Jurnal Terapan Teknologi Informasi
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Penelitian Artificial Intelligence untuk Satelit Komunikasi menggunakan Jaringan Syaraf Tiruan (JST)
Get PDFSatellite Communications offers the promise of periodic continuous service in uncovered and covered areas, with service scalability. However, several issues must be addressed first to realize these benefits, such as resource management, network control, network security, spectrum management, and satellite energy usage are more difficult compared to terrestrial networks. Meanwhile, artificial intelligence (AI), which includes deep machine learning, and security learning continues to grow as a research field and has shown a wide range of results in various applications, including wireless communications. In particular, the application of AI to various aspects of satellite communications is showing excellent potential, including beam- hopping, anti-jamming, network traffic forecasting, channel modeling, telemetry mining, ionospheric scintillation detection, interference management, remote sensing, behavioral modeling, space-air-ground integration, and energy management. This work provides an overview of AI and its diverse sub-fields, and modern algorithms. Some of the problems encountered in various aspects of satellite communication systems are discussed, and proposed and potential AI-based solutions are presented. Finally, an outlook on the field is described, with future steps expected.Satelit Komunikasi menawarkan harapan berkelanjutan secara berkala pada layanan area yang belum dan sudah terjangkau, dengan skalabilitas layanan. Namun, beberapa masalah harus diatasi terlebih dahulu untuk merealisasikan manfaat ini, seperti manajemen sumber daya, kontrol jaringan, keamanan jaringan, manajemen spektrum, dan penggunaan energi satelit lebih sulit dibandingkan dengan jaringan terestrial. Sementara itu, kecerdasan buatan (AI), adalah termasuk pembelajaran mesin yang mendalam, dan pembelajaran keamanan terus berkembang, sebagai bidang penelitian dan telah menunjukkan hasil yang berbagai macam dalam berbagai aplikasi, termasuk komunikasi nirkabel. Secara khusus, penerapan AI pada berbagai aspek komunikasi satelit yang menunjukkan potensi sangat baik, termasuk beam- hopping, anti-jamming, peramalan lalu lintas jaringan, pemodelan saluran, penambangan telemetri, pendeteksian kilau ionosfer, pengelolaan interferensi, pengindraan jarak jauh, pemodelan perilaku, pengintegrasian ruang-udara-darat, dan pengelolaan energi. Karya ini memberikan gambaran umum tentang AI dan sub-bidangnya yang beragam, dan algoritma modern. Beberapa masalah yang dihadapi dalam berbagai aspek sistem komunikasi satelit yang dibahas, dan solusi berbasis kecerdasan buatan yang diusulkan dan solusi berbasis kecerdasan buatan yang potensial disuguhkan. Akhirnya, sebuah pandangan tentang bidang ini digambarkan, dengan langkah-langkah di masa depan yang diharapkan
Analisis Penghematan Daya Listrik dengan Implementasi FX-80 Supervisor Controller pada Sistem Water Chiller
Get PDFThis research aims to analyze electrical power consumption and cooling system efficiency between the FX-80 Supervisor Controller and a system without a controller in the field. Measurements are carried out for one year by taking data on electrical power consumption and Coefficient of Performance (COP) every month. The research results show that the system with the FX-80 Supervisor Controller consumes lower electrical power and has a higher COP than the system without the controller. The higher efficiency of systems with controllers represents significant energy savings potential for companies. This research recommends the use of controllers in cooling systems to increase energy efficiency.Penelitian ini bertujuan untuk menganalisis konsumsi daya listrik dan efisiensi sistem pendingin antara FX-80 Supervisor Controller dan sistem tanpa kontroler di lapangan. Pengukuran dilakukan selama satu tahun dengan mengambil data konsumsi daya listrik dan Coefficient of Performance (COP) setiap bulan. Hasil penelitian menunjukkan bahwa sistem dengan FX-80 Supervisor Controller mengonsumsi daya listrik lebih rendah dan memiliki COP lebih tinggi dibandingkan sistem tanpa kontroler. Efisiensi yang lebih tinggi pada sistem dengan kontroler menunjukkan potensi penghematan energi yang signifikan bagi perusahaan. Penelitian ini merekomendasikan penggunaan kontroler dalam sistem pendingin untuk meningkatkan efisiensi energi
Penerapan Framework Rasa untuk Membangun Sistem FAQ Bot Sebagai Layanan Informasi BIRO 3
Get PDFDuta Wacana Christian University (UKDW), specifically Bureau 3 (BIRO 3), provides a variety of information services accessible through both online channels, such as Instagram, WhatsApp, and email, and offline methods. However, BIRO 3 has not yet implemented an FAQ Bot system, which means that frequently asked questions are still answered manually. This practice renders the question-and-answer process regarding campus information repetitive and time-consuming. This research aims to implement the RASA Open Source framework to develop an FAQ Bot system to automate the retrieval of information for frequently asked questions at BIRO 3, thereby enhancing the efficiency of its information services.
