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
11	Tuning of a 2DOF PI-PID Controller for use with Second-order-like Processes - Galal Ali Hassaan 10.29126/23942231/IJCT-V5I5P11 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract This paper presents a tuning approach for a 2DOF PI-PID controller to be used with second-order-like processes. The MATLAB computer program is used through its optimization toolbox to tune the controller subjected to four functional constraints. The functional constraints are selected to produce good performance of the control system regarding the transient and steady state characteristics. The tuning technique used is compared with another technique and the effectiveness of the controller was investigated through comparison with using other two controllers. Keyword: 2DOF PI-PID controller, controller tuning, control system performance. Galal Ali Hassaan"Tuning of a 2DOF PI-PID Controller for use with Second-order-like Processess" Vol. 5 - Issue 5 (67 - 73) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P11
12	Implementation of Logistic Regression Algorithm for Complaint Text Classification in Indonesian Ministry of Marine and Fisheries - UmniySalamah , DesiRamayanti 10.29126/23942231/IJCT-V5I5P12 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Social media is usually used to express emotion in opinion or complaint statement regarding an object. In organization, this statement contained opinion and complaint to a service or program by it organization. This feedback can be used by organization to improve and enhance their quality. This research attempted to classify the reports from LAPOR! based on complaint and non-complaint using machine learning algorithm named Logistic regression (LR). This research completed through five research phases. The first phase is data collection, which is followed by crawling and labelling dataset, procession data, modelling dataset using Logistic Regression (LR), and evaluating classifier performance. As the result, the Logistic Regression model using Count Vectorizer feature extraction achieved better performance than Tfidf Vectorizer. Keyword: Indonesian text,marine and fisheries sciences, logistic regression, text classification. UmniySalamah , DesiRamayanti"Implementation of Logistic Regression Algorithm for Complaint Text Classification in Indonesian Ministry of Marine and Fisheries" Vol. 5 - Issue 5 (74 - 78) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P12
13	Supervised Classification of Indonesian Text Document Using Extreme Gradient Boosting (XGBoost) - UmniySalamah , DesiRamayanti 10.29126/23942231/IJCT-V5I5P13 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract One of the machine learning algorithms that recently gained benchmarks in state of the art various problems in machine learning is eXtreme Gradient Boosting (XGBoost). This algorithm has been solved many in various data mining and machine learning challenge, and has been applied in various problems by giving good results. This research will classify text data using XGBoost to predict a text whether classified as complain or non-complaint based on existing data in social media.In this experiment, we installed XGBoost package on our system for used in Python. XGBClassifier is imported to our codes to support in using sklearn's Grid Search for tuning parameters with parallel processing. The XGBoost algorithm uses multiple parameters so that it can be improved by tuning the parameters, i.e. eta or learning rate, gamma, max_depth, min_child_weight, subsample, colsample_bytree and alpha. As the result, the best value for each parameter are 'reg_alpha': 0.01, 'colsample_bytree': 0.9, 'learning_rate': 0.5, 'min_child_weight': 1, 'subsample': 0.8, 'max_depth': 3, 'gamma': 0.0. Moreover, the computational time that required to tune those parameters is 13870.012468 and the best accuracy that achieved is 0.927943760984. Keyword: Indonesian text, text classification, marine and fisheries sciences, XGBoost. UmniySalamah , DesiRamayanti"Supervised Classification of Indonesian Text Document Using Extreme Gradient Boosting (XGBoost)" Vol. 5 - Issue 5 (79 - 84) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P13
