Jurnal Teknik Informatika dan Sistem Informasi最新文献

{"title":"Klasifikasi Wilayah Potensi Risiko Kerusakan Lahan Akibat Bencana Tsunami Menggunakan Machine Learning","authors":"Arvira Yuniar Isnaeni, S. Prasetyo","doi":"10.28932/jutisi.v8i1.4056","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.4056","url":null,"abstract":"Indonesia is an archipelagic country with a long coastline where some areas are prone to tsunami waves which can result in land damage. Tsunamis occur due to earthquakes or volcanic eruptions under the sea that cause movement of the seabed and then create strong waves. The Special Region of Yogyakarta, precisely in Bantul Regency, is one of the areas that have a high risk of a tsunami disaster because the area is located in the expanse of the Indian Ocean which has quite impulsive plate movements. This study aims to find out information about the level of risk of land damage due to the tsunami using vegetation index data from OLI 8 Landsat imagery. Classification or prediction using the Artificial Neural Network (ANN) method. The vegetation index used is NDVI, NDWI, NDBI, SAVI, and MNDWI. The relationship between SAVI and NDVI has a positive correlation coefficient with the highest value of 0.962 where the potential risk of low damage is 0.933 and the potential risk of high damage is 0.856. Classification of potential areas of high risk of damage to tsunami land (High Risk) using the ANN method resulted in 7 villages with high risk. The ANN algorithm is the most accurate method for classification predictions between the Random Forest and SVM methods which get an accuracy of 95.45% and get a Kappa value of 86.08%. Spatial prediction using IDW produces a map of the distribution of the potential risk area for land damage caused by the tsunami.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128957985","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":"Pendeteksi Sampah Metal untuk Daur Ulang Menggunakan Metode Convolutional Neural Network","authors":"Ranti Holiyanti, Sukma Wati, Ikbal Fahmi, Chaerur Rozikin","doi":"10.28932/jutisi.v8i1.4492","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.4492","url":null,"abstract":"Waste is part material that has no value within the scope of production. If you no longer need it, metal cans can take about 80 to 200 years to decompose. CNN is part of the supervised learning method that exists in deep learning, where those who have expertise in representing images or images from several categories increase recognition, namely in classifying objects, doing scene recognition, and detecting object detection. In this study, using the CNN method as a development model and applying the ResNet 50 network design, which includes the type Convolutional Neural Network (CNN) that operates by way of working, namely receive an input in the form of an image or images. The input will be carried out by training that is set using the CNN architecture so that later it will produce an output that can recognize objects as expected in knowing the types of cardboard and glass waste. The implementation of this research uses the Python programming language, Anvil, and the TensorFlow and Keras libraries. The system has succeeded in detecting the type of metal waste from general waste and assisting third parties, namely implementing it through the website using Anvil. The input shape for CNN modeling in this study is 512x384 pixels, which has a value of 100 eras, and the data set used contains images of metal waste and general waste found 547 images, resulting in an accuracy of 96%.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132185315","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":"Penerapan Metode Simple Additive Weighting dalam Menentukan Perguruan Tinggi Negeri","authors":"Muhammad Dedi Irawan, Yustria Handika Siregar, Sity Tree Adinda Tambunan, Muhammad Artha Ardika","doi":"10.28932/jutisi.v8i1.3966","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.3966","url":null,"abstract":"World University Ranking is a system tool that functions to measure and assess all the best universities around the world (World Class University) which aims to advance all Universities through websites owned by each University. There are several problems in choosing a college. The selection of campuses or State Universities (PTN) is still often a problem or obstacle for every prospective student and parent to choose further education for the future of their children, especially as we often know that there are many universities in Indonesia. Indonesia ranges from state universities to private universities. One of the efforts in the selection recommendations made to facilitate this is to conduct an assessment of the best PTN. In this study, the Simple AdditiveWeighting (SAW) method was applied to the best college recommendation system. The criteria used are Tuition Fees, Academic Reputation, Employer Reputation, Teaching, Research, and Citation. After the criteria are determined, the next process is theranking process of the existing alternatives. The results of each method can provide recommendations for students or parents in choosing a college.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121395151","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":"Perancangan Aplikasi Monitoring Kalori Sebagai Upaya Pencegahan Penyakit Diabetes Mellitus Berbasis Android","authors":"Diyah Intan Pramitha Sari, Restyandito Restyandito, Kristian Adi Nugraha","doi":"10.28932/jutisi.v8i1.4301","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.4301","url":null,"abstract":"There are still many people who pay less attention to calories, both the amount of calorie needs of the body and the number of calories that have been consumed. One of the contributing factors is the difficulty of manually calculating the number of calories itself. Meanwhile, consulting with nutritionists is expensive.It's very risky for health. So made an application monitoring the number of calories. It applies goal directed design (GDD) method. In this study, usability test was conducted using 3 aspects of usability, namely effectiveness, efficiency, and satisfaction in accordance with ISO-9241-11 standard that produces effectiveness value of 97%, efficiency value of 66%, and satisfaction value of 86.75%. A total of 92.5% of respondents felt helped in calculating their calorie count. 