Ilkom Jurnal Ilmiah最新文献

{"title":"Influence of gray level co-occurrence matrix for texture feature extraction on identification of batik motifs using k-nearest neighbor","authors":"Z. Y. Lamasigi, Andi Bode","doi":"10.33096/ilkom.v13i3.1025.322-333","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.1025.322-333","url":null,"abstract":"Batik is one type of fabric that is unique because it has a special motif, in Indonesia itself batik is unique because it has certain motifs that are made based on the culture from which batik was made. This study aims to examine the effect of the texture feature extraction method on the identification of batik motifs from five major islands in Indonesia. The method used in this study is the Gray Level Co-occurrence Matrix as the texture feature extraction of batik motifs to obtain good batik motif identification accuracy results and to determine the value of the proximity of the training data and image testing of batik motifs, the K-Nearest Neighbor classification method will be used based on texture feature extraction value obtained. In this experiment, 5 experiments will be carried out based on angles 0 degrees, 45 degrees, 90 degrees, 135 degrees, and 180 degrees using the values of k is1, 3, 5, and 7. The confusion matrix will be used to calculate the accuracy level of the K-Nearest Neighbor classification. From the results of experiments carried out using training data as many as 607 images and testing as many as 344 images in five classes used with angles of 0 degrees, 45 degrees, 90 degrees, 135 degrees, 180 degrees, and values of k are 1, 3, 5, and 7, getting the highest accuracy results is at an angle of 135 degrees and 180 degrees with a value of k is 1 of 89.24% and the lowest is at an angle of 90 degrees with a value of k is 3 of 67.44%. This shows that the Gray level co-occurrence matrix method is good for extracting the texture features of batik motifs from five major islands in Indonesia, it is evidenced by the results of the average accuracy of the classification obtained.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43421892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geographic information system in determining flood and safe zone for flood mitigation","authors":"N. K. Nur, M. Chaerul, Abdul Azis","doi":"10.33096/ilkom.v13i3.942.294-299","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.942.294-299","url":null,"abstract":"Computer-based technology has pervaded practically every aspect of human life in the modern era. Through diverse information systems, various fields have employed computer-based technology to build theories and their applications. Geographic Information System (GIS) technology is one type of computer-based system that is widely employed. Various disciplines can use Geographic Information System (GIS) technology to research and map flood zones. The research approach employed is the employment of ARC GIS 10.5 system technology to determine the flood zone's features. Pampang, Tamamaung, Sinri Jala, and Karuwisi Utara are four villages that are flood-prone locations that are included in the warning zone, according to the results of data processing using GIS software and data analysis illustrated from mapping the flood area in Panakkukang District. There are 1,985 hectares in the Rappocini sub-district, which is included in a vulnerable region, namely Bantabantaeng Village, and 145,709 hectares in Karunrung Village, Gunung Sari, Bontomakkio, Tidung, Kassi-Kassi, Mappala. Parts of the Manggala, Bangkala, and Borong regions, as well as sub-districts of Manggala, are included in the vulnerable areas. Tamalanrea Indah, Tamalanrea Jaya, and Tamalanrea sub-districts are the Tamalanrea sub-districts that have been designated as vulnerable zones.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43239030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The application of system usability scale method to measure the usability of electronic learning system (e-learning) of politeknik caltex riau","authors":"Rika Perdana Sari, Silvana Rasio Henim","doi":"10.33096/ilkom.v13i3.920.266-271","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.920.266-271","url":null,"abstract":"The COVID-19 pandemic that has occurred globally in all countries, including Indonesia, has generally changed the series of business process arrangements in almost all sectors, including education. One of the affected educational institutions is the Caltex Riau Polytechnic (PCR) campus. The impact of this pandemic has forced the academic members (lecturers and students) to carry out the online lecture process since the odd semester of the 2020/2021 academic year. The online lecture process is facilitated by an electronic learning system (e-learning). Changes in the pattern of learning process, from face-to-face to online methods using e-learning, raises several usability problems. The usability measurement of e-learning at PCR was carried out using the System Usability Scale (SUS) questionnaire. This study involved 196 participants. From the usability analysis of e-learning at PCR, the score obtained was 58.75 with the assessment criteria on the adjective rating was OK, the grade scale was D, and the acceptable ranges were at marginal low. This means that it is necessary to evaluate and improve the utilization of the features/services provided by the e-learning platform so it can be more efficient, effective, and satisfying to its users.