INFOKUM
The INFOKUM a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Software Engineering. Image Processing Datamining Artificial Neural Networks
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<![CDATA[Decision Support System For Selection Of Electric Light Ball For Household With Technique Method For Order Preference By Simillarity To Ideal Solution (Topsis) ]]>
<![CDATA[Pandi Barita Nauli Simangunsong]]>;
<![CDATA[Paska Marto Hasugian]]>;
<![CDATA[Makmur Tarigan]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[In the selection of these light bulbs, users are often confused with the choice of light bulbs that are so widely circulated in the market, ranging from brands, types, quality, prices that continue to compete and with other advantages on offer often make users confused to get Energy efficient light bulbs at affordable prices and with the best quality. The problem doesn't just stop there when placing light bulbs in each room of the house also often gets into trouble. The problem that is often caused is mismatch, this usually happens when the light bulb has been placed. The wattage capacity of the light bulb often does not match the size of the room, resulting in less than optimal lighting. Watt capacity or large power consumption sometimes also does not guarantee to be able to get good lighting. Therefore we need a decision support system that can calculate values to be able to help users determine the desired light bulb properly and precisely according to needs. This decision support system implements the technique for order preference by simillarity to ideal solution (TOPSIS) method, which is a method that can give weighting and ranking for each criterion. With the technique for order preference by simillarity to ideal solution (TOPSIS) method, the author creates a system that is expected to later be able to assist decision making in the selection of electric light bulbs.]]>
<![CDATA[Application of the Analytical Hierarchy Process (AHP) Method in Hospitality Waiters Recruitment ]]>
<![CDATA[Preddy Marpaung]]>;
<![CDATA[Rita Hamdani]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Hospitality waiters are the spearhead of a hotel in providing services to guests or customers. Where also the dignity of a hotel is in the waiters themselves, because it is the waiters who deal directly with customers such as welcoming guests, providing information about hotels, honesty, behavior and other matters related to service. Therefore, it is necessary to pay attention to the criteria or expertise of the prospective waiters recruited by the hotel in maintaining the reputation or good name of the hotel for the convenience of customers and to increase hotel turnover. However, there is no system or method applied by the hotel, in this case the Halay Tanjung Morawa hotel to support and facilitate the management in making decisions to determine prospective waiters in the recruitment carried out by the hotel.Analytical Hierarchy Process (AHP).with the use of the AHP method can produce good and effective decisions in recommending the best waiters according to the highest score, which is rank 1, so that the existence of a decision support system with the application of this AHP method can assist hotel management in recruiting their waiters for each episode objectively.]]>
<![CDATA[Enhance the Accuracy of k-Nearest Neighbor (k-NN) for Unbalanced Class Data Using Synthetic Minority Oversampling Technique (SMOTE) and Gain Ratio (GR) ]]>
<![CDATA[Khairul Umam Syaliman]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[k-Nearest Neighbor (k-NN) has very good accuracy results on data with almost the same class distribution, but on the contrary for information whose class distribution is not the same, the accuracy of k-NN will generally be lower. In addition, k-NN does not separate information for each class, implying that each class has an equal influence in determining the new information class, so it is important to choose a class that generally applies to information before characterizing the class assignments process. To overcome this problem, we will propose a structure that uses the Synthetic Minority Oversampling Technique (SMOTE) strategy to address class distribution problems and Gain Ratio (GR) to perform attribute selection to generate a new dataset with a reasonable class spread and significant class information attributes. E-Coli and Glass Identification were among the datasets used in this review. For objective results, the 10-fold-cross validation method will be used as an evaluation method with k values 1 to 10. The results of the research prove that SMOTE and GR can increase the accuracy of the k-NN method, where the highest increase occurred in the Glass Identification dataset by a difference increase of 18.5%. The lowest increase in accuracy occurred in the E-Coli dataset with an increase of 11.4%. The overall proposed method has given better performance, although the value of precision, recall, and F1-Score is not better than original k-NN when used in dataset E-Coli. To all datasets, an improvement from precision is 41.0%, recall is 43.4% and F1-Score is 41.5%.]]>
