IJCT - Volume 5, Issue 5 / September- October 2018

S.No	Title/Author Name	Serial No
1	Text Classification on Dataset of Marine and Fisheries Sciences Domain using Random Forest Classifier - Desi Ramayanti, Umniy Salamah 10.29126/23942231/IJCT-V5I5P1 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract The number of text documents contained opinions and suggestions are increasing and challenging to interpret one by one. Whereas if the text documents are processed and properly interpreted, this text document can provide a general overview of a particular case, organization, or object. This research focused on text classification on marine and fisheries domain by analyzing the Twitter data related to Ministry of Marine Affairs and Fisheries, Republic of Indonesia. By using random forest algorithm, this research will classify text documents whether classified as complaint or non-complaint based on existing data in social media in order to support follow up to the complaint. Related work of random forest algorithm included Bosch, Zisserman, and Muoz (2007); Schroff, Criminisi, and Zisserman (2008); Kuznetsova, Leal-Taix�, and Rosenhahn (2013); Shotton et al., (2013); Joshi, Monnier, Betke, and Sclaroff (2017) has been used as references to completed this research. The phase of this research including data acquisition, data pre-processing, feature selection, classification and classifier evaluation. As the result, we foundbest performance is achieved when we use parameters with values, i.e. 'bootstrap': False, 'min_samples_leaf': 1, 'n_estimators': 10, 'min_samples_split': 3, 'criterion': 'entropy', 'max_features': 3, 'max_depth': None. The best score is achieved in this experiment is 0.956063268893 using those parameter values with computational time required to tune parameters is 109.399434 second. Keyword: text classification, social media, marine and fisheries sciences, e-government, text classifier, random forest algorithm. Desi Ramayanti, Umniy Salamah " Text Classification on Dataset of Marine and Fisheries Sciences Domain using Random Forest Classifier " Vol. 5 - Issue 5 (01 - 07) - September - October 2018 , International Journal of Computer Techniques (IJCT) , ISSN: 2394 - 2231 , www.ijctjournal.org ×	IJCT-V5I5P1
2	Naive Bayes Optimization Based On Particle Swarm Optimization to Predict the Decision of Insurance Customer Candidate - Saruni Dwiasnati, Yudo Devianto 10.29126/23942231/IJCT-V5I5P2 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract In order to deal with business competition and increase the company's revenue, both company leaders and management in a company are required to be able to make the right decisions in determining the sales strategy. To be able to do this, companies need a large amount of information to be analyzed further. The company executive expects technology that can produce information that is ready to be used to assist them in making corporate strategic decisions. They want to know what products should be improved, how much the results obtained by the company will be achieved. To meet the needs of entrepreneurs above, there are many ways that can be pursued. One of them is by utilizing corporate data. Based on the identification of the problems that have been described, the problem is formulated as follows: how the optimization results for the Naive Bayes algorithm based on Particle Swarm Optimization, how to build a prototype to predict customer data by using the appropriate data mining classification method. This study aims to recommend a prototype of the data mining classification method for potential customer predictive data in offering an existing product based on data mining classification method, namely the Na�ve Bayes algorithm based on Particle Swarm Optimization. This study, if viewed from the form of data and information that is managed, this research is classified as a quantitative type of research. Quantitative research is a research whose hypothesis can be tested by statistical techniques. This method is used when conducting quality testing using the k-fold cross validation method (k = 10) which displays the value of accuracy, precision, recall, ROC for each method that is compared. The results of application development and model performance measurement will be explained in this section. Application development will be discussed in testing to show that the results of the application are made as expected. Whereas in the measurement of model performance will be explained the results of the model performance measurement for the analysis of potential customers and potential customers not to be offered insurance products at PT. XYZ by using Naive Bayes based on Particle Swarm Optimization, the results obtained in the algorithm that has been optimized are made an application developed. Keyword: Insurance, Mining Data, Classification, Naive Bayes , Particle Swarm Optinmization. Saruni Dwiasnati, Yudo Devianto " Naive Bayes Optimization Based On Particle Swarm Optimization to Predict the Decision of Insurance Customer Candidate " Vol. 5 - Issue 5 (08 - 14) - September - October 2018 , International Journal of Computer Techniques (IJCT) , ISSN: 2394 - 2231 , www.ijctjournal.org ×	IJCT-V5I5P2