14	A Survey On Complementary Aspect Based Opinion Targets With Opinion Words Co-Extraction In Opinion Mining - Mr. Umesh Nanavare , Prof.Darshana Patil 10.29126/23942231/IJCT-V5I5P14 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Textual information is mainly classified into two main types: facts and opinions. The entities, events and their properties are objective expression of facts. Facts are something which already happened or actually the case itself. They are (e.g., iPhone is an Apple product).Opinions are subjective expressions which describe peoples? judgment, viewpoint, feelings towards entities, events and their properties. (e.g., I like this Apple iPhone 6). Opinion Mining is the computational study of people�s opinions towards entities and their aspects. Entities basically refer to individuals, events, topics, products and organizations. Aspects are attributes or components of entities. In the last few years, social media is the main source to express and share people�s opinion on entities and their aspects. Because of the availability of vast opinionated web contents in the form of comments, reviews, blogs, tweets, status updates, etc. It is difficult for people to analyse all opinions at a time to make good decisions. There is a need for effective automated systems to evaluate opinions and generate accurate results. Mining opinion targets and opinion words from online reviews is important tasks for fine-grained opinion mining, the key component of which involves detecting opinion relations among words. To this end, this work proposes a Complementary Aspect based Opinion Targets with Opinion Words Co-Extraction Algorithm. Experimental Result shows the proposed algorithm extracts opinion targets and opinion words more precisely. Keyword: Aspect-based Opinion Mining, Maximum Entropy Model, Word Embedding. Mr. Umesh Nanavare , Prof.Darshana Patil"A Survey On Complementary Aspect Based Opinion Targets With Opinion Words Co-Extraction In Opinion Mining" Vol. 5 - Issue 5 (85 - 90) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P14
15	Signature Recognition with Zernike Moment Method Using Support Vector Machine - Mr. Ilham Aristanto, Achmad Solichin 10.29126/23942231/IJCT-V5I5P15 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract The signature is one of biometrics owned humans that are written in a special way and have a different signature pattern between each other. The signature is typically used as the main mechanisms in States that the parties signed, knowing, approve and is responsible for the entire content of the document. However, the forgery of signatures still often occurs and is detected it will be difficult if done by the party that is already trained. Thus, required the existence of an application that can help identify a person's signature to minimize the practice of pe malsuan signature. This research proposed a system to identify the signature extraction characteristics of Zernike Moment, in order to match the right consistency and the degree of accuracy of the signature using the method of Support Vector Machine. Size, shape, pressure, and position of the signature being the main factors influencing the process of identification. Before the extraction process characteristic of Zernike Moment done cropping process against the next image done praproses grayscale and binarisasi. The next stage of the process of classification in order to recognize authenticity while counting accuracy against the method of Support Vector Machine. From the research that has been done to the 23 employees produce value accuracy of 88%. Keyword: Signature, Digital Image, Pattern Recognition, Support Vector Machine, Zernike Moment. Ilham Aristanto, Achmad Solichin"Signature Recognition with Zernike Moment Method Using Support Vector Machine" Vol. 5 - Issue 5 (91-97) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P15
16	A Survey on EDLC: Enhanced Data Leakage Controller for Secure Multi-Cloud Storage - Prof.Satav S. D., Mr. Arvind Dalvi 10.29126/23942231/IJCT-V5I5P16 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Multi-Cloud Storage implies the use of different distributed storage administrations utilizing a solitary web interface instead of the defaults given by the distributed storage merchants in a solitary heterogeneous design. This Multi-Cloud stockpiling model enable clients to store cut scrambled information in different cloud drives. In this way, it offers help for different distributed storage administrations utilizing the single interface instead of utilizing single distributed storage administrations. Cloud security objective essentially centers on issues that identify with data protection and security parts of distributed computing. Also, the information in users� data can be leaked e.g., by means of malicious insiders, backdoors, bribe and coercion. This most recent information stockpiling administration and information control model spotlight on malevolent insider's entrance on put away information, assurance from pernicious documents, expulsion of brought together circulation of information stockpiling and evacuation of obsolete records or downloaded records every now and again. Information proprietor does not really need to stress over the fate of the information put away in the Multi-Cloud server might be extricated or corrupted. The other is entrance control of information. The proposed technique guarantees the document or information can't get access without the learning or authorization of the proprietor. Thus, this synopsis aims at offering an Enhanced Data Leakage Controller (EDLC) which reduces malicious