The system was developed using RASA Open Source and implemented on the Telegram messaging platform. The evaluation was conducted through a two-fold approach. First, internal testing of the RASA model on the validation dataset yielded optimal results, achieving accuracy, precision, and F1-scores of 1.000. On the test data, the model demonstrated strong performance with an accuracy of 0.915, a precision of 0.928, and an F1-score of 0.912. Second, functional testing was performed by engaging users in predefined scenarios. This second phase of testing resulted in a functional accuracy of 95% based on 200 collected data points.
The user testing results indicate that the FAQ Bot system was successfully developed and capable of achieving a functional accuracy rate of 95%. Despite its high performance, limitations were identified in the form of eleven false positive and false negative cases out of the 200 data points. This suggests that the model has not yet perfectly learned to comprehend all variations of user input. Therefore, recommendations such as expanding the training dataset and exploring modifications to the RASA Open Source framework are proposed to refine the system\u27s capabilities, enabling it to handle all types of inquiries accurately.Universitas Kristen Duta Wacana(UKDW), khususnya BIRO 3 memiliki berbagai layanan informasi yang dapat diakses baik secara online seperti Instagram, whatsapp, Email maupun offline. Namun saat ini BIRO 3 belum mengimplementasikan sistem FAQ Bot, sehingga pertanyaan yang sering diajukan masih dijawab secara manual. Hal ini membuat aktivitas tanya jawab mengenai informasi kampus menjadi repetitif dan memakan waktu. Penelitian ini bertujuan untuk menerapkan RASA Open Source untuk mengembangkan sistem FAQ Bot guna mempermudah pencarian informasi terkait pertanyaan yang sering ditanyakan di BIRO 3 secara otomatis serta meningkatkan efisiensi layanan informasi.
Sistem dikembangkan dengan RASA Open Source dan diimplementasikan pada antarmuka Telegram. Evaluasi dilakukan melalui dua pendekatan. Pertama, pengujian internal model RASA menunjukkan hasil optimal pada data validasi dengan nilai akurasi, presisi, dan skor-F1 mencapai 1.000. Pada data uji (test data), model menunjukkan performa yang kuat dengan akurasi 0.915, presisi 0.928, dan skor-F1 0.912. Kedua, pengujian fungsional dilakukan dengan melibatkan pengguna melalui skenario. Hasil pengujian kedua mendapatkan akurasi sebesar 95% dari 200 data yang dikumpulkan
Hasil pengujian pengguna menunjukkan bahwa sistem FAQ Bot berhasil dikembangkan dan mampu mencapai tingkat akurasi fungsional sebesar 95%. Meskipun performanya tinggi, masih ditemukan kelemahan berupa sebelas kasus false positive dan negative dari 200 data, yang mengindikasikan bahwa model belum sempurna dalam memahami semua variasi input. Oleh karena itu, saran seperti penambahan data latih dan eksplorasi modifikasi framework RASA Open Source direkomendasikan untuk menyempurnakan kemampuan sistem agar dapat menangani seluruh jenis pertanyaan secara akurat
Pembuatan Sistem Penerimaan Peserta Didik Baru SMP Maria Immaculata Berbasis Website
Get PDFThe research aims to develop a student admission system for Maria Immaculata Junior High School to improve the current inefficient process relying on Google Forms and manual document submission. In This Article, The waterfall methodology will be employed for system development, while questionnaires and usability testing will be used for user evaluation then using through questionnaires and usability testing. The research will involve PPDB (Penerimaan Peserta Didik Baru) staff and parents as respondents. Initial requirements will be gathered through observation and interviews with PPDB committee members. After analysis, the system\u27s database and user interface will be designed and implemented. Testing will be conducted