3	Analysis Comparison of The Classification Data Mining Method to Predictthe Decisions of Potential Customer Insurance - Reza Avrizal, Arief Wibowo, Angger Styo Yuniarti, Deassy Ari Sandy, Kamal Prihandani 10.29126/23942231/IJCT-V5I5P3 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Current insurance business increasingly developed due to the increasing public awareness to insure and provide protection against various aspects of his life. Insurance service companies whose customers come from bank customers are very concerned about the quality of service to customers. Constraints the companies are difficulties in determining potential customers. Buy or No if the company could identify levels-levels to determine the potential value of the customer so the customer data can be classified. As for some of the criteria that are considered important in determining the potential client that is based on area, age and job. For it to be developed an application of data mining to determine criteria for the customer. Data mining techniques applied is Classification while the method used is the classification Decision Tree (decision tree) and support vector machine (SVM). There are three parameters of the test were used as evaluation system i.e. accuracy, precision and recall. From the results of the comparisons, the decision tree has a higher percentage than the SVM i.e. 86.37% accuracy, precision and recall 86.25% 90.14%. ROC curve and decision tree classification of diagnosis rate is excellent whereas the SVM good classification. Keyword: Insurance, Data Mining, Decision Tree, C45, Support Vector Machine. Reza Avrizal, Arief Wibowo, Angger Styo Yuniarti, Deassy Ari Sandy, Kamal Prihandani " Analysis Comparison of The Classification Data Mining Method to Predictthe Decisions of Potential Customer Insurance " Vol. 5 - Issue 5 (15 - 20) - September - October 2018 , International Journal of Computer Techniques (IJCT) , ISSN: 2394 - 2231 , www.ijctjournal.org ×	IJCT-V5I5P3
4	Internet of Things in Smart Agriculture:Intelligent Irrigation Monitoring - Kalai Mani.A, Girija Magesh 10.29126/23942231/IJCT-V5I5P4 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Gardens make up the biggest inundated yield by surface zone in North America, and convey with it an interest for more than 9 billion gallons of freshwater every day. In spite of ongoing improvements in water system control and sprinkler innovation, cutting edge water system frameworks do nothing to make up for regions of turf with heterogeneous water needs. In this work, we overcome the physical constraints of the customary water system framework with the improvement of a sprinkler hub that can detect the neighbourhood soil dampness, impart remotely, and incite its own sprinkler in view of a midway processed calendar. A model is then created to process dampness development from overflow, assimilation, and dispersion. Incorporated with an improvement system, ideal valve booking can be found for every hub in the space. In a turf territory covering more than 10,000ft, two separate arrangements traversing a sum of 7 weeks demonstrate that MAGIC can diminish water utilization by 23.4% over customary grounds booking, and by 12.3% over condition of-the art evapo-transpiration frameworks, while significantly improving conditions for plant wellbeing. Notwithstanding ecological, social, and medical advantages, MAGIC is appeared to restore its speculation in16-year and a half in light of water utilization alone. Keyword: Soil dampness, Assimilation, customary grounds booking, evapo-transpiration, MAGIC. Kalai Mani.A, Girija Magesh "Internet of Things in Smart Agriculture:Intelligent Irrigation Monitoring" Vol. 5 - Issue 5 (21 - 27) - September - October 2018, International Journal of Computer Techniques (IJCT), ISSN: 2394 - 2231 , www.ijctjournal.org ×	IJCT-V5I5P4
