ILKOM Jurnal Ilmiah
ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, including Artificial intelligence, Computer architecture and engineering, Computer performance analysis, Computer graphics and visualization, Computer security and cryptography, Computational science, Computer networks, Concurrent, parallel and distributed systems, Databases, Human-computer interaction, Embedded system, and Software engineering.
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<![CDATA[The weighted product method and portfolio assessment in ranking student achievement ]]>
<![CDATA[Andi Tenri Sumpala]]>;
<![CDATA[Muhammad Nurtanzis Sutoyo]]>;
<![CDATA[Huzain Azis]]>;
<![CDATA[Fadhila Tangguh Admojo]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.827.148-154
<![CDATA[The learning process has a correlation with learning achievement which can be shown through the marks given by a teacher to students from several fields of study. The ranking of student learning achievements performed by the school refers to the grades of the subject is important for the SNMPTN (National Selection for State Higher Education). To determine student achievements, the method used in the current study is the weighted product. If the results of student ranking using the WP method have the same value, then a portfolio assessment is used. Of the 127 student achievement ratings, there were seven people who had the same Vector value. Then, the seven people who have the same vector value were graded using portfolio assessment. The results showed that the implementation of the WP method and portfolio assessment could determine the ranking of student achievement.]]>
<![CDATA[Performance comparison of support vector machine (SVM) with linear kernel and polynomial kernel for multiclass sentiment analysis on twitter ]]>
<![CDATA[Rifqatul Mukarramah]]>;
<![CDATA[Dedy Atmajaya]]>;
<![CDATA[Lutfi Budi Ilmawan]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.851.168-174
<![CDATA[Sentiment analysis is a technique to extract information of one’s perception, called sentiment, on an issue or event. This study employs sentiment analysis to classify society’s response on covid-19 virus posted at twitter into 4 polars, namely happy, sad, angry, and scared. Classification technique used is support vector machine (SVM) method which compares the classification performance figure of 2 linear kernel functions, linear and polynomial. There were 400 tweet data used where each sentiment class consists of 100 data. Using the testing method of k-fold cross validation, the result shows the accuracy value of linear kernel function is 0.28 for unigram feature and 0.36 for trigram feature. These figures are lower compared to accuracy value of kernel polynomial with 0.34 and 0.48 for unigram and trigram feature respectively. On the other hand, testing method of confusion matrix suggests the highest performance is obtained by using kernel polynomial with accuracy value of 0.51, precision of 0.43, recall of 0.45, and f-measure of 0.51.]]>
<![CDATA[Palm oil extraction rate prediction based on the fruit ripeness levels using C4.5 algorithm ]]>
<![CDATA[Wahyu Supriyatin]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.714.92-100
<![CDATA[Oil palm plantations are one of the main keys in supporting Indonesia’s economic growth. The rising consumption needs for palm oil products make it necessary to carry out data mining activities to increase CPO production. The maturity factor of palm fruit dramatically affects the quality of the oil extraction content (CPO yield) produced. This study aims to investigate the effect of fruit ripeness on the yield of CPO by using a data mining classification method with a decision tree. The algorithm used to generate decision tree classification is the C4.5 algorithm. The implementation of the C4.5 algorithm in the study was carried out using the Rapid Miner Studio 5.2 tools. The results shows that the yield of CPO is influenced by the attributes of the condition of the long and ripe fruit, the condition of the long and overripe fruit, the normal condition of the fruit and the age of 3-6 years and the condition of the fruit of normal and age of 7-10 years. Decision tree C4.5 algorithm generates 8 rules with 4 rules showing a high production value, which means that the four rules affect the yield of CPO.]]>
<![CDATA['Pakarena' dance image classification using convolutional neural network algorithm ]]>
<![CDATA[Abdul Ibrahim]]>;
<![CDATA[Rachmat Rachmat]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.816.134-139
