International Journal of Engineering and Emerging Technology
International Journal of Engineering and Emerging Technology is the biannual official publication of the Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University. The journal is open to submission from scholars and experts in the wide areas of engineering, such as civil and construction, mechanical, architecture, electrical, electronic, and computer engineering, and information technology as well. The scope of these areas may encompass: (1) theory, methodology, practice, and applications; (2) analysis, design, development and evaluation; and (3) scientific and technical support to establishment of technical standards.
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<![CDATA[Data Mining for Clustering Revenue Plan Expense Area (APBD) by using K-Means Algorithm ]]>
<![CDATA[Wahyudin Wahyudin]]>;
<![CDATA[I Putu Ari Wijaya]]>;
<![CDATA[Ida Bagus Alit Swamardika]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[APBD is a systematic detailed list of receipts, expenditures and local spending within a certain period ( 1 year ) arranged in Permendagri No. 16 of 2006, so that the data APBD can be used as guidelines for governments and local expenditures in carrying out activities to raise revenue to maintain economic stability and to avoid inflation and deflation. Government financial institutions in areas such as DPKA kota Bima, experienced difficulties in identifying the relevance of each archive data on a APBD that so much, that results in a data warehouse, in addition to the administration, APBD in the government of Kota Bima have not been effective. To minimize the difficulty in identifying heap data archive APBD, then the data warehouse can be used to produce a knowledge that by using the techniques of Data Mining ( DM ), the method used is clustering and forecasting, clusterisasi performed using the K-Means Algorithm while for forecasting with multiple linear regression. With this method intended to classify and identify the data in the budget that have certain characteristics in common, and can predict the value of APBD in the future.]]>
<![CDATA[Analysis of Clustering for Grouping of Productive Industry by K-Medoid Method ]]>
<![CDATA[Indah Cahya Dewi]]>;
<![CDATA[Bara Yuda Gautama]]>;
<![CDATA[Putu Arya Mertasana]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[With the number of existing data, would have difficulty in doing the classification and the classification of the existing data. To resolve the issue, one way to do clustering is with data mining using clustering technique. The purpose of this research is the importance of knowing the pattern of the production of an industry that can provide the decision and the construction of clustering patterns for development and industrial progress. The results of this research can provide recommendations to improve the development of industry, help the owners of industry to develop the industry to an increase in the number of production and product quality, improve the competitiveness of the owner of the industry in developing its products. In this research will use the K-Medoids algorithm for data grouping of the industry so that it will be found the information that can be used for the recommendations of the improvement of marketing. The results of clustering with the number of cluster 3 produces the first group contains 85 members, the second group contains 222 members and the third group numbered 3 members. The third group are classified as productive because it has a combination of the value of the production of the most high the results of clustering have the quality of purity worth 1 means good cluster quality.]]>
<![CDATA[Application of Consumer Clustering Mining Data Mining in Household with Fuzzy Multi Criteria Decision Making (FMCDM) ]]>
<![CDATA[Muhammad Anshari]]>;
<![CDATA[I Putu Suryadharma]]>;
<![CDATA[Nyoman Putra Sastra]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[This study aims to classify consumers in the selection of houses using Fuzzy Multi Criteria Decision Making (FMCDM) method based on data mining. Alternative houses provided there are four of the minimalist houses, contemporary modern homes, classical houses, and traditional ethnic houses. To generate these choices, there are five criteria: price criteria, home/type criteria, interior criteria, exterior criteria, and home environmental criteria. The results of this study can help system users in determining the choice of home type based on the user's tastes of the criteria available and also can help the investors and contractors in building houses, villas, hotels, and housing of the criteria.]]>
<![CDATA[Mapping Patterns Achievement Based on CRISP-DM and Self Organizing Maps (SOM) Methods ]]>
<![CDATA[Santi Ika Murpratiwi]]>;