with PPDB staff to obtain feedback and make necessary improvements who can impacted to School or programs. Finally, the system will be deployed for public use. The system\u27s usability was evaluated through questionnaires and usability testing. The results indicate high levels of ease of use, ease of learning, usefulness, and satisfaction, with an overall usability score of 83%. This suggests that the developed system is effective and well-received by users.Penelitian ini bertujuan untuk mengembangkan sistem pendaftaran siswa untuk SMP Maria Immaculata Junior High School guna meningkatkan proses pendaftaran yang saat ini tidak efisien, yang masih bergantung pada Google Forms dan pengajuan dokumen secara manual. Dalam artikel ini, metodologi Waterfall akan digunakan untuk pengembangan sistem, sedangkan kuesioner dan pengujian kegunaan akan digunakan untuk evaluasi pengguna lalu dipergunakan juga untuk metode through questionnaires and usability testing. Penelitian ini akan melibatkan staf PPDB (Penerimaan Peserta Didik Baru) dan orang tua sebagai responden. Persyaratan awal akan dikumpulkan melalui observasi dan wawancara dengan anggota komite PPDB. Setelah analisis, database dan antarmuka pengguna sistem akan dirancang dan diimplementasikan. Pengujian akan dilakukan dengan staf PPDB untuk mendapatkan umpan balik dan melakukan perbaikan yang diperlukan yang dapat berdampak pada sekolah atau program. Akhirnya, sistem akan diimplementasikan untuk penggunaan publik. Kegunaan sistem dievaluasi melalui kuesioner dan pengujian kegunaan. Hasilnya menunjukkan tingkat tinggi dalam kemudahan penggunaan, kemudahan belajar, kegunaan, dan kepuasan, dengan skor kegunaan keseluruhan sebesar 83%. Hal ini menunjukkan bahwa sistem yang dikembangkan efektif dan diterima dengan baik oleh pengguna
Perancangan Aplikasi Website Pengelolaan Surat Masuk dan Keluar Dengan Menggunakan Metode Design Thinking Studi Kasus: Rektorat UKDW
Get PDFLetters are one of the most common forms of communication in people\u27s daily lives. Activities related to letters are commonly referred to as correspondence. Duta Wacana Christian University Yogyakarta is one of the institutions where correspondence activities are still carried out for internal organizational purposes Initially, correspondence activities at UKDW were still done manually by using physical letters, which were sent to the intended address by asking people to deliver them directly. However, the correspondence process is becoming less efficient. The process that must be passed is quite long, so it takes a lot of time and energy.
This incoming and outcoming lettters management website was designed to help and facilitate UKDW employees in carrying out correspondence activities, which were formerly performed manually, through the use of a website. This research uses design thinking as the design method. The Design Thinking method consists of several steps: Empathize, Define, Ideate, Prototype, and Testing. For the testing phase, the author uses the Usability Testing as a method to evaluate the effectiveness, efficiency, and user satisfaction of the website.Surat merupakan salah satu media komunikasi yang sampai saat ini masih umum digunakan dalam kehidupan manusia sehari-hari. Kegiatan yang berkaitan dengan surat biasa disebut dengan surat menyurat. Universitas Kristen Duta Wacana Yogyakarta menjadi salah satu tempat di mana masih melangsungkan kegiatan surat menyurat untuk kepentingan internal organisasinya. Awalnya, kegiatan surat menyurat di UKDW masih dilakukan secara manual dengan menggunakan surat fisik dan mengirimkan surat tersebut kepada alamat yang dituju dengan meminta orang mengirimkan langsung. Namun, semakin hari proses surat menyurat ini dirasa sudah mulai tidak efisien lagi. Proses yang harus dilalui pun tergolong cukup panjang sehingga memakan banyak waktu dan tenaga.
