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<![CDATA[Penerapan K-Means dan Rank Order Centroid pada Proporsi Individu dengan Keterampilan Teknologi Informasi dan Komputer ]]>
<![CDATA[Nurfitriana, Diana]]>;
<![CDATA[Voutama, Apriade]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.608
<![CDATA[Technological developments occur so quickly, resulting in continuous changes that qualified human resources are needed to support the endless times that run. This study will classify individuals with information technology and computer skills in Indonesia based on region. This research used K-Means clustering, the Rank Order Centroid method, and the Davies-Bouldin Index clustering evaluation method to assess accuracy. K-means clustering is a simple algorithm and does not require a target class. There are areas for improvement in the K-Means process, namely at the initial centroid determination stage. Therefore, the ROC method is used. Based on data taken from the website of Badan Pusat Statistik Nasional about the proportion of productive age individuals 15-59 years who have Information and Computer Technology skills by the province during 2017-2021. It produces 3 clusters, including a high-level cluster in which there are 8 provinces, a medium-level cluster in which there are 22 provinces, and a low-level cluster in which there are 4 provinces, and obtained a DBI value of 0.163625 which is close to 0, meaning that the quality of the accuracy of the clustering results is good. Based on clustering results with good accuracy, using K-Means can be combined with ROC and is quite effective. The government can use the results of this study to prioritize improving the quality of human resources in areas with low-level information and computer technology skills. Suggestions for further research using other clustering algorithms and ROC as a comparison.]]>
<![CDATA[Analisis dan Perbandingan Tools Forensik menggunakan Metode NIST dalam Penanganan Kasus Kejahatan Siber ]]>
<![CDATA[Yuladi, Achmad Iqbal]]>;
<![CDATA[Indrayani, Rini]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.636
<![CDATA[Cybercrime cases in Indonesia have increased yearly; during the COVID-19 pandemic as it is now, people rely on the internet to carry out daily activities such as teaching and learning activities, buying and selling online, working from home, etc. Therefore, cybercrime cases in Indonesia have increased. One of the most common examples is Cyberbullying cases on various social media networks with mobile platforms, one of which is WhatsApp Messenger. This study will analyze and compare the results of the MOBILedit Forensic Express and Magnet Axiom tools using the National Institute of Standards and Technology (NIST) method. This method can facilitate the investigation process in the case scenarios in this research. Researchers will also compare the results of the two tools used in this forensic process. The results of this study using the National Institute of Standards and Technology (NIST) method on the WhatsApp apps showed the Magnet Axiom tools were slightly superior with an accuracy of 82,8% compared to MOBILedit Forensics Express 72,7% in the condition that the object was not rooted.]]>
<![CDATA[Klasifikasi Jenis Burung menggunakan Metode Transfer Learning ]]>
<![CDATA[Pane, Yeremia Yosefan]]>;
<![CDATA[Sihombing, Jeremia Jordan]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.744
<![CDATA[Indonesia is known for its abundant natural resources, including its diverse bird fauna. The identification and classification of bird species is essential in maintaining biodiversity as well as for practical habitat management. Therefore, an efficient and accurate approach is needed to identify bird species. This study uses a deep learning approach to test and compare the MobileNetV2 architecture with architectures used in previous studies in recognizing bird species. We use a transfer learning approach that utilizes existing knowledge from pre-trained models and combines it with a Convolutional Neural Network (CNN) algorithm to detect and classify birds based on images with a total image data of 95376. Experimental results show that by using the MobileNetV2 architecture, we achieved an accuracy of 96.4% with a loss value of 0.241. Compared with the architecture used in previous research, our results show a significant improvement in accuracy and efficiency. The time taken to perform the classification at each step is about 646 ms. This study shows that using MobileNetV2 architecture in the transfer learning approach with CNN effectively performs bird species classification.]]>
<![CDATA[Smart Buildings menggunakan Hyperledger Fabric Blockchain untuk Manajemen Transaksi dan Pemodelan 3D ]]>
<![CDATA[Asmiatun, Siti]]>;
<![CDATA[Novita Putri, Astrid]]>;
<![CDATA[Zaman, Badroe]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.751