<![CDATA[A.A Ngurah Narendra]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[Successful of regional development is a reflection of the good government policy. Many programs created by the local government every period but many programs stop without results. Therefore, we need to evaluation its government programs. Evaluation of government programs must do to prevent the failure of the programs. One way to evaluate the government programs is to collect the support data to see the data model and analyzed the data. In this research will conduct an evaluation on the achievement of RPJMD performance of Bali Province by using data mining. The process of data mining used the CRISP-DM method and Self Organizing Maps (SOM) for mapping the achievement patterns. The used data is RPJMD data in the 2013-2018 period. but the data used for data mining process only 3 years data that is 2014-2016 as a middle evaluation. That data clustered into five clusters. The final result of this research are 78% of assessment indicators in the RPJMD program are inconsistent position and 22% are in an inconsistent position. Moreover, there are 84 assessment indicators that have no reached the target. From that results of data, assessment mapping can use as the guidance of Bali Province to catch up the achievement of RPJMD programs and prepare the next strategies to support the success of the RPJMD program during the RPJMD period.]]>
<![CDATA[Designing Data Warehouse in Finance Company Study at PT ABC ]]>
<![CDATA[Putu Suta Adya Dharma Rahadi]]>;
<![CDATA[Putu Widiadnyana]]>;
<![CDATA[Nengah Sweden]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[Along with the development of technology and business needs that are more advanced, the more effective and efficient uses of Information Systems is an important thing for companies to continue competing in the era of globalization. Every company wants an appropriate Information System to run business activities smoothly. Using data warehouses can help PT ABC's problems in accommodating large amounts of data with its OLTP system which can then be processed in determining future strategies through OLAP systems. So as to get the reports needed in maintaining the consistency and improve the performance of the company.]]>
<![CDATA[Application of Neural Network Overview In Data Mining ]]>
<![CDATA[Rifky Lana Rahardian]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[Data Mining is the term used to describe the process extract value / information from the database. Four things are needed in order to effectively data mining: data that has a high quality, right of data, examples of which are adequate, and the correct device. To obtain valuable information in the required data mining algorithms applied in data mining in large databases. There are a lot of complex algorithms in data mining. One is the so-called Neural networks have an important role in data mining.]]>
<![CDATA[Prediction of DOTA 2 Match Result by Using Analytical Hierarchy Process Method ]]>
<![CDATA[Gede Adi Aryanata]]>;
<![CDATA[Putu Suta Adya Dharma Rahadi]]>;
<![CDATA[Yanu Prapto Sudarmojo]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[This research discuss about how to predict a match result by using data mining as the foundation to make a conclusion. In this research, Analytical Hierarchy Process (AHP) is used as a main data mining method for making a prediction. AHP works by using pre-existing data events as training data to obtain predictions of future data results. This research uses four parameters to predict the result of international Dota 2 match. Those parameters are experience per minutes (XPM) and gold per minutes (GPM), matchmaking ratio (MMR) point, 3 head to head matches result, and the last 10 results matches. In its implementation, the four parameters are given different rules and priority levels to support the performance of the AHP method. The result of this study has a satisfactory level of accuracy regarding the victory estimation of the match.]]>
<![CDATA[Design and Balancing Load Current in 3-Phase System Using Microcontroller ATMEGA 2560 ]]>
<![CDATA[Cok Gede Indra Partha]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[The design of balancing the load current on three-phase systems using a microcontroller ATMega 2560 is a tool that serves to reduce the power loss. Power loss due to the load current unbalance the current flows in the neutral phase on three-phase systems. Current flows in the neutral phase distribution transformer into a detriment to PT. PLN (Persero) for the power lost to the earth and can not be used by consumers. So that it will balanced the load current to reduce the value of neutral current. The tool is also equipped with a monitoring system that displays current magnitude of each phase including the neutral phase.The methods in making this tool is divided into two parts: first, the design of hardware consist of designing electronic components which are used by the current sensor circuits, relay, LCD (Liquid Crystal Display) etc. Second, the design of software is a tool listing program procedure including the monitoring program displays the current of each phase on LCD using the Arduino IDE. SCT013-030 current sensor used, the output of the current sensor is connected to the pin ADC (Analog to Digital Converter) microcontroller ATMega 2560. Then microcontroller process the data and