Perancangan website pengelolaan surat masuk dan keluar ini dilakukan untuk membantu dan mempermudah para staff di UKDW dalam melakukan aktivitas surat menyurat, yang semula dilakukan secara manual diubah pelaksanaannya dengan digunakan sistem website. Dalam penelitian ini digunakan metode Design Thinking sebagai metode perancangannya. Metode Design Thinking terdiri dari beberapa langkah yaitu Emphatize, Define, Ideate, Prototype dan Testing. Untuk tahap testing penulis menggunakan metode Usability Testing sebagai metode pengujian efektivitas, efisiensi serta pengujian tingkat kepuasan pengguna.
Optimasi Akurasi Koefisien Pajak Kendaraan Bermotor di Indonesia Menggunakan Metode Klasifikasi dan Regres
Get PDFThe growing awareness of the impact of motor vehicle emissions on the environment has encouraged Indonesia’s Ministry of Environment and Forestry to enforce emission testing regulations. These emission standards serve as a basis for calculating Motor Vehicle Tax (PKB). The Transportation Technology Research Center (BRIN) developed a tax coefficient prediction system to support this policy. Initial research utilized Orange Data Mining for machine learning analysis with algorithms like Random Forest, Neural Network, and AdaBoost. However, Orange Data Mining has limitations in flexibility, particularly in parameter tuning and preprocessing data, as well as inefficiencies in handling large datasets. This study adopts a more flexible approach, employing AutoML LazyPredict for quick identification of optimal models and GridSearchCV for hyperparameter optimization. The methodology involves two approaches: classification and regression. Classification employs models such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Extra Tree, and LightGBM, while regression utilizes Support Vector Regressor (SVR) optimized with GridSearchCV. Both approaches enable a comprehensive comparison and analysis of model performance. The results indicate that SVM and Decision Tree excelled in classification, achieving an accuracy of 100%. In regression, the models demonstrated high 16 performance with R² values ranging from 0.95 to 1.00, indicating exceptional predictive accuracy. Evaluations were conducted using metrics such as MAE, MSE, and R² for regression, along with accuracy scores and classification reports for classification tasks. This research underscores the effectiveness of machine learning model optimization, with both analyzed algorithms showing outstanding performance for classification and regression tasks.Peningkatan kesadaran akan dampak emisi kendaraan bermotor terhadap lingkungan mendorong Kementerian Lingkungan Hidup dan Kehutanan Indonesia untuk menerapkan regulasi uji emisi. Nilai standar emisi ini dapat menjadi dasar perhitungan Pajak Kendaraan Bermotor (PKB). Tim Pusat Riset Teknologi Transportasi (BRIN) mengembangkan model prediksi koefisien pajak untuk mendukung kebijakan ini. Penelitian awal menggunakan Orange Data Mining untuk analisis machine learning dengan algoritma seperti Random Forest, Neural Network, dan AdaBoost. Namun, Orange memiliki kelemahan pada fleksibilitas, terutama dalam tuning parameter, preprocessing dataset, serta keterbatasan menangani dataset besar. Dalam penelitian ini, Google Colab digunakan sebagai platform utama untuk memaksimalkan fleksibilitas analisis dan kustomisasi model. Algoritma AutoML LazyPredictditerapkan untuk mengidentifikasi model terbaik secara cepat, sedangkan GridSearchCV digunakan untuk optimasi hyperparameter. Pendekatan pertama adalah klasifikasi menggunakan model seperti Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Extra Tree, dan LightGBM. Pendekatan kedua adalah regresi menggunakan Support Vector Regressor (SVR), yang dioptimalkan dengan GridSearchCV. Kedua metode ini digunakan untuk membandingkan performa model dan menganalisis hasil. Hasil penelitian menunjukkan bahwa SVM dan Decision Treememberikan hasil klasifikasi terbaik dengan akurasi mencapai 100%. Untuk regresi, nilai R² berkisar antara 0,95 hingga 1,00 menunjukkan tingkat akurasi prediksi yang sangat tinggi. Evaluasi dilakukan dengan metrik seperti MAE, MSE, dan R² untuk regresi, 14 serta accuracy score dan classification report untuk klasifikasi. Penelitian ini membuktikan bahwa optimasi model machine learning berhasil, dengan kedua algoritma dianalisa menunjukkan kinerja yang sangat baik untuk klasifikasi dan regresi