insiders and data leakages with an algorithm that improves data sharing security in Multi-Cloud storage services. This technique will offer a secure environment whereby the data owner can store and retrieve data from Multi-Cloud Environment without file merging conflicts and prevents insider attacks to obtain meaningful information. The exploratory outcomes demonstrate that the recommended show is appropriate for basic leadership process for the information proprietors in the better selection of multi-distributed storage benefit for sharing their data safely. Keyword: Multi-Cloud storage, Enhanced Data Leakage Controller. Prof.Satav S. D., Mr. Arvind Dalvi"A Survey on EDLC: Enhanced Data Leakage Controller for Secure Multi-Cloud Storage" Vol. 5 - Issue 5 (98-103) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P16
17	Decision Support System for Determining the Best Participants of Changes in Leadership Training Using AHP and Topsis Methods : Case Study of Human Resource Development Agency Province Of Banten - Zubeida meilany, Moedjiono, Nana sofiana, Rhoiansyah 10.29126/23942231/IJCT-V5I5P17 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Leadership training is education and training designed for government officials to shape and develop them into leaders of change. Competence as a leader of change will be formed through direct practice in the field. This form of direct practice in leadership training is to implement a change project in his office. The implementation of the change project began with drafting a change project followed by the implementation of the change project, and compiling the project change report. The determination of the best participants in the Leadership Training Change Project of the Banten Province Regional Human Resources Development Agency was carried out based on the specified criteria. The criteria used are Innovation Design, Change Achievement, Support Statement, and Activity mobilizing Support. The problem faced by these agencies is how to determine the best participants from a number of alternative participants. This system is a Decision Support System built using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity To Ideal Solution (TOPSIS). The criteria weighting is done using AHP and the ranking is done using TOPSIS. The results of testing the acceptance of the system with 4 (four) aspects of testing, obtained the result of Ease Perception of 91.43%, Usability Perception of 86.86%, Attitude to Use 87.90%, and System Usage Value of 81.90%. So overall the average value of the TAM method is 86.66% and overall the quality of the system works well. Keyword: Decision Support System, Change Project, AHP, TOPSIS, Banten Province Regional Human Resource Development Agency. Zubeida meilany, Moedjiono, Nana sofiana, Rhoiansyah"Decision Support System for Determining the Best Participants of Changes in Leadership Training Using AHP and Topsis Methods : Case Study of Human Resource Development Agency Province Of Banten" Vol. 5 - Issue 5 (104-111) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P17
18	Decision Support System Determining Location of General Electricity Provider Station Using ANP and TopsisMethod in PT PLN Persero Jakarta Raya - Onggo Imam Subekti, Arisona Benyamin Belipati, Mochammad Darip 10.29126/23942231/IJCT-V5I5P18 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract In selecting the location of a new general electricity supply station there are several criteria that can influence decision making, the choice of the right location can provide benefits in terms of meeting domestic energy needs and in terms of economy. To get an objective and transparent decision, a system is needed to help decision-makers determine the location of the SPLU, which criteria and alternative locations are suitable for the needs of the company. The system method developed to determine the best location established the SPLU from the many locations offered using the ANP and Topsis methods, which is one method of resolving decision-making problems based on the concept that the chosen alternative is the best. And it will be seen the influence of one criterion with other criteria, the criteria used are strategic location, population density, land status, easy to reach, distance between public electricity supply stations, parking lots, waiting rooms and surrounding security, which is divided into three criteria clusters. The results of this study indicate the best location is DuriKosambi with a value of 0.7334 and for the quality of this system to get a good response from the commercial division. Keyword: Criteria, alternative, TOPSIS, ANP, electricity, location, strategic. Zubeida meilany, Moedjiono, Nana sofiana, Rhoiansyah"Decision Support System Determining Location of General Electricity Provider Station Using ANP and TopsisMethod in PT PLN Persero Jakarta Raya" Vol. 5 - Issue 5 (112-122) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P18