<![CDATA[Traffic Officers Attendance System Design Using GPS and IMEI Smartphone ]]>
<![CDATA[Adnan Buyung Nasution]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[The reduction of traffic congestion level in the capital is not only viewed from the side of road width, vehicle density, and waiting time at the traffic signs but also no less important is the presence of traffic officers who secure every traffic crossroads. Therefore, it takes a system design that can perform online attendance at the traffic officer. This design utilizes a smartphone device that is IMEI (International Mobile Equipment Identity) as an identification officer and GPS (Global Positioning System) as a marker of attendance at the crossing of traffic signs. By using IMEI and GPS is expected to know the position and identity of officers and work time on the officer.]]>
<![CDATA[DECISION SUPPORT SYSTEM TO CHOOSE SMARTPHONE USING TOPSIS METHOD ]]>
<![CDATA[Agung Hamdika Surya]]>;
<![CDATA[Ilka Zufria]]>;
<![CDATA[Yusuf Ramadhan Nasution]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Technology has developed very rapidly nowadays, especially on smartphones. Nowadays smartphone is an item that is in great demand by everyone. smartphone is a mobile phone that has a function like a computer and also called mini computer. There are people who find it difficult to choose a smartphone with various advanced features available. Therefore, a decision support system was made using the TOPSIS method to select the smartphone that suits your needs. TOPSIS (Technique for order prefrence by similarity to ideal solution) is one of the multi-criteria decision making methods to find preference values based on criteria and alternatives. A total of 7 criteria chosen by the author that are: price, brand, ram, battery, front camera, rear camera and display. Therefore, the alternatives used are Samsung A20, Xiaomi Mi A1, Realme C2, Asus Zenfone Max M2 and Oppo F5 Youth. The data is then calculated using the TOPSIS method based on the stages. So that we can get the preferences value and the rank of the smartphone we wanted which is then implemented into a web-based application. Keywords : Smartphone, TOPSIS, DSS]]>
<![CDATA[Implementation Particle Swarm Optimization to improve the performance of Naive Bayes on Diabetes Detection Data ]]>
<![CDATA[Handini Arga Damar Rani]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Diabetes has certainly been widely known throughout the world as a serious disease. According to WHO data in 2014 there were about 422 million adults who had diabetes. This is very interesting because the increase is very visible, almost more than doubled when compared to in 1980 people with diabetes were only around 108 million people. The more sophisticated technological developments nowadays, various types of diseases can be detected computerized using the data mining method. In this study, the researcher proposes the particle swarm optimization method to improve the quality of the data to be used in the detection of diabetes using the nave Bayes method. The resulting model was tested to obtain the accuracy and AUC (Area Under Curve) of each algorithm so that it was found that testing using nave Bayes got an accuracy value of 96.15% with an AUC value of 0.991. Meanwhile, testing using the Naïve Bayes method based on attribute selection using the Particle Swarm Optimization (PSO) method, obtained an accuracy value of 97.13% with an AUC value of 0.995.]]>
<![CDATA[GEOGRAPHIC INFORMATION SYSTEMS FOR THE DISTRIBUTION OF COMMUNITY SERVICE ACTIVITIES IN KUANTAN SINGINGI DISTRICT ]]>
<![CDATA[Nofri Wandi Al Hafiz]]>;
<![CDATA[M. Hasim Siregar]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Villages where community service has been carried out so far the data will be stored in the LPPMDI archive file in the form of a work report, which annually will be given to LPMP for making lecturer performance reports, but LPPM itself does not yet have historical data on Community Service in the form of maps, so that villages that have been carried out activities or that have never been visited, cannot be presented in a visual form that can be accessed by many people, only limited to report data, besides that the problems that exist in each village in Kuantan Singingi Regency will be different, so a system is needed to describe and select potential and appropriate locations to serve as locations for community service and display the results of this service, villages where community service has been carried out have been mapped and seen the results of the community program the team appointed to implement it in the form of ideas the implementation team, the types of activities carried out, the targets to be achieved by the team in the service program, the results produced after the service, and activity documentation, all of this is entered into a system that can be seen in the form of maps, with the aim of being accessible to general users such as the public. or related institutions.]]>