Redesain Remote Laboratorium Rumpun Mata Kuliah Jaringan Komputer FTI UKDW dengan Pendekatan Modular
No full textThe implementation of a remotely accessible network laboratory at FTI UKDW commenced in 2022, utilizing a VPN (Virtual Private Network) based remote system. Previous research identified several technical challenges in its implementation, coupled with periodic subscription cost constraints. Consequently, this study aims to redesign the system by adopting port forwarding as an alternative, with the expectation of optimizing the remote laboratory implementation while reducing maintenance costs. This research focuses on analyzing the performance quality of the redesigned remote laboratory using the port forwarding method. Additionally, the study aims to measure the level of comfort among students in using the remote network laboratory system through the collection of questionnaire data. The results of the research indicate that the redesign with the port forwarding method can be implemented as expected. Students expressed a high level of satisfaction, reaching 50%, with the majority finding it easy to access practical tools and considering the system user-friendly.Penerapan laboratorium jaringan yang dapat diakses secara remote di FTI UKDW dimulai pada tahun 2022 dengan menggunakan sistem remote berbasis VPN (Virtual Private Network). Penelitian sebelumnya mengidentifikasi beberapa kendala teknis dalam implementasinya dan menimbulkan kendala biaya berlangganan berkala. Oleh karena itu, penelitian ini memiliki tujuan untuk melakukan perancangan ulang sistem dengan mengadopsi metode port forwarding sebagai alternatif yang diharapkan dapat mengoptimalkan penerapan remote laboratorium sambil mengurangi biaya pemeliharaan. Penelitian ini fokus pada analisis terhadap kualitas performa dari desain remote laboratorium dengan menggunakan metode port forwarding. Selain itu, penelitian juga bertujuan untuk mengukur tingkat kenyamanan mahasiswa dalam menggunakan sistem jaringan remote laboratorium melalui pengumpulan data kuesioner. Dari hasil penelitian, perancangan ulang dengan metode port forwarding dapat diimplementasikan sesuai dengan skenario yang diharapkan. Mahasiswa menunjukkan tingkat kepuasan yang tinggi, mencapai 50%, dengan sebagian besar merasa mudah dalam mengakses alat praktikum dan menilai sistem ini user-friendly
Analisis Perbandingan Moodle dan Google Classroom Menggunakan Technology Acceptance Model
Get PDFThe study aims to analyze the comparison of student acceptance levels of the Learning Management System (LMS) which are Moodle and Google Classroom using the Technology Acceptance Model (TAM) in the West Java region, Indonesia. The results of this study show that there is a difference in the level of acceptance of the two LMSs but the difference is not very significant. Moodle appears to be slightly more effective in increasing student productivity and is more commonly used in West Java due to the sample of respondents who are mostly from the Faculty of Information Technology (FIT) at Maranatha Christian University. FIT students have largely adopted the Moodle LMS implemented into the Morning Platform (Maranatha Online Learning). With more complex features, Moodle meets the needs of more experienced users. On the other hand, Google Classroom is considered easier to use, especially for students who are new to the LMS. However, over a longer period of time, Moodle maintained a slight edge in terms of usability and user satisfaction. This research makes an important contribution in understanding the preferences and needs of university students in terms of LMS usage, especially in the West Java region.The study aims to analyze the comparison of student acceptance levels of the Learning Management System (LMS) which are Moodle and Google Classroom using the Technology Acceptance Model (TAM) in the West Java region, Indonesia. The results of this study show that there is a difference in the level of acceptance of the two LMSs but the difference is not very significant. Moodle appears to be slightly more effective in increasing student productivity and is more commonly used in West Java due to the sample of respondents who are mostly from