generate a current value displayed on the LCD. The other result of processing current value is a command to enable or disable the relay that connects three-phase resource with single-phase loads.The result of the test design of balancing load current on three-phase system using a microcontroller ATMega 2560 succeed balancing the load current by moving the channel load of sequence number load the smallest connected to the phase with the current biggest load toward a phase that has a load current smallest when neutral current exceeds the limit is permitted. In this situation, the neutral current will not be possible be zero. In fact, the maximum current value for the neutral phase for PT. PLN (Persero) 50 amperes calibrated to 1 ampere and is used as a limit on this prototype. If the neutral current on LCD monitor exceeds 1 ampere, then there will be balancing of the load current. The current sensor measurement results are displayed on a monitoring approach measurement result using pliers ampere.]]>
<![CDATA[Implementation of Data Mining To Predict Period of Students Study Using Naive Bayes Algorithm ]]>
<![CDATA[Ida Bagus Adisimakrisna Peling]]>;
<![CDATA[I Nyoman Arnawan]]>;
<![CDATA[I Putu Arich Arthawan]]>;
<![CDATA[I Gusti Ngurah Janardana]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[The quality of universities, especially study programs in Indonesia is measured based on accreditation conducted by BAN PT. According to BAN PT the quality is measured based on 7 main standards, one of them is Student and Graduate. One of the problems that still be the subject of discussion related to student failure is about the students who graduated not on time. Students graduating not on time are students who can not complete their studies in accordance with the provisions of time given. The existence of a graduate student is not timely of course cause problems and potentially drop out that affect the quality of education and accreditation. A system that predicts students' graduation is required by evaluating their learning outcomes. The timeliness of graduating students can be done with data mining techniques to find graduation patterns of students who have graduated which then used as a basis to predict students' graduation in the next year. This study showed that Naïve Bayes was able to classify the correct data testing on average by 86.16% and 13.84% error. In addition, other information obtained from the data testing used that the students who entered from the PMDK Pass graduated on time as much as 40%, other paths graduated on time by 26.7%, and pass filter exam on time 13.3%.]]>
<![CDATA[Analysis of Shopping Cart At Drugs Store By Using An Apriori Algorithm ]]>
<![CDATA[Adi Panca Saputra Iskandar]]>;
<![CDATA[Kheri Arionadi Shobirin]]>;
<![CDATA[Komang Oka Saputra]]>
<![CDATA[ International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June ]]>
Publisher : <![CDATA[Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University ]]>
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<![CDATA[Competition in the business world in the pharmacy industry, demands the Pharmacist to determine a strategy that can increase drug sales. One way is to overcome the problems that occur in drugs store such as problems and sales of drug recommendations to suppliers who still use the prediction system of pharmacists. Data growth is less so utilized, data and information become useless like waste, sales strategy only as a little assumption without information and knowledge in server, consequently sales down and not range and items become expired and stock procurement is not according to market demand. Extracting data or an effort to retrieve valuable knowladge and information in a large database is called data mining or Knowledge Discovery in Database or usually shortened as KDD . One of the most popular algorithm in data mining technic is Apriori Algorithm, while the discovery of “relational combination pattertn among itemset used Assosiation Rules”. Data mining has been implemented into the various fields like : business or trade, education and telecommunication. In bussiness for instance, the implementation result of data mining use ‘algorithm Apriori which can give a hand to help the Businessmen make decision on supplies. For example, the necessity of supplies system in a drugstore as one of the mecical stuff supplier, and to determine which product as the priority should be supplied to anticipate out of stock of supplies availability in the store, as the results will also affect to the consumer service and daily income. Drugs are essential unit should be supplied and being and essential factor which will impact to the consumer trust to a hospital or another medical service. That is why the availability of medical drugs in drugstores is completely needed to support the succes of distribution to the consumers, so the activity of medical service to consumers run thoroughly. In this case, data mining is seen as able to buildt intelligent business environment as solution for competing increated compitition among the drugstores in future.]]>