5	Enhancing Clustering Mechanism by Implementation of EM Algorithm for Gaussian Mixture Model - Rajvinder Kaur, Maninder Kaur 10.29126/23942231/IJCT-V5I5P5 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract EM is frequently used for data clustering in machine learning&computer illusion. In normal language dispensation two well-known instances of algorithm are Baum-Welch algorithm&inside-outside algorithm for unsupervised induction of probabilistic free grammars. data mining technologies are open to all people with IoT technologies for decision making support & system optimization. Data mining involves discovery novel, interesting, & potentially useful model from data & applying algorithms to extraction of no hide information Due to increasing amount of data available online, World Wide Web had becoming one of most valuable resources for information retrievals & knowledge discoveries. Keyword: Data mining, web mining, web intelligence, knowledge discovery, fuzzy logic. Rajvinder Kaur, Maninder Kaur"Enhancing Clustering Mechanism by Implementation of EM Algorithm for Gaussian Mixture Model" Vol. 5 - Issue 5 (28 - 33) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P5
6	Employee Performance Appraisal System Using Adaptive Neuro Fuzzy Inference System (Anfis): A Case Study of Amik Pakarti Luhur - Reza Sulistyawan, Mohammad Syafrullah, HadidtyoWisnu Wardani, Novian Hendrianto 10.29126/23942231/IJCT-V5I5P6 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Employee performance indicates the result of work from employee in conducting the job based on competence, manner, and motivation. In evaluating employee performance, there are many factors, including loyalty, responsibility, discipline, integrity, team work, and leadership factors. Employee roles in advancing the organization is needed because without a good performance, the organization cannot achieve its objectives well. In AMIK PakartiLuhurTangerang, employee performance evaluationis done subjectively from the result of meeting, hence, the result of evaluation is not accurate. The samples is done by purposive sampling technique, which is the questionnaire is given to respondents. Employee Performance Evaluation Model is made with Adaptive Neuro Fuzzy Inference System (ANFIS) Sugeno method and Toolbox Matlab 8.2 R2013b.To ensure that the system meet the minimum standard quality, thus, the system use Software Quality Assurance (SQA) in evaluating software quality.The conclusion from employee performance evaluation model has a good level of accuracy. Keyword: Employee Performace, Adaptive Neuro Fuzzy Inference System (ANFIS) Sugeno Method, Matlab R2013b, SQA Method. Reza Sulistyawan, Mohammad Syafrullah, HadidtyoWisnu Wardani, Novian Hendrianto"Employee Performance Appraisal System Using Adaptive Neuro Fuzzy Inference System (Anfis): A Case Study of Amik Pakarti Luhur" Vol. 5 - Issue 5 (34 - 41) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P6
7	Impact of Online Travel Booking Application Quality towards Purchase Intention in Indonesia - Nur Ani, Handrie Noprisson 10.29126/23942231/IJCT-V5I5P7 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Many mobile vendors attempted to development mobile device with technology innovation. However, the increasing amount of mobile application developers caused the competition among them to attract new or current users become more amazing and difficult. The mobile application should have quality to attract customer to use mobile application in order to conduct transportation services transaction or purchase intention. In Indonesia, one of the most downloaded mobile applications is mobile commerce application for transportation services. This study adapted research work by Lit et al (2017) to identify component of application quality that influenced to purchase intention of online travel booking based on Indonesian people perspectives. As the result, complementary has the biggest influence purchase intention with t-value 6.771. Moreover, entertainment has influence to purchase intention with t-value 5.334. usability has influence to Purchase Intention with t-value 4.620. Ease of use has influence to purchase intention with t-value 3.641. Keyword: Online travel, application quality, PLS-SEM, factors analysis. Nur Ani, Handrie Noprisson"Impact of Online Travel Booking Application Quality towards Purchase Intention in Indonesia" Vol. 5 - Issue 5 (42 - 47) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P7