<![CDATA[Home construction or home renovation must consider many complex factors. That is because there will be errors / human errors that occur. The impact of that will cause losses to architectural services and eliminate dissatisfied customer trust. Another problem is that customers use intermediaries or third parties in the home construction/renovation process, increasing funds. That is because the process of building/renovating the house is different fromations. This research utilizes a hyper ledger fabric blockchain and intelligent building technology to manage architect and consumer management without intermediaries. Technology can manage home construction/renovation through information on 3-dimensional house plans, initial home budgets, prices for building materials, and daily material needs. The purpose is to monitor the building/renovation of a house without a third party. This study uses the Multimedia Development Life Cycle (MDLC) Development Method to make its application. Meanwhile, blockchain technology is applied using Hyperledger Fabric Software. This research can increase trust and benefit both the customer and the developer. The results of this study are that by making block numbers 65 – 66, it is recorded that each transaction has a processing time from 2022-08-14 02:32:47 to 2022-08-14 02:32:50; it takes approximately.]]>
<![CDATA[Strategi Implementasi SIEM untuk Mengurangi Risiko terhadap Kebocoran Informasi ]]>
<![CDATA[Anggara, Taufik Rendi]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.756
<![CDATA[More than 100 instances of information leakage brought on by unauthorized access occurred in 2022. This study used case studies in conjunction with system development. Early Warning Systems (EWS) are intended to give current information on event violations. When the worker goes to the console, EWS will warn and ask for verification. In Centralised Log Management (CLM), data logs were filtered with a policy-based Correlation setup approach. Network Security devices are configured for Rule-Based Correlations, and log data will be forwarded to CLM. In the case of an occurrence, logs are crucial to the inquiry. We used the CLM model to secure log data. EWS can filter harmful activity and malicious events from all current devices using this CLM. EWS will send any malicious activities or events it detects through telegram and email. Applying CLM and EWS with IT risk measurement can assist in reducing the risk of information leakage and offer quick information for breaches or incidents, according to this study. Evaluation, which lasted for two weeks, produced outcomes including less unauthorized activity, outstanding performance in the notification system that may assist in verifying access to the proper privileges for accessing the device, and simple detection of unauthorized access and file modifications, among other things.]]>
<![CDATA[Pengaruh Keseimbangan Data terhadap Akurasi Model Support Vector Machine pada Data Set Donor Darah ]]>
<![CDATA[Widyanto, Agung]]>;
<![CDATA[Kusrini]]>;
<![CDATA[Kusnawi]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.771
<![CDATA[In classification, unbalanced data is expected. Unbalanced data has an inequality ratio between the majority and minority classes. Models trained with unbalanced data tend to predict the minority class as the majority class. This study aims to determine the effect of data balance on the accuracy of the Support Vector Machine (SVM) classification model. The data set used is the blood donor data set downloaded from the repository belonging to the University of California, Irvine (UCI). The Waikato Environment for Knowledge Analysis (WEKA) tool was chosen to present the results of training development and model testing. The research framework scheme is used as a reference for knowledge flow. In scenario 1, data pre-processing includes handling missing values using mean-impulse and normalizing MinMax scaling. With a data set that has an inequality ratio of 1:3, the SVM classifier gets an accuracy performance of 76.7%. In scenario 2, post-pre-processing is done by balancing the data using the Synthetic Minority Oversampling Technique (SMOTE). SVM classifier gets 69.8% accuracy performance. Model performance is evaluated using confusion metrics. The gap in recall values for each class is very high in scenario 1 (2.8% and 99.8%). Things are different in scenario 2 (75.6% and 64%). The test results of 748 samples obtained an accuracy of 76.7% for the scenario-1 model and 93.2% for the scenario-2 model. This proves that the balance of data influences the accuracy of the SVM classification model.]]>
<![CDATA[Implementasi Metode Clarke and Wright Savings dalam Penyelesaian Vehicle Routing Problem di PT. Adiguna Gasindo ]]>
<![CDATA[Munir, Misbahul]]>;
<![CDATA[Kurniawan, Muchamad]]>;
<![CDATA[M, Moch. Kalam]]>;
<![CDATA[Setyawati, Indah]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.876
<![CDATA[A vehicle routing problem (VRP) is a problem in finding the most optimal route with the addition of a constraint. PT. Adiguna Gasindo is one of the LPG gas agents who needs help in shipping to agents, the problem is that there is a limit to the amount of LPG cargo that can be transported. In this research, we will solve the LPG delivery problem by optimizing distance and cost. The Clarke and Wright Savings Method, commonly known as the Saving Matrix, will be implemented to complete VRP. In this study, the distance approaches are the nearest insert and nearest neighbor. The test scenarios were carried out using three types of vehicles with different capacities, namely small (225 kg), medium (275 kg), and large (480 kg). The results obtained will be compared with the actual results (routes done) due to validation. From the results of 90 different scenarios, the results obtained by vehicles with large loads are those of vehicles that get the most optimal route in terms of distance and cost. The saving matrix will be more optimal if it is done by adding the nearest insert or nearest neighbor technique.]]>