the Faculty of Information Technology (FIT) at Maranatha Christian University. FIT students have largely adopted the Moodle LMS implemented into the Morning Platform (Maranatha Online Learning). With more complex features, Moodle meets the needs of more experienced users. On the other hand, Google Classroom is considered easier to use, especially for students who are new to the LMS. However, over a longer period of time, Moodle maintained a slight edge in terms of usability and user satisfaction. This research makes an important contribution in understanding the preferences and needs of university students in terms of LMS usage, especially in the West Java region
Penerapan Sistem Rekomendasi Registrasi Mata Kuliah Informatika UKDW
Get PDFEvery time a new academic year begins, the UKDW Informatics study program will provide courses that students can choose when registering. The courses provided are basically divided into compulsory courses and elective courses. Based on these 2 types of courses, for Informatics students, especially in choosing elective courses, it is often adjusted to each student\u27s area of interest. This area of interest is then adjusted to the courses available at the time of registration, however, Informatics students often experience confusion in choosing courses at the time of registration.
Therefore, this research will design a course recommendation system that is used to help recommend courses to UKDW Informatics Students before registering. There are 2 engines used by the system, namely Python and Laravel. Python is used to process recommendations, while Laravel is only used to display recommendations. The recommendation process carried out by Python will use Collaborative Filtering which has processes including collecting data in the form of course rating results, processing similarities between courses for each area of interest, and calculating an evaluation matrix using MAP. Then the results of the highest similarity will be used as criteria for displaying recommendations. The results of the recommendations will then be checked using Laravel, so that each student can have different course recommendations.
The system was tested with 10 test cases in the form of student scenarios from the classes of 2021, 2020 and 2019. The test case results show the courses that students should take, while the evaluation is related to the results of the courses recommended by the system. The testcase evaluation results were stated to have a success rate of 80% based on 8 out of 10 successful testcases. Furthermore, the system has an accuracy level for subjects of interest of 46.36% which is calculated using the Mean Average Precision (MAP) method by averaging based on the precision of 10 testcases. Precision is calculated by comparing the courses in the field of interest that have been recommended with the courses in the field of interest that have been taken in each test case.Setiap tahun ajaran baru dimulai, prodi Informatika UKDW akan menyediakan mata kuliah yang dapat dipilih mahasiswa saat melakukan registrasi. Mata kuliah yang disediakan ini pada dasarnya dibagi menjadi mata kuliah wajib dan mata kuliah pilihan. Berdasarkan 2 macam mata kuliah ini, bagi Mahasiswa Informatika terutama dalam memilih mata kuliah pilihan seringkali disesuaikan dengan bidang minat dari masing-masing mahasiswa. Bidang minat ini yang kemudian disesuaikan dengan mata kuliah yang ada pada saat registrasi, namun walaupun demikian bagi Mahasiswa Informatika sering mengalami kebingungan dalam memilih mata kuliah pada saat registrasi.
Oleh sebab itu penelitian ini akan merancang sebuah sistem rekomendasi mata kuliah yang digunakan untuk membantu merekomendasikan mata kuliah kepada Mahasiswa Informatika UKDW sebelum melakukan registrasi. Terdapat 2 mesin yang digunakan sistem dalam memproses rekomendasi yaitu Python dan Laravel. Proses rekomendasi yang dilakukan oleh Python akan menggunakan Item-Based Collaborative Filtering yang memiliki proses diantaranya mengumpulkan data berupa hasil rating mata kuliah, memproses similarity antar mata kuliah untuk tiap bidang minat, serta menghitung matriks evaluasi dengan menggunakan MAP. Kemudian hasil dari similarity yang paling tinggi akan digunakan sebagai kriteria untuk menampilkan rekomendasi menggunakan Laravel.