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42293436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The selection of SNMPTN applicants using the TOPSIS and rank order centroid (ROC) methods","authors":"M. Sutoyo, Andi Tenri Sumpala Mangkona","doi":"10.33096/ilkom.v13i3.936.272-284","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.936.272-284","url":null,"abstract":"One of the main functions of higher education is to develop personality abilities and shape the character of a dignified nation's civilization. One of the entry pathways for new student admissions at State Universities is the SNMPTN Path. While the number of participants who are accepted by looking at the quota on the SNMPTN line is only 20 percent of the capacity. Decision Support System as a solution that can assist policymakers in determining a decision. In this study, a decision support system was built using the TOPSIS method for selecting and ROC as a weighting for each criterion. Based on the results of the selection test for SNMPTN participants using the TOPSIS and ROC methods as weighting, it proves that it can display the cumulative ranking results of each alternative based on the criteria values owned.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47976318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grouping the spread of the covid-19 virus based on the positive case number, population and area width using the k-means clustering method","authors":"Asep Muhidin, Muhtajudin Danny, Elkin Rivali","doi":"10.33096/ilkom.v13i3.1011.314-321","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.1011.314-321","url":null,"abstract":"The spread of the Covid-19 virus began to enter Indonesia in early 2020. Until now, the spread of the virus is still occurring in several parts of Indonesia, although it has begun to decline in many areas. ). The possibility of direct human contact depends on the number of confirmed positives, the population and the area. Therefore, this study looks for the characteristics of the city/district area group based on the population, area and number of residents who are confirmed positive for the Covid-19 virus using the K-Means Clustering method. The clustering process begins with finding the best number of clusters (K) using the elbow method and testing cluster members using the silhouette and davies-bouldin index methods. The best K value results obtained by the elbow method are 3 clusters (K=3). The results of K-Means Clustering with 3 clusters show that in cluster 1, a city or district with a small area with a large population, the number of positive COVID-19 residents is large. In cluster 2, a city or district with a small area, with a moderate population, the number of people who are positive for COVID-19 is small. And in cluster 3, a city or district with a large area, with a very small population, the number of positive COVID-19 residents tends to be moderate.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44752006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of cendrawasih birds using convolutional neural network (CNN) keras recognition","authors":"Warnia Nengsih, Ardiyanto Ardiyanto, A. Lestari","doi":"10.33096/ilkom.v13i3.865.259-265","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.865.259-265","url":null,"abstract":"Classification is part of predictive modeling and supervised learning. This method is used to determine the data class based on the previous value. In solving certain cases, there are various classification methods with varying degrees of accuracy. Convolutional Neural Network (CNN) is part of the Multilayer Perceptron (MLP) for processing two-dimensional data. CNN is also part of the Deep Neural Network and is applied to image objects. Some sources state that the classification process using images is not appropriate to be implemented in MLP. This will result in the accuracy of the method in handling certain cases. This study uses cendrawasih bird as object in the classification process to determine the accuracy of the keras recognition method. From the results of this study, a training model was conducted using 10 epochs with an accuracy and loss value of 0.0850 and 2.5658 respectively. These results indicate that MLP can successfully complete the classification process using images. These results indicate that MLP can successfully complete the classification process using images .","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46735015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The implementation of forward chaining and certainty factor methods to examine the covid-19 vaccination eligibility","authors":"H. Herlina, Valensa Yosephi, Hazriani Hazriani","doi":"10.33096/ilkom.v13i3.973.307-313","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.973.307-313","url":null,"abstract":"","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46011756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Usability testing of intensive course mobile application using the usability scale system","authors":"M. Rohandi, Nurlaila Husain, Indri Wirahmi Bay","doi":"10.33096/ilkom.v13i3.821.252-258","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.821.252-258","url":null,"abstract":"The Mobile Intensive Course (MIC) application version 2 is an application designed to assist the learning process of the English intensive course subject. Measurement of the application usability has never been done before, so the effectiveness, efficiency, and user satisfaction for this application have not been measured yet. Also, usability measurement can be