<![CDATA[One of the riches of the Indonesian nation comes from the diversity of ethnicities and cultures, especially dance, which is the culture of the Indonesian people, starting from their ancestors until now, their authenticity is still maintained. The wrong cultural dance that develops, especially in South Sulawesi, which consists of four (4) ethnic groups, namely: Bugis, Makassar, Toraja and Mandar, which have their own dance dances from each tribe in South Sulawesi to maintain this dance. There is a need for collaboration between local community leaders, government and researchers, especially researchers to raise dance dances from the Makassar Tribe called Pakkarena dance using the Convolutional Neural Network (CNN) method to the Pakarena dance image in distinguishing or classifying an object on digital images with an accuracy level of 95 75%.]]>
<![CDATA[Fruit recognition system using color filters and histograms ]]>
<![CDATA[Budi Sugandi]]>;
<![CDATA[Rahmi Mahdaliza]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.822.140-147
<![CDATA[Nowadays, many children and adults do not know the type or name of fruits, especially if the fruit is a rare one. In this paper, a system was developed that can recognize fruit names in real time using a camera as a visual sensor. The camera captured the image and processed using image processing. This paper proposed a method using HSL color filters, RGB histograms and shapes of fruit objects to detect and recognize fruits. The proposed method was divided into two processes, namely the training and testing processes. The training process was carried out to obtain a database of each fruit. The first process of training was object detection using an HSL color filter. The calculation of the RGB histogram was conducted on the HSL color filtered object. After that, the object's roundness was measured. Meanwhile, the testing process was done by looking for the similarity of the histogram data of the test object with the reference object by using the histogram distance equation. The similarity of the object was determined by the distance value of the histogram of the tested fruit with the referenced fruit. Similar objects would have histogram distances less than the threshold values. Tests were implemented in several types of fruit. The test results showed the system could recognize fruit names accurately.]]>
<![CDATA[Internet of things based humidity control and monitoring system ]]>
<![CDATA[Eka Purnama Harahap]]>;
<![CDATA[Md Asri Ngadi]]>;
<![CDATA[Untung Rahardja]]>;
<![CDATA[Faisal Rizki Azhari]]>;
<![CDATA[Kenita Zelina]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Prodi Teknik Informatika FIK Universitas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.852.175-186
<![CDATA[This study proposes smart monitoring by utilizing IoT in agriculture which aims to assist farmers in monitoring crops in order to reduce the risk of failure. Quantitative method was employed to collect data from the Soil Moisture Sensor and DHT22 which are to read and write data that can be monitored on a cloud server or csv file to evaluate the risk. This monitoring system is created using the Python programming language by utilizing the Raspberry Pi as a microprocessor. The result of this study is data acquisition that is connected to the internet. Data can be accessed at Thingspeak to show indications and crop yields. Analogue form and indicators of water in soil moisture are indicated by colored marks. Proper monitoring shows more accurate crop data that enable the farmers to prevent crops from drying out. This system is expected to reduce the risk of crop failure as well as increase the agriculture productivity.]]>
<![CDATA[Sentiment analysis of game product on shopee using the TF-IDF method and naive bayes classifier ]]>
<![CDATA[Rifki Kosasih]]>;
<![CDATA[Anggi Alberto]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.721.101-109
<![CDATA[In every product sold on the E-commerce platform, there is a review column from consumers who have made transactions on the products. These reviews are in the form of comments and ratings (stars from one to five) written and given by consumers based on their assessment of the products purchased. With the product evaluation feature based on the rating, the consumer can find out how good or bad the quality of the product is. However, a problem arises when some consumers give negative comments with five stars or vice versa. This causes the product assessment feature based on the rating to be less good so that it does not represent the real value. Therefore, to determine the quality of the product, sentiment analysis was carried out using the TF-IDF method and the Naive Bayes Classifier based on reviews from buyers. The data collected is 1000 reviews which are divided into 700 training data and 300 test data. The next stage is the preprocessing text such as case folding (converting uppercase letters to lowercase), tokenizing (separating sentences into single words), stopwords (removing tokenizing conjunctions that have nothing to do with sentiment analysis), stemming (changing words into basic word forms), and word weighting with TF-IDF. The last step is to classify. Based on the classification results obtained an accuracy rate of 80.2223%.]]>
