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<![CDATA[Kombinasi Linier Target Data Untuk Regresi Multitarget Menggunakan Principal Component Analysis ]]>
<![CDATA[Yonathan Purbo Santosa]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.516
<![CDATA[Linear regression is a method to predict numbers, a dependent variable (output) based on some independent variables (inputs). The problem with regression is that some data does not fall into linear problems. Based on this problem, RLC was invented to randomly find a correlation between output by projecting the data into the higher dimension. Unfortunately, RLC does not provide ways to inverse the projection, resulting in poor performance results. On top of that, projecting the data into a higher dimension will increase the learning algorithm complexity. Consequently, PCA can solve the problems by projecting the target data into a lower dimension while leaving possibilities for inverse transformation. This research was implemented with the help of the sci-kit-learn library to create and train the regression model and transform the dataset using Python programming language. As a result, for 12 datasets, augmentation using PCA achieved lower error in 7 datasets than RLC, averaging at 0.3270 for augmentation using PCA and 0.4003 for augmentation using RLC.]]>
<![CDATA[Sistem Klasifikasi Karakter Kepribadian Siswa Sekolah Dasar berdasarkan Tipologi Hippocrates Galenus menggunakan Metode Naïve Bayes ]]>
<![CDATA[Muhammad Sabri]]>;
<![CDATA[Dedy Kasriadi]]>;
<![CDATA[Irsal Irsal]]>;
<![CDATA[Suci Ramadhani Arifin]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.577
<![CDATA[Schools must shape students' personalities through learning activities and programs that can make students become educated human beings with noble characters as the nation's next generation. Teachers as educators need to recognize students' character to develop more effective teaching methods. So far, the guidance process by teachers at SD Inpres 12/79 Palattae has been carried out face-to-face, namely by talking directly to students and carried out without knowing the student's character. As a result, the guidance and counseling that is carried out are sometimes ignored by students. Based on these circumstances, this research was then carried out to build an information system that implements the Naïve Bayes method in elementary school students' personality character classification system based on the Hippocrates-Galenus typology to know the personality types possessed by students. With this system, the teacher can assist in knowing the personality types possessed by students so that it makes it easier to build the mindset, attitude, and behavior of students so that they become positive, good-natured, noble-spirited, and responsible individuals.]]>
<![CDATA[Sistem Informasi Pelayanan Surat Menyurat Di Kelurahan Desa Sriwijaya Lampung Tengah ]]>
<![CDATA[Andronias Siregar]]>;
<![CDATA[Arief Satriansyah]]>;
<![CDATA[Rachmat Hidayat]]>;
<![CDATA[Maya Septa Wijaya]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.588
<![CDATA[Information technology has progressed quite rapidly, and more and more years are increasingly developing technology worldwide. Information technology greatly benefits the world government by creating village websites and building computer-based information systems. With information technology, everyone can process and access data and information they want to convey to the whole community through the website so that everyone can access it easily without having to come and ask the staff or person concerned. The problem with the mailing service in the Village of Sriwijaya Village, Central Lampung, where the process of making letters is still done manually, there are still writing errors. The purpose of creating this correspondence information system is to overcome existing problems and help employees and staff make it easier to update village and community development information by easily accessing this information; with this system, staff can also improve skills in information technology. The method used by the waterfall in making this information system includes making correspondence and information systems in the Sriwijaya village, using the PHP program and MYSQL database. The results of this study are a web-based correspondence information system that is very helpful for community services in making certificates, KK, KTP, SKU, and more quickly and saves time.]]>
<![CDATA[Progressive Web Apps: Pengembangan dan Studi Penerimaan pada Mahasiswa Indonesia Menggunakan Scrum dan UTAUT ]]>
<![CDATA[Herman Herman]]>;
<![CDATA[Frederick Frederick]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.603