19	A Survey on CSOAL: Cost-Sensitive Online Active Learning with Its Application to Malicious URL Detection - Divyashree Kelji, Dr. P. D. Lambhate 10.29126/23942231/IJCT-V5I5P19 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Malicious Uniform Resource Locator (URL) identification is a vital issue in web pursuit and mining, which assumes a basic job in web security. In writing, many existing examinations have endeavoured to figure the issue as a consistent administered twofold grouping undertaking, which ordinarily plans to streamline the forecast precision. Be that as it may, in a genuine malevolent URL discovery undertaking, the proportion between the quantity of malignant URLs and authentic URLs is exceptionally imbalanced, making it extremely unseemly for essentially enhancing the expectation exactness. Additionally, another key restriction of the current work is to expect a lot of preparing information is accessible, or, in other words the human marking cost could be conceivably very costly. To illuminate these issues, in this paper, so present a novel system of Cost-Sensitive Online Active Learning (CSOAL), which just inquiries a little portion of preparing information for marking and specifically streamlines two cost-delicate measures to address the class-irregularity issue. Specifically, so propose two CSOAL calculations and dissect their hypothetical execution as far as cost-delicate limits. It direct a broad arrangement of tests to look at the experimental execution of the proposed calculations for a substantial scale testing malevolent URL discovery assignment, in which the empowering results demonstrated that the proposed strategy by questioning a to a great degree little measured named information (around 0.5% out of 1-million examples) can accomplish better or exceptionally equivalent grouping execution in contrast with the best in class cost-uncaring and cost-touchy online characterization calculations utilizing an immense measure of named information. Keyword: Uniform Resource Locator, Online Active Learning, Malicious URL. Divyashree Kelji, Dr. P. D. Lambhate"A Survey on CSOAL: Cost-Sensitive Online Active Learning with Its Application to Malicious URL Detection" Vol. 5 - Issue 5 (123-130) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P19
20	A Survey on Packet Scheduling Schema for Smart Cities Using Iot - Vikas Mehta, Dr. P.D. Lambhate 10.29126/23942231/IJCT-V5I5P20 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract The Internet of Things (IoT) for smart cities is a large integrated system that consists of sensor networks, wireless mesh networks, mobile communications, social networks, smart transportation and intelligent transportation. With the utilizations of Internet of Things for shrewd urban communities, the continuous execution for countless parcels is confronting genuine test. The previous algorithms don�t consider the impact between different nodes, so there will be some extra time when the emergency data packets are sent to the sink node. The classical QoS approach, such as Differentiated Services (diffserv), adopts this idea. It assigns priorities according to the type of the sensor and characteristics of the data in networks. Base paper proposes EARS, an efficient data-emergency-aware packet scheduling scheme for smart cities. EARS describe the packet emergency information with the packet priority and deadline. Also for the enhancement scheme we can apply the security algorithm for sharing the data, so that data get more secure. In this paper we also scheduling packets schema for smart cities using Internet of Things. Keyword: Internet of Things, Quality of Service, Packet Scheduling, Differentiated Services. Vikas Mehta, Dr. P.D. Lambhate"A Survey On Packet Scheduling Schema For Smart Cities Using Iot" Vol. 5 - Issue 5 (131-138) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P20
21	A Survey On BPA: Bigdata Parallelism Algorithm For Distributed Machine Learning - Prajakta Ugile , Dr.S.B.Chaudhari 10.29126/23942231/IJCT-V5I5P21 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract A variety of machine learning (ML) algorithms are used to explore and exploit big data originating from diverse sources such as activities on the internet, profiling and transactions in finance, advertisement and healthcare, or experiments in the physical sciences, to name a few. It is important to outline a sensible methodology that gives dynamic correspondence streamlining to enhance the usage of the bunch, quicken the preparation times and reinforce the precision of the preparation display. Due to the increase in data volume and the complexity of the ML model, especially the increase in the number of parameters, single machines have been unable to fully and quickly train the ML model. Using distributed systems that partition the big data across machines and allow each machine to read and update all ML model parameters. Keyword: Machine Learning, Big data Parallelism Algorithm. Prajakta Ugile , Dr.S.B.Chaudhari"A Survey On BPA: Bigdata Parallelism Algorithm For Distributed Machine Learning" Vol. 5 - Issue 5 (139-145) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P21