used as a reference for the level of user loyalty, whether it is net promoters, passive users, or detractors. One of the usability measuring tools that are easy to use but still valid and reliable, is the System Usability Scale (SUS). The purpose of this study was to test the usability of the application to determine the quality using the SUS questionnaire. This research was conducted in four steps, namely 1) trying out the application to the respondents; 2) distributing SUS questionnaires; 3) calculating the average SUS score; 4) analyzing the average SUS score. This study involved 37 respondents consisting of students and EIC lecturers. The results of this study indicates that the usability of the application can be accepted by users with an average SUS score of 70.61 and obtained C mark based on the CGS assessment. Nevertheless, the application only obtained passive users. The average contribution value for learnability was still low, namely 1.9 from the maximum score 4. It is necessary to improve future applications in terms of application learnability that allowing users to be more familiar with applications and potentially becoming net promoters.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46400619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image processing analysis to determine fajr time using the imagej application","authors":"Arif Septianto, R. Rosalina, H. Ramza","doi":"10.33096/ilkom.v13i3.954.300-306","DOIUrl":"https://doi.org/10.33096/ilkom.v13i3.954.300-306","url":null,"abstract":"The determination of early prayer times is an essential aspect as it is one of the five pillars in Islam and prerequisites for prayers to be accepted. The government has set a standard for carrying out the fajr prayer by determining the degree of appearance of the fajr as-Sadiq at -2 0̊ . This study aims to compare the initial determination of the government's fajr time using different sensors. In this case, the drones as the image sensor. The drone was chosen because it has several advantages. The result of data is in the form of images. Then the images were processed using digital image processing software, called Imagej. The data from Imagej processing were in the form of mean and standard deviation. All data were then recapitulated using Microsoft excel and plotted to form data which was then carried out by a polynomial approach to determine the cut-off point as an early indicator of the beginning of fajr. The method used in this study is using a qualitative analysis method with a polynomial 5 approach. The conclusion obtained in this study is that the government's fajr time is 21 minutes faster. The standard used in this study is a DIP of -13.9 5̊ . Unlike the SQM with 2D drone data, the 3D version generates more accurate data analysis and is not easy to manipulate because it can be verified with image data.","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44568905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"'Pakarena' dance image classification using convolutional neural network algorithm","authors":"A. Ibrahim, Rachmat Rachmat","doi":"10.33096/ilkom.v13i2.816.134-139","DOIUrl":"https://doi.org/10.33096/ilkom.v13i2.816.134-139","url":null,"abstract":"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%. E-ISSN 2548-7779 ILKOM Jurnal Ilmiah Vol. 13, No. 2, August 2021, pp. 134-139 135 Ibrahim & Rachmat (‘Pakarena’ dance image classification using convolutional neural network algorithm) Method A. Pakarena Dance Before it became the current form of Pakarena dance show in Figure 1, it was known as Sere Jaga which was part of a community ritual ceremony before planting rice and after planting rice. Where the dancers hold a bunch of quality rice (rice seeds that have been selected through a ceremony) which is considered the goddess of rice. Then the Sere Jaga dance developed into a ritual ceremony carried out throughout the night in welcoming the rice harvest ceremony. These ceremonies include ammatamata jene, benteng ammata, and others. The existence of art in Indonesia cannot be separated from mystical stories at that time. This can also be seen in the arts from the South Sulawesi region, namely the Pakarena Dance. The beginning of its emergence cannot be predicted with certainty because there are only oral stories that are passed down from generation to generation. Pakarena dance originated from a myth about the separation between the inhabitants of the Land of Heaven and the inhabitants of the Ancient Earth. Before parting ways, Boting Langi taught the Lino people how to live, grow crops, raise livestock, and hunt through hand, body and foot movements. These movements then become ritual dances when the community expresses its gratitude to the residents. Another story mentions that the Pakarena dance is associated with legend as the first Somba (king) of the Kingdom of Gowa. It is said that Pakarena first appeared with Putri Tumanurung ri Tamalatea. According to the story, Pakarena is a companion and complement to the greatness of Tumanurung ri Tamalate [9]. Figure 1. Pakarena Dance B. Convolutional Neural Network The technique used in overcoming this ANN problem is used for image processing, classification and image grouping, in this case dance images that can directly perform image processing. ANN is an adaptive system that can change its structure to solve problems based on external and internal information f","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45901037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}