<![CDATA[Expert System Application for Identification of Chili Plant Diseases Using Forward Chaining and Oreste Methods ]]>
<![CDATA[Muthmainnah]]>;
<![CDATA[Rizky Putra Fhonna]]>;
<![CDATA[Safwandi]]>;
<![CDATA[Veri Ilhadi]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Chili is a plant that has an important role in human life. Apart from being a source of vitamins, chili can also be used as a mixture of food and medicine. In the implementation of planting, chili plantings often fail, including crop failure due to various kinds of diseases. However, to find out the type of disease that attacks it requires an expert / agricultural expert, while in handling chili plant diseases it is often time-constrained due to the limited knowledge of the farmers and the lack of an expert who is an expert in this field who can go directly to farmers. Therefore, to overcome the problems of farmers, a system that has knowledge like an expert in this case has knowledge of the symptoms and diseases of chili plants. To answer this problem, a web-based expert system application will be built. The design of this system uses the forward chaining and oreste method which is intended to assist farmers in diagnosing chili plant diseases. Expert systems are used in all fields, one of which is in the field of food crops. One of the benefits of expert systems in the field of food crops is that it makes it easier for farmers to detect diseases in chili plants so that farmers can find out the type of disease and how to handle it quickly without having to wait for experts who have competence in that field.]]>
<![CDATA[Application of the Dijkstra Method in the Geographic Information System of the Nearest School Route Based on Android ]]>
<![CDATA[Muhammad Syahputra Novelan]]>;
<![CDATA[Dian Kurnia]]>;
<![CDATA[Rizky Putro Nugroho Dwi Cahyo]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Klambir V Kebon Village, Hamparan Perak District, Deli Serdang Regency is one of the villages that has a variety of and quality education locations. To advance the world of education in the village of Klambir V, it is necessary to have information media that can take advantage of android smartphones. Therefore we need a geographic information system that produces information for directions to the closest location from where you live to an Android-based school. One of the methods used to find the closest route is the Djikstra method. This method can complete the search for the shortest path from an origin vertex to a destination vertex in a weighted graph. The result of this system is that with the application of finding the shortest path, the process of finding the nearest school can be accessed more quickly and with accurate information. The Djikstra algorithm used in the process of finding the shortest path is very helpful and easy to understand by the author. Distance information at each point becomes clearer and can manage the time in the school search process.]]>
<![CDATA[Decision Support System Determining the Best Private Universities Using the Analytical Hierarchy Process Method (Case Study: LLDIKTI Wilayah I) ]]>
<![CDATA[Dewi Wahyuni]]>;
<![CDATA[M. Rhifky Wayahdi]]>
<![CDATA[ INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Private Universities (PTS) are an option to continue post-graduate education, especially in the city of Medan. Quality private universities are very influential in carrying out education. In order to be easy to compete in the wrong world of work such as accepting new workers and especially in increasing career paths, PTS accreditation is very influential in the world of work as one of the requirements for evaluating job application administration files because a good PTS must have good accreditation. Determining PTS in this Medan city is not easy, because there are many PTS in this Medan city. There are too many private universities in existence, making it difficult to choose PTS manually, and the results of the selection are sometimes inaccurate and become a problem in selecting the best PTS. Decision Support System (DSS) is a system that can assist a person in making accurate and targeted decisions. The method used in this Decision Support System uses the Analytical Hierarchy Process (AHP). This method was chosen as one of the best alternatives because it is able to find and select which are the best private universities based on the specified criteria.]]>