22	Optimization of Algorithm C4.5, Naive Bayes With Particle Swarm Optimization in Predicting Career Suitability of Vocational High School Students: Case Study of SMKN 1 Rangkasbitung - Rini Marlina, Adrianto, Wahyu Amaldi, M.Johan Budiman 10.29126/23942231/IJCT-V5I5P22 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract SMK Bisa�(=Vocational High School Can) be one of the tagline issued by the Ministry of Education and Culture in order to face the free market of ASEAN Economic Community(=MEA), so that the graduates of Vocational schools are ready to compete in the work field. Career is one aspect that cannot be separated from vocational school graduates, because one of the main goals of vocational school graduates is that they are absorbed in the work field or working. Some of the graduates who work are suitable with the majors in Vocational Schools but many of them are working not suitable with their majors. This study discusses the prediction of the suitability of Vocational students' careers. The method used in predicting career suitability uses C4.5 and Naive Bayes methods which are optimized using PSO. The results of the two methods used are increasing accuracy in both methods so that optimization produces algorithms that are superior between the two methods. From the superior algorithms that are used to predict the suitability of Vocational students' careers. After conducting the research, the accuracy of the C4.5 method is 89.14%, Naive bayes 86.86%. Furthermore, these two methods are optimized using PSO and the accuracy results is increasing. The result optimized accuracy of C4.5 becomes 93.80% while Naive Bayes is optimized to be 89.80%. Thus there is an increase in accuracy in both methods. Keyword: Career Suitability, Algorithm C4.5, Naive Bayes, PSO. Rini Marlina, Adrianto, Wahyu Amaldi, M.Johan Budiman"Optimization of Algorithm C4.5, Naive Bayes With Particle Swarm Optimization in Predicting Career Suitability of Vocational High School Students: Case Study of SMKN 1 Rangkasbitung" Vol. 5 - Issue 5 (146-153) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P22
23	Recommendations of the Best Lecturers Selection Method Using Simple Additive Weighting (SAW) and the Analytical Hierarchy Process (AHP) - Andi Moch Januriana, Didik Wiguna, Sonny Nugroho Aji 10.29126/23942231/IJCT-V5I5P23 [ Abstract ] [ Cite ] [ PDF ] Tweet Abstract Colleges in this case was a working parent lecturers, very interested parties maintain the quality of the professors in the teaching and learning process. The selection process of the best lecturers have been regulated by the KEMENTRISTEK of HIGHER EDUCATION including lecturer required to have the Superior achievements of Work i.e. covers, learning, research and community service. At this time in maintaining the quality of professors, Faculty of social and political sciences of the University of Sultan AgengTirtayasa recently did an assessment of teaching and learning (Learning) with assessment of students toward professors about four (4) competencies assessed, namely Pedagogic Competence (1), (2) Professional Competence, (3) the competence of personality, (4) Social Competence. The assessment process takes a long time and where judgment objectiveness is still not following the standard KEMENTRISTEK of HIGHER EDUCATION, then the need to resolve the matter with the designed a system of information presented by building a support system decision method using Simple Additive Weighting (SAW) as a method to process data learning and Analytical Hierarchy Process (AHP) as a method that can process data research and outreach because of the penilaianya based on the the criteria, after doing its automatic data, then the value of the method of AHP SAW and would do the merging value so that the system will provide recommendations to the ranking of the best lecturers FROM Untirta with the method of calculation based on SAW and AHP. Keyword: SAW, AHP, decision support system, the determination of the best Professors, SAW-AHP. Andi Moch Januriana, Didik Wiguna, Sonny Nugroho Aji"Recommendations of the Best Lecturers Selection Method Using Simple Additive Weighting (SAW) and the Analytical Hierarchy Process (AHP)" Vol. 5 - Issue 5 (154-161) - September - October 2018, International Journal of Computer Techniques (IJCT) ,ISSN: 2394 - 2231, www.ijctjournal.org ×	IJCT-V5I5P23
24	Vertically Distributed Feature Selection for Distributed Data Mining. - Hitesh Ninama : Click Here	IJCT-V5I5P24
	Under in review process, article will publish soon......

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

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