<![CDATA[Analisis dan Perancangan Antarmuka Aplikasi Wisata Menggunakan Metode User Centered Design (UCD) ]]>
<![CDATA[Purbo, Yevi Septiray]]>;
<![CDATA[Utomo, Fandy Setyo]]>;
<![CDATA[Purwati, Yuli]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.977
<![CDATA[Lampung has many tourist attractions and natural areas that attract the attention of tourists, both domestic and foreign. However, there are still challenges in optimizing Lampung's tourism potential. One of the challenges is limited access to information regarding tourist destinations, accommodation and available activities. Apart from that, coordination between tourists and related parties such as destination managers and tourism services also need to be improved. To overcome this problem, a prototype of the VACALAM (Vacation Lampung) application was designed using Figma with the User-Centered Design (UCD) method. This research aims to increase user comfort and satisfaction in using the Vacalam application and encourage tourists to visit Lampung. In this application there are several features including ticket booking features, tour lists, trending tours, and a list of events in Lampung. The results of this research are user interface designs that follow good design principles, including simplicity, consistency, and readability. The use of colors, typography, and icons are also considered to improve the clarity and visual appearance of the application. The good user interface design and user experience have been tested using the System Usability Scale (SUS), with a final score of 71.75. These results provide guidance for other application developers in designing engaging and responsive user interfaces and user experiences using Figma.]]>
<![CDATA[Rancang Bangun Website Lelang Mobil menggunakan Framework Codeigniter 3 pada PT.ABC ]]>
<![CDATA[Surya, Alfin Adi]]>;
<![CDATA[Haromain, Imam]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.1031
<![CDATA[An auction is a public sale of goods by oral or written bidding to achieve the highest price. PT.ABC is an auction company engaged in car auctions. PT.ABC is still using conventional methods for auction activities. The conventional system has several disadvantages, including manual recording, vulnerability to loss, and bidders being required to come to the location to buy auction items. This research builds a car auction website to improve the efficiency of the auction business. The application was built using the CodeIgniter 3 Framework using the MySQL database and web socket technology, Socket.IO. The software development method uses the waterfall method. Data collection was carried out by interview and observation at PT.ABC obtained data on the needs of the online auction system, the flow of car auction activities, and the things participants need to take part in the auction. Application development used a modeling concept, namely UML. The application was tested using a user acceptance test with 5 respondents for the admin and 24 people for the front-end. Evaluation results show that the application is very feasible to use and helps the process of running a business, with results from the questionnaire for the admin website at 93% and the front-end website at 91.67%.]]>
<![CDATA[Klasifikasi Motif Songket Palembang menggunakan Support Vector Machine berdasarkan Histogram of Oriented Gradients ]]>
<![CDATA[Yohannes, Yohannes]]>;
<![CDATA[Al Rivan, Muhammad Ezar]]>;
<![CDATA[Devella, Siska]]>;
<![CDATA[Meiriyama, Meiriyama]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i2.1032
<![CDATA[Songket Palembang is one of the intangible cultural heritages with the domain of traditional craftsmanship and crafts. Songket Palembang has several motifs, including Chinese Flowers, Cantik Manis, and Pulir. Preservation efforts are carried out by providing an understanding of Palembang Songket patterns. This study classified Palembang Songket patterns based on shape features using the Histogram of Oriented Gradient (HOG) method. Based on the test results of 45 test data images, the HOG method can become a feature in the image classification of Palembang Songket patterns, namely Chinese Flowers, Cantik Manis, and Pulir. The Support Vector Machine (SVM) method is a classification method that can recognize Palembang Songket patterns with RBF, Linear, and Polynomial kernels. The results showed that the RBF kernel was the best kernel that produced an average accuracy value of 88.1%, a precision of 84.1%, a recall of 82.2%, and an f1-score of 82.6%, and the three Palembang Songket patterns tested, it was found that the Palembang Songket patterns that were easiest to classify well were the Cantik Manis patterns for all types of SVM kernels.]]>
