportation. The purpose of this study is to improve patients comfort while waiting in queue by applying untethering the queue. Untethering the queue is a service that allows people to be in a queue even though they are not in the waiting room.Methods: The system applies the FCFS (First Come First Serve) algorithm to manage patients’ queue and integrates this queue system with Telegram and SMS gateway. It makes patients easier to take queue numbers and receive notification of health service time from the Radiology Section of Sanglah Hospital.Result: As a result of this study is an untethering the queue application which is web-based queue system integrated to Telegram and SMS gateway. The daily queue services in the Radiology Section of Hospital can be improved through this application.Conclusion: Patients can only come to the hospital when the queue numbers obtained nearly the health service time so that it leads to time efficient and comfort while waiting in queue.Keywords:First Come First Serve, Multi Channel Access, SMS, Telegram, Untethering the Queue

Hybrid Mobile Executive Information (m-EIS) System Using Quasar Framework for Indonesia Financial Service Authority Dina Fitria Murad; Wirianto Widjaya; Dwi Rahmania Noviani; Nur Fitriyyah; Liany Minarni Saputri
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Given the digital transformation in currently emerging digital era in Financial Service Industry; marked by the rise of Fintech; Financial Service Authority (FSA) is challenged to mitigate new type of risks that are introduced by it. As first step, Indonesia FSA seeks for an effective and efficient way to present up-to-date Strategic Information to its Top Executive Leaders to enable informed strategic decision making.Objective: This study aimed to find the solution to provide information strategic information to Indonesia FSA executives at any-time any-where. The researchers hypothesize that mobile Executive Information System could effectively serve the purpose.Methods: The research activities are laid out based on the Unified Process (UP) Methodology and use Unified Modelling Language (UML) diagrams to communicate the design. At the end of the study, a survey-based on TAM2 is conducted to confirm the study result. The survey is tested to measure its validity, reliability and correlation analysis using SPSS.Results: The study produce mobile executive information system (m-EIS) geared with the latest UI technology framework; Quasar; and microservice pattern. The m-EIS is deployed and implemented. The survey result shows the overall users’ acceptance of the implementation.Conclusion: The study recommends the further enhancement of m-EIS and highlights limitation of the current study for which future study could address and improve.Keywords:Executive Information System, Financial Service Authority, Financial Service Industry, Hybrid Mobile Application, Unified Modelling Language, Unified Process

Analysis of Emoticon and Sarcasm Effect on Sentiment Analysis of Indonesian Language on Twitter Debby Alita; Sigit Priyanta; Nur Rokhman
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Indonesia is an active Twitter user that is the largest ranked in the world. Tweets written by Twitter users vary, from tweets containing positive to negative responses. This agreement will be utilized by the parties concerned for evaluation.Objective: On public comments there are emoticons and sarcasm which have an influence on the process of sentiment analysis. Emoticons are considered to make it easier for someone to express their feelings but not a few are also other opinion researchers, namely by ignoring emoticons, the reason being that it can interfere with the sentiment analysis process, while sarcasm is considered to be produced from the results of the sarcasm sentiment analysis in it.Methods: The emoticon and no emoticon categories will be tested with the same testing data using classification method are Naïve Bayes Classifier and Support Vector Machine. Sarcasm data will be proposed using the Random Forest Classifier, Naïve Bayes Classifier and Support Vector Machine method.Results: The use of emoticon with sarcasm detection can increase the accuracy value in the sentiment analysis process using Naïve Bayes Classifier method.Conclusion: Based on the results, the amount of data greatly affects the value of accuracy. The use of emoticons is excellent in the sentiment analysis process. The detection of superior sarcasm only by using the Naïve Bayes Classifier method due to differences in the amount of sarcasm data and not sarcasm in the research process.Keywords: Emoticon, Naïve Bayes Classifier, Random Forest Classifier, Sarcasm, Support Vector Machine

Analyzing E-Commerce Success using DeLone and McLean Model Ruth Johana Angelina; Aji Hermawan; Arif Imam Suroso
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: The increasing usage and development of e-commerce in Indonesia, demands competition between e-commerce that exists. To be successful e-commerce should be balanced with a good information system. Some clinical research has established what factors that affected the success, including DeLone and McLean. According to their e-commerce success model, there are six variables that affect e-commerce success, system quality, information quality, service quality, use, user satisfaction, and net benefitObjective: The study aims to analyze the relationship between system quality, information quality and service quality to user satisfaction and use. In addition, the study aims to analyze the relationship between user satisfaction and use to a net benefit.Methods: This study draws on the DeLone and McLean Model of Information System (IS) success model. It is a quantitative study that was conducted in the form of a survey of 110 users of each Lazada, Bukalapak, and Shopee users.Results: By applying DeLone and McLean model, this findings confirmed four hypotheses were significant in Bukalapak, Lazada, and Shopee.Conclusion:There were significant effect between the system quality on user satisfaction, service quality on use, service quality on user satisfaction and user satisfaction on net benefits. Meanwhile, system quality had insignificant effect to use and also information quality to use in Bukalapak, Lazada, and Shopee.Keywords: DeLone and McLean model,E-Commerce Success, Information System Success Measurement, IS Success Model

Clustering of Drug Sampling Data to Determine Drug Distribution Patterns with K-Means Method : Study on Central Kalimantan Province, Indonesia Wahyuri Wahyuri; Umi Athiyah; Ira Puspitasari; Yunita Nita
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Background: Drug sampling and testing in the context of post-marketing control is an important component to ensure drug safety in the supply chains. The results are used by the Indonesian National Agency for Drug and Food Control (NA-FDC) for conducting public warnings, evaluating the Good Manufacturing Practice (GMP) and Good Distribution Practice (GDP) implementation, and enforcing the law against drug violation.Objective: This study aimed to identify and analyze drug distribution patterns to provide an overview of drug sampling in the public sector. Methods: The data was collected from Balai Besar Pengawas Obat dan Makanan (BBPOM) Palangka Raya’s database. The collected data were the drug sampling data from Integrated Information Reporting Systems (IIRS) application from 2014 to 2018. Next, we employed CRISP-DM methodology to analyze the data and to identify the pattern. K-means clustering model was selected for data modeling.Results: The dataset contained five attributes, i.e., drug name, therapeutic classes, district/city, sample category, and evaluation of drug surveillance. The drug distribution pattern formed three clusters. First cluster contained 522 drug items in eight therapeutic classes and spread over ten districts, second cluster contained 1542 drug items in five therapeutic classes and spread over five districts, and third cluster contained 503 drug items in eleven therapeutic classes and spread across nine districts.Conclusion: To conclude, the applied data mining technique has improved the decision on the drug sampling planning. It also provides in-depth information on the improvement of drug post-marketing control performance in Central Kalimantan Province.Keywords: Clustering, CRISP-DM, Data Mining, Drug distribution patterns, Drug quality control, Drug sampling

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