Sistem dilakukan uji coba dengan 10 testcase berupa skenario mahasiswa dari angkatan 2021, 2020 dan 2019. Hasil testcase menunjukkan mata kuliah yang seharusnya diambil mahasiswa, sedangkan evaluasi terkait dengan hasil mata kuliah yang direkomendasikan sistem. Hasil evaluasi testcase dinyatakan memiliki tingkat keberhasilan 80% berdasarkan 8 dari 10 testcase yang berhasil. Selanjutnya sistem memiliki tingkat keakuratan untuk mata kuliah bidang minat sebesar 46.36% yang dihitung menggunakan metode Mean Average Precision (MAP) dengan melakukan rata-rata berdasarkan presisi dari 10 testcase. Presisi dihitung dalam dengan cara membandingkan mata kuliah bidang minat yang telah direkomendasikan dengan mata kuliah bidang minat yang telah diambil pada tiap testcase
Sistem Check-In Di Lingkungan Sma Budya Wacana Dengan Memanfaatkan Qr Code Dan Geolokasi
Get PDFTechnology began to develop rapidly at that time. Many tools have been invented to facilitate human work, one of which is the Quick Response Code. QR Codes are two-dimensional matrix codes or barcodes created to allow scanners to respond quickly and receive data quickly. QR Codes can be used to manage the attendance of students, teachers, and school staff. This study defines a QR Code work system for student, teacher, and staff badges to manage student, teacher, and staff activity data and keep track of all students attending school. employee activities. This study uses the Waterfall System Development Life Cycle method. The key component of the system is a webcam scanner that reads QR Codes filled with master keys for student, teacher, and staff data. Attendance plays an important role in all institutions. This can lead to errors on the part of the school or students. For example, inefficient use of paper, absenteeism, missing monthly reports, missing wastepaper, etc. In addition, handwritten attendance carries the risk of absenteeism due to corruption of attendance data, which can lead to carelessness by employees and students.Technology began to develop rapidly at that time. Many tools have been invented to facilitate human work, one of which is the Quick Response Code. QR codes are two-dimensional matrix codes or barcodes created to allow scanners to respond quickly and receive data quickly. QR codes can be used to manage the attendance of students, teachers, and school staff. This study defines a QR code work system for student, teacher, and staff badges to manage student, teacher, and staff activity data and keep track of all students attending school. employee activities. This study uses the Waterfall System Development Life Cycle method. The key component of the system is a webcam scanner that reads QR codes filled with master keys for student, teacher, and staff data. Attendance plays an important role in all institutions. This can lead to errors on the part of the school or students. For example, inefficient use of paper, absenteeism, missing monthly reports, missing wastepaper, etc. In addition, handwritten attendance carries the risk of absenteeism due to corruption of attendance data, which can lead to carelessness by employees and students.
Intisari— Teknologi saat itu mulai berkembang pesat. Telah banyak ditemukan alat untuk mempermudah pekerjaan manusia, salah satunya adalah Quick Response Code. Kode QR adalah kode matriks atau barcode dua dimensi yang dibuat untuk memungkinkan pemindai merespons dengan cepat dan menerima data dengan cepat. Kode QR dapat digunakan untuk mengelola kehadiran siswa, guru, dan staf sekolah. Studi ini mendefinisikan sistem kerja kode QR untuk lencana siswa, guru, dan staf untuk mengelola data aktivitas siswa, guru, dan staf serta melacak semua siswa pergi ke sekolah. aktivitas karyawan. Penelitian ini menggunakan metode Waterfall System Development Life Cycle. Komponen kunci dari sistem ini adalah pemindai webcam yang membaca kode QR yang diisi dengan kunci utama untuk data siswa, guru, dan staf. Kehadiran memainkan peran penting di semua institusi. Hal ini dapat menimbulkan kesalahan dari pihak sekolah atau siswa. Misalnya, penggunaan kertas yang tidak efisien, ketidakhadiran, laporan bulanan yang hilang, dan kertas bekas yang hilang. Selain itu, presensi tulisan tangan memiliki risiko presensi karena rusaknya data presensi yang dapat menimbulka