97.5% of respondents felt more alert to diabetes after using the app, and 62.5% of respondents said that they would re-use the app for daily use in the future.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138364","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":"Perbandingan Relational Database dan Non-Relational Database dalam Pengembangan Smart Tourism","authors":"Mutmainnah A, Musyrifah, Nuralamsyah Zulkarnaim","doi":"10.28932/jutisi.v8i1.4353","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.4353","url":null,"abstract":"The smart tourism application that is built cannot be separated from the role of the database. The more data stored in a database system, it will affect the speed of access of the information system that uses it. This study will test the performance of query response time between two types of databases with 92 data records of tourist attractions, 106 restaurants and 59 lodging data. Tests were carried out on Data Manipulation Language (DML), aggregate function testing, and logical operator testing. The result of this study is that Non-relational databases are proven to be superior in the DML testing process (insert, select, update, and delete) than Relational Databases. For the process of testing logical operators (AND, OR, and NOT) Non-relational databases are proven to be superior to Relational Databases. In the MIN aggregate function test the results are the same, while the MAX Relational Database aggregate function test is superior to the Non-relational database.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122343151","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":"Perancangan System Crawler dengan MenerapkanArsitektur Distributed Task","authors":"Heri Santoso, Indyah Hartami Santi, Ni’ma Kholila","doi":"10.28932/jutisi.v8i1.4205","DOIUrl":"https://doi.org/10.28932/jutisi.v8i1.4205","url":null,"abstract":"PDC Media Group is a company engaged in online trading. The need for data insight in the online marketplace is very important. Likewise, how to get quite a lot of data, of course, requires automation such as crawling data on the marketplace website. Due to the large amount of data, crawler systems are often not optimal in crawling data. The application of distributed tasks on the crawler system provides convenience in scaling the server both vertically and horizontally. Therefore, the large and growing data can be handled by the crawler system. The application was developed with the Python language, with the  application server using Google Cloud Computing. In a distributed task architecture requires a component in the form of a message broker. The message broker used in designing this system is RabbitMQ. Testing the crawler system uses 3 scenarios, namely with 1 worker, 2worker, and 3 worker. The results for the 1 worker scenario are 19.3 requests per second and 332 ms for response time. The results for the 2 worker scenario are 41.4 requests per second and 328 ms for response time. While the results for the 3 worker scenario are 60 requests per second and 331 ms for response time.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"28 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124495188","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":"Deteksi Serangan Spoofing Wajah Menggunakan Convolutional Neural Network","authors":"Raden Budiarto Hadiprakoso, I. Buana","doi":"10.28932/jutisi.v7i3.4001","DOIUrl":"https://doi.org/10.28932/jutisi.v7i3.4001","url":null,"abstract":"Facial recognition-based biometric authentication is increasingly frequently employed. However, a facial recognition system should not only recognize an individual's face, but it should also be capable of detecting spoofing attempts using printed faces or digital photographs. There are now various methods for detecting spoofing, including blinking, lip movement, and head tilt detection. However, this approach has limitations when dealing with dynamic video spoofing assaults. On the other hand, these types of motion detection systems can diminish user comfort. As a result, this article presents a method for identifying facial spoofing attacks through Convolutional Neural Networks. The anti-spoofing technique is intended to be used in conjunction with deep learning models without using extra tools or equipment. Our CNN classification dataset can be derived from the NUAA photo imposter and CASIA v2. The collection contains numerous examples of facial spoofing, including those created with posters, masks, and smartphones. In the pre-processing stage, image augmentation is carried out with brightness adjustments and other filters so that the model to adapt to various environmental conditions. We evaluate the number of epochs, optimizer types, and the learning rate during the testing process. The test results show that the proposed model achieves an accuracy value of 91.23% and an F1 score of 92.01%.