<![CDATA[Currently, the usage of mobile applications and the total activity on mobile phones through web browsing or native applications is very high. Most users use native mobile apps to browse the content of specific industries. Another way to do so is through a web browser. However, both have limitations. In web applications, users' experience is not that great compared to native applications. On mobile native applications, it requires higher development costs to ensure the app can be accessed across multiple platforms. To solve this problem, Google launched progressive web apps as an alternative, where progressive web apps can be accessed through different platforms, saving development costs but still providing a user experience almost the same as native apps. The focus of this research is to develop a progressive web app with React.js using the scrum method and also to research user acceptance of progressive web apps through qualitative methods/interviews based on the UTAUT research model to general students and lecturers of computer science. The result of this research, based on UTAUT points, shows positive responses toward accepting progressive web apps. Then with the rapid development of the web and browsers, progressive web apps will potentially have a promising future. With this research, it is hoped that can bring benefits to the decision to use the progressive web apps, become a reference for the next research, and increase the knowledge of the public and readers about the progressive web apps.]]>
<![CDATA[Perbandingan Model Machine Learning pada Klasifikasi Tumor Otak Menggunakan Fitur Discrete Cosine Transform ]]>
<![CDATA[Simeon Yuda Prasetyo]]>;
<![CDATA[Ghinaa Zain Nabiilah]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.605
<![CDATA[Brain tumors are abnormal tissue growths characterized by excessive cell growth in certain brain parts. One of the reliable techniques currently available to identify brain tumors is using Magnetic Resonance Imaging (MRI) scans. The scanned MRI images are monitored and examined for tumor detection by a specialist. Developing more effective and efficient tools to help medical professionals identify brain tumors is urgent as the number of people suffering from brain tumors soars, and the death rate will reach 18,600 in 2021. In previous research, machine learning-based models demonstrated the ability to detect brain tumors with a classification accuracy of 92%, and this result is reliable. We computationally tested several hyperparameters using publicly available MRI datasets to obtain the most reliable binary classification accuracy in MRI brain images. A high level of model accuracy is achieved by testing various existing machine-learning model architectures and inserting a feature map extracted from the Discrete Cosine Transform (DCT). Classification of MRI images achieved the highest accuracy on test data at 93% using the Support Vector Machine (SVM) model.]]>
<![CDATA[Analisis Text Mining Klasifikasi Kegiatan Keluarga menggunakan Orange dengan Metode Naive Bayes ]]>
<![CDATA[Arsya Fathiarahma]]>;
<![CDATA[Apriade Voutama]]>;
<![CDATA[Taufik Ridwan]]>;
<![CDATA[Nono Heryana]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.606
<![CDATA[The dual roles performed by women often lead to conflict in the family. Disputes can occur due to the lack of family roles in helping balance the work at home and office experienced by career women and mothers. The Naïve Bayes algorithm is used in this study to determine the results of applying the Naïve Bayes algorithm classification based on role, activity, age, and interest in a family. A total of 287 data records generated from the survey were used in this study and a data split of 80:20 for training and testing data using orange data mining tools. The results show that the calculation accuracy with the Naïve Bayes algorithm reaches 93%, with the conclusion that the use of orange data mining tools results in good accuracy.]]>
<![CDATA[Analisis Sentimen Ulasan Aplikasi MyPertamina pada Google Play Store menggunakan Algoritma NBC ]]>
<![CDATA[Rihan Maulana]]>;
<![CDATA[Apriade Voutama]]>;
<![CDATA[Taufik Ridwan]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.609
<![CDATA[The MyPertamina application is a digital service application from Pertamina with various services initiated and created to carry out purchases in vehicle fuel transactions. The existence of the MyPertamina application made by PT Pertamina caused reactions and criticism from some application users. Each user has various opinions about the MyPertamina application, as evidenced by the different star ratings in Google Play Store reviews. This study aims to determine the sentiments of MyPertamina application users, which are divided into two classes, namely positive and negative. The dataset in this study uses scraping results from user reviews on the Google Play Store. The data taken to carry out sentiment analysis is from 1 July 2022 to 31 July 2022, and the dataset is taken randomly. The dataset is classified by rating: ratings 4 and 5 as positive sentiment and ratings 1, 2, and 3 as negative sentiment. In this study, Google Colab tools will be used using Python programming. The dataset used is 5722 data labeled positive and negative, with the division of training data by 80% and test data by 20%. The MyPertamina application sentiment analysis results tend to be hostile towards using the application. This study used classification with the Naïve Bayes Classifier (NBC) algorithm. By using the Naïve Bayes Classifier algorithm, it produces 87% accuracy, 86% precision, 90% recall, and 87% f1-score.]]>