<![CDATA[Development of augmented reality application for introducing tangible cultural heritages at the lampung museum using the multimedia development life cycle ]]>
<![CDATA[Imam Ahmad]]>;
<![CDATA[Yuri Rahmanto]]>;
<![CDATA[Devin Pratama]]>;
<![CDATA[Rohmat Indra Borman]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.859.187-194
<![CDATA[Museum Lampung is one of the largest museums in Lampung Province which has a collection of tangible cultural heritage. If the museum visitors are seeking information about the collections, they will be assisted by museum guides orally. However, the limited number of guides are not enough to serve visitors during the school holidays. Therefore, to help visitors to find information about its cultural heritage collection, Augmented Reality (AR) technology was developed. AR is a technology that can display 3D objects in a real environment. The AR application that will be built is developed with the MDLC approach, where this method is suitable for developing multimedia applications. This research produces an application that can display 3D objects when the user's camera is directed to the collections of Museum Lampung and provides information related to these objects. Based on the test results on aspects of perceived usefulness, convenience, intention, and user friendliness, generally respondents answered "Agree" with a percentage of 83%. This indicates that the application is acceptable to the user.]]>
<![CDATA[Glucose level detection system in glucose solution using TCS3200 sensor with If-Else method ]]>
<![CDATA[Kemal Thoriq Al-Azis]]>;
<![CDATA[Alfian Ma'arif]]>;
<![CDATA[Sunardi Sunardi]]>;
<![CDATA[Fatma Nuraisyah]]>;
<![CDATA[Apik Rusdiarna Indrapraja]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.733.110-116
<![CDATA[Early and routine examination of glucose levels plays an important role in preventing and controlling diabetes mellitus and maintaining the quality of life. Checking blood sugar levels by hurting the body (invasive) can lead to infections caused by needles. As an alternative, the examination is carried out in a non-invasive way using excretory fluid in the form of urine, which is reacted with Benedict's solution that create a color change. Experts in the laboratory only carry out an examination using non-invasive methods because in determining glucose levels, it requires accuracy and eye health factors. Therefore, a glucose level detection system was created using a sample of glucose solution to determine the system's parameters using the if-else method. The glucose level detection system is conducted by mixing the glucose solution with Benedict's solution to produce a color change. Then the reaction results are read by the TCS3200 sensor and processed by Arduino to be classified, according to predetermined parameters. The decision results based on the classification of the glucose level parameters that have been determined are displayed on a 16x2 LCD. The results achieved in this study on 10 samples of glucose solution that were tested and processed by the if-else method were successfully read and classified based on predetermined parameters.]]>
<![CDATA[Enterprise architecture design using TOGAF at foundation of triputra persada horizon education ]]>
<![CDATA[Arif Budimansyah Purba]]>;
<![CDATA[Ahmad Mubarok]]>;
<![CDATA[Jajang Mulyana]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.847.155-162
<![CDATA[The use of information technology in the field of education is currently a top priority for managing academic and supporting activities. Tri Putra Persada Horizon Education Foundation which manages two high schools, namely the College of Health Sciences and the College of Information and Computer Management should face a challenge to align business strategy with information technology, and how to integrate all the parts involved in the business and represent it in an information system. To find out the business strategy and governance of information technology used at the Tri Putra Persada Horizon Education Foundation, an Enterprises Architecture Framework is needed, one of which is TOGAF ADM. The Enterprises Architecture design contained in TOGAF ADM includes a vision architecture that defines the vision of the company or agency, a mapped business architecture in the form of value chain analysis, an information system architecture in which there is a data architecture and application architecture and the last is technology architecture. This research produced an enterprise architecture design blueprint consisting of artifacts, in the form of catalogues, matrices, and diagrams based on the phases of TOGAF ADM. The result of the Enterprise Architecture design was an integrated information system recommendation and the technology architecture. The design is expected to be a reference in improving the quality of business and is expected to make it easier to achieve the business goals of the Tri Putra Persada Horizon Education Foundation.]]>