8	Determining Factors of Perceived Value, Trust and Innovativeness to Promote Purchase Intention - Nur Ani, Handrie Noprisson 10.29126/23942231/IJCT-V5I5P8 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Activities of electronic business in the online travel booking application are ultimately aimed to increase revenue as much as possible through an increase in the number of purchases. To obtain more revenue is influenced by many factors, both from the consumer perspective and from the business organization itself. This study is a preliminary study to develop a factor model that affects purchase intention in online travel booking application. The research model examined four main variables, i.e. innovativeness, trust, perceived value and purchase intention. This model is adapted from research model that is proposed by Escobar-Rodriguez (2017). We used bootstrap resampling procedure based on partial least squares (PLS) by processing 984 data.Based result of data analysis, trust has the biggest influence to purchase intentionwith t-value 8.280. Moreover, trust also support perceived value with t-value 29.619. Perceived value influences the purchase intention in online travel booking application with t-value 7.091. Keyword: online travel booking, electronic innovativeness, trust, perceived value. Nur Ani, Handrie Noprisson"Determining Factors of Perceived Value, Trust and Innovativeness to Promote Purchase Intention" Vol. 5 - Issue 5 (48 - 53) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P8
9	Design of System Agenda Module for Prospective Employee Selection - Nia Rahma Kurnianda 10.29126/23942231/IJCT-V5I5P9 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract PT Persada is a company engaged in labor outsourcing. Variables such as client, workforce, job, as well as the number of selection processes complicate problems received. There are several problems we found of the selection process agenda. So we try to design a system to manage the problems. The basic theories we used in this study are IS, UML, Human Resource and Selection, SMS Gateway and our previous study. The result of this study is presenting as a design of information system with integration of web based and SMS Gateway solutions. Keyword: Selection Agenda, UML, Web Based SMS Gateway System, HRIS Module, Information System Module. Nia Rahma Kurnianda"Design of System Agenda Module for Prospective Employee Selection" Vol. 5 - Issue 5 (54 - 59) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P9
10	Naive Bayes Method For Process For Selection Of PPA Scholarship to Students: Case Study Of Informatics and Computer Management Academy Of Pakarti Luhur Tangerang - Badrus Zaman Sapto Mardi Putro, Krisna Adiyarta M, Sri Wahyuningsih, Pepi Permatasari 10.29126/23942231/IJCT-V5I5P10 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract The selection process for PPA Scholarship students currently at Pakarti Luhur AMIK is not subjective, namely through meeting results so that the accuracy of the results is reduced. This decision is adjusted by several requirements criteria so that the selection of PPA scholarship recipients in accordance with the requirements contained in the Pakarti Luhur scholarship can be chosen, which is based on the Academic Achievement Scholarship (PPA) guidelines, circulated by the Ministry of Research, Technology and Higher Education. This study is in the form of a case study with research and development methods whose subject of research is the Information and Computer Management Academy of Pakarti Luhur. This model is designed for the selection process of students who have the opportunity to win PPA scholarships, with the Naive Bayes method used. The results of the model with the Naive Bayes Method in the process of selecting desktop-based PPA Scholarship winners display features of data class input menu, input data requirements, student input to be selected, data conversion process to training data, validation process, and data testing. The results of the model design can provide objective results and ease in helping to carry out the selection process. The test results also show that the use of the Naive Bayes method can be used as an alternative in making decisions in the selection of PPA Scholarship students who have an accuracy of 93.4783%. Keyword: - - -. Badrus Zaman Sapto Mardi Putro, Krisna Adiyarta M, Sri Wahyuningsih, Pepi Permatasari"Naive Bayes Method For Process For Selection Of PPA Scholarship to Students: Case Study Of Informatics and Computer Management Academy Of Pakarti Luhur Tangerang" Vol. 5 - Issue 5 (60 - 66) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P10
	Under in review process, article will publish soon......

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IJCT - Volume 5, Issue 5 / September- October 2018

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