<![CDATA[Pengembangan Aplikasi Emoticon Recognition dan Facial Recognition menggunakan Algoritma Local Binary Pattern Histogram (LBPH) dan Convolutional Neural Network (CNN) ]]>
<![CDATA[Haeruddin Haeruddin]]>;
<![CDATA[Herman Herman]]>;
<![CDATA[Patrick Pratama Hendri]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.613
<![CDATA[In the current modern era facial recognition technology can be found inside of everyday life, but said technology still has a big problem which is deepfake, where in which a deepfake can bypass security systems created with facial recognition as its base, one facial aspect that a deepfake cannot replicate perfectly is the emotion that can be observed from expression, which is why an emotion can be used as a tool to detect a deepfake, which is why an application that can detect both face and emotion at the same time is needed to add security to facial recognition technology, writer has succeeded in creating an application that can do both emotion recognition and facial recognition at the same time using LBPH (Local Binary Pattern Histogram) algorithm and purposive sampling technique for the facial recognition aspect with 67.5% accuracy and CNN (Convolutional Neural Network) algorithm using FER2013 (Facial emotion Recognition 2013) dataset for the emotion recognition aspect with 58.4% accuracy, with CRISP-DM method that can achieve the average accuracy rate of 63%, because currently not many research combine facial recognition using LBPH (Local Binary Pattern Histogram) algorithm and emotion recognition using CNN (Convolutional Neural Network) algorithm at the same time.]]>
<![CDATA[Design System pada Perancangan Antarmuka Perangkat Lunak Sistem Akses Digital ]]>
<![CDATA[Apriansyah Rizqi Setiawan]]>;
<![CDATA[Marsani Asfi]]>;
<![CDATA[Agus Sevtiana]]>;
<![CDATA[Sudadi Pranata]]>;
<![CDATA[Willy Eka Septian]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.619
<![CDATA[In developing software systems, there were no rules for making interface patterns in web base applications. The problem is the inconsistency of design styles between software, and the interface design development process takes a long time. This study aims to produce a design framework called Access Digital Design System. The system development method approach used in this research is Atomic Design which has several stages adapted to the investigation. In this study, the design system built is limited to product elements consisting of functional patterns and perceptual patterns. This research will produce a design system made up of perceptual and available marks as output artifacts in the form of code libraries, style guides, and pattern libraries. Based on the study, the designed Design System can reduce time spent creating user interface designs by using component guidelines and documentation with standardized foundation elements to increase productivity. Additionally, the final interface design becomes more consistent and uniform.]]>
<![CDATA[Pengaruh Pemasaran Media Sosial terhadap Keterlibatan Pelanggan (Survei pada Pengguna Halodoc di Indonesia) ]]>
<![CDATA[Alif Ridha Ramadhani]]>;
<![CDATA[Mochamad Ardan Fauzi]]>;
<![CDATA[Muhammad Mufti Abdullah]]>;
<![CDATA[Syti Sarah Maesaroh]]>;
<![CDATA[Oding Herdiana]]>
<![CDATA[ Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023 ]]>
Publisher : <![CDATA[LPPM STT Terpadu Nurul Fikri ]]>
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DOI: 10.54914/jtt.v9i1.622
<![CDATA[This study was conducted to obtain information about the magnitude of the influence of social media marketing on customer engagement. Social media marketing (X) is the independent variable, and customer engagement (Y) is the dependent variable in this study. Followers on the Halodoc Instagram account were selected to be the population in this study, and the sample was taken randomly (simple random sampling), with 120 respondents successfully obtained. The SEM method is used to analyze data with the help of IBM SPSS AMOS 21 software for Windows in the data processing. The results of data processing illustrate that there is an influence of social media marketing on customer involvement of (0.931) with a p-value (0.002) <0.05. Artificial Intelligence-Analitycs for social media is a tool for efforts to increase the competitiveness of official Instagram managers for a business against competitors owned by analyzing content optimization through various services in the form of statistics and metrics from Artificial Intelligence-Analitycs providers, which are generally website-based. The author's recommendation for Halodoc is to increase closeness with customers so that their bonds become stronger through planning content that is useful for the community and packaged attractively. Later it is hoped that there will be more user-generated content or posting word-of-mouth recommendation comments from customers to other customers.]]>