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117038962","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":"Career Success Model: A Case Study of Information Technology Graduates","authors":"Julianti Kasih, Doro Edi, Radiant Victor Imbar","doi":"10.28932/jutisi.v7i3.4082","DOIUrl":"https://doi.org/10.28932/jutisi.v7i3.4082","url":null,"abstract":"Success in a career is everyone's dream, and it is not an exception for Information Technology graduates who are engaged in information technology-related jobs. Several studies have documented the role of the following two (2) constructs, namely Career Competence (CC) and Lecturer Competence (LC), in Career Success (CS). The authors believe that University Commitment (UC) must be included in this list. This research aims at developing a model that explains and measures the relationship amongst those four (4) constructs. The model that will be developed is based on the Structural Equations Modelling Technique. Respondents participating in this research are IT graduates working in IT-related jobs who have graduated from three (3) private universities in Bandung (Indonesia), namely, Maranatha Christian University (UKM), Parahyangan Catholic University (UNPAR), and Harapan Bangsa Institute of Technology (ITHB)) with graduating years ranging from 2006 to 2018. The collected data will be processed using IBM SPSS AMOS. This research proves that firstly, LC influences both UC and CC, secondly, UC influences CC, and lastly, CC affects CS. Further hope this model can be developed for other universities in Indonesia to increase Lecture Competency and University Commitments by the strategic plans of each university. \u0000  \u0000Respondents participating in this research are IT graduates working in IT-related jobs who have graduated from three (3) private universities in Bandung (Indonesia), namely, Maranatha Christian University (UKM), Parahyangan Catholic University (UNPAR), and Harapan Bangsa Institute of Technology (ITHB)) with graduating years range from 2006 to 2018. The collected data will be processed using IBM SPSS AMOS. This research proves that firstly, LC influences both UC and CC, secondly, UC influences CC, and lastly, CC affects CS. Further hope this model can be developed for other universities in Indonesia to increase Lecture Competency and University Commitments by the strategic plans of each university. \u0000  \u0000Keywords— Department of Information Technology, Career Success, Commitment of Higher Education Lecturer Competency, Career Competence","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125775022","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":"Perancangan Antarmuka Berdasarkan Evaluasi Usabilitas Penggunaan Aplikasi KlikDokter Untuk Pralansia dan Lansia","authors":"Christianti Angelin Maarende, Danny Sebastian, Restyandito Restyandito","doi":"10.28932/jutisi.v7i3.4081","DOIUrl":"https://doi.org/10.28932/jutisi.v7i3.4081","url":null,"abstract":"The situation and condition of the spread of Covid-19 in Indonesia have forced everyone to reduce the intensity of going out of the house, including activities related to the need for health services. Therefore, a solution is needed so that people can meet their health needs without leaving the house. Taking into account that the elderly as the community group that is most vulnerable to contracting the virus and has the highest mortality rate, it can be said that the elderly is the group of people who most need online health services. Along with the growing penetration of internet usage and the increasing number of smartphone ownership in Indonesia, m-health is the right choice to help people access health services online via smartphones. KlikDokter is an example of m-health or a mobile-based application that provides various online health services. However, it was found that there were complaints that the KlikDokter application was too complicated and difficult for the elderly to use. From this problem, a usability test was finally carried out on the KlikDokter application interface, to identify what interface elements in the KlikDokter application were difficult for elderly users. The research respondents were divided into two groups with 16 and 17 people respectively. The first group is the elderly group aged >60 years. And the second group is the pre-elderly group with ages between 45 to 59 years. A pre-elderly group is a comparison group (control group). This test is carried out by measuring several aspects of usability, namely effectiveness, efficiency, user satisfaction, error, and cognitive load.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132016191","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":"Aplikasi Pengelolaan Persediaan Bahan Pada Usaha Kecil Menengah Pakaian Jadi","authors":"Antonius Susanto, C. E. Nugraheni, Maria Widyarini","doi":"10.28932/jutisi.v7i3.4125","DOIUrl":"https://doi.org/10.28932/jutisi.v7i3.4125","url":null,"abstract":"Clothing is one of the basic or primary needs. With the influence of clothing fashion that continues to grow, many Small and Medium Enterprises (SMEs) have sprung up engaged in the clothing sector. SMEs are one of the driving forces of the Indonesian economy. SMEs engaged in the clothing sector are businesses that produce apparel. The materials used in the manufacture of clothing also vary, so that inventory management and material requirements planning are essential processes in the manufacture of clothing. In this study, a simple mobile application was developed that can be used for material inventory management for SMEs. The primary function of this application is to record materials (inventory) and plan production needs using the Reorder Point (ROP) method. The Reorder Point (ROP) method is an order limit point helpful in knowing when a company holds an order. Program development using Android Studio IDE with Flutter framework and Dart programminglanguage. The results of functional testing on this application are 90% achieved following the expected results. The user acceptance test concludes that this application has the potential to facilitate SMEs in managing the inventory of material.","PeriodicalId":185279,"journal":{"name":"Jurnal Teknik Informatika dan Sistem Informasi","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121390546","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}