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All Journal Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication MDP Student Conference
Yoannita, Yoannita
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Other

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Perangkat Lunak Pengenalan Jenis Roti Pada Toko Roti Dengan Menggunakan Model Deteksi Objek Yolov8 Putra, Ronaldo; Yoannita, Yoannita
MDP Student Conference Vol 3 No 1 (2024): The 3rd MDP Student Conference 2024
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v3i1.7625

Abstract

Bakery shop is a business entity in the Food & Beverage sector that sells various types of sweet bread. The diversity of bread types poses a challenge for cashiers in recognizing one type of bread from another, leading to input errors in the cashier's computer. This research explores the use of YOLOv8 object detection to effectively identify different bread types. The dataset consists of 507 samples, including 164 Sosis Keju Brs, 157 Kulit Nangka Coklat, 103 Flosy Chicken, 75 Pizza Mini, and 80 Pizza Brs, trained over 100 epochs, resulting in a mean average precision (mAP) of 0.92%. The detection model performs well in recognizing bread types; however, it has some limitations, particularly when the bread is separated and not stacked on top of each other. A cashier software based on computer vision is also developed to assist cashiers in conducting transactions without the need for individual input.
Transfer Learning dengan MobileNetV3 untuk Deteksi Serangan Spoofing Wajah pada Foto Krisna Putra, Jelvin; Yoannita, Yoannita
Jurnal Algoritme Vol 5 No 2 (2025): April 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i2.10954

Abstract

Deteksi serangan spoofing wajah menjadi tantangan dalam teknologi pengenalan wajah, terutama pada sistem presensi karyawan yang rentan terhadap penyalahgunaan, seperti penggunaan foto untuk memalsukan kehadiran. Penelitian ini mengembangkan metode deteksi spoofing berbasis transfer learning dengan memanfaatkan arsitektur MobileNetV3, yang dirancang untuk efisiensi pada perangkat dengan keterbatasan sumber daya, seperti perangkat seluler. Model yang dikembangkan dilatih menggunakan dataset dengan pembagian rasio 70:15:15 untuk pelatihan, validasi, dan pengujian, menggunakan pendekatan supervised learning. Hasil eksperimen menunjukkan bahwa varian MobileNetV3-Large dengan teknik fine-tuning, yang dilakukan dengan membuka kembali lapisan setelah lapisan ke-130, mampu mencapai akurasi 99,58% pada data pelatihan, 99,94% pada validasi, dan 99,77% pada pengujian. Selain itu, model ini memperoleh HTER sebesar 0,002254791432, yang menunjukkan efektivitas tinggi dalam mengidentifikasi serangan spoofing wajah.
Implementasi Sistem Informasi Kehadiran Karyawan di PT Anugerah Alam Konstruksi Maximilliano, Wesley; Krisna Putra, Jelvin; Yoannita, Yoannita
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.10956

Abstract

PT Anugerah Alam Konstruksi faces challenges in employee attendance recording, which is still done manually, where field workers submit photos via WhatsApp, while office staff attendance is recorded directly by the admin. This method results in disorganized attendance data and requires more time for processing. To address this issue, an Android and web-based Employee Attendance Information System was designed and developed. This study employs an iterative method, allowing system development to be carried out in stages through multiple cycles. The stages include requirements analysis, system design using an Entity Relationship Diagram (ERD), implementation using Dart for the Android application and PHP for the web administration, as well as system testing and evaluation. The Android application enables employees to clock in based on predefined time and location, while the web-based system facilitates admins in managing, verifying, and compiling attendance reports. The implementation of this system is expected to enhance operational efficiency and company productivity through more accurate and organized attendance recording.
CLASSIFICATION OF AMERICAN SIGN LANGUAGE USING SCALE INVARIANT FEATURE TRANSFORM FEATURES AND ARTIFICIAL NEURAL NETWORKS Alviando, Muhammad Restu; Al Rivan, Muhammad Ezar; Yoannita, Yoannita
Jurnal Algoritme Vol 1 No 1 (2020): Oktober 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (918.03 KB) | DOI: 10.35957/algoritme.v1i1.403

Abstract

American Sign Language (ASL) is a sign language in the world. This study uses the neural network method as a classification and the scale invariant feature transform (SIFT) as feature extraction. Training data and test data for ASL images were extracted using the SIFT feature, then ANN training was conducted using 17 training functions with 2 hidden layers. There are architecture used [250-5-10-24], [250-5-15-24] and [250-15-15-24] so there are 3 different ANN architectures. Each architecture is performed 3 times so that there are 9 experiments (3 x 3 trials run the program). Determination of the number of neurons concluded by the training function is selected by the best test results on the test data. Based on the training function and the extraction of SIFT features as input values ​​in the neural network it can be concluded that from 17 training functions, trainb with neuron architecture [250-5-10-24] becomes the best training function producing an accuracy value of 95%, precision of 15 % and recall 5%.
Perancangan Aplikasi Simulasi Penyelamatan Diri Dari Gempa Bumi Marzali, Azizurrahman; Udjulawa, Daniel; Yoannita, Yoannita
Jurnal Algoritme Vol 1 No 2 (2021): April 2021 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (958.577 KB) | DOI: 10.35957/algoritme.v1i2.892

Abstract

Menurut The World Risk Index tahun 2019, Indonesia berada pada peringkat 37 dari 180 negara paling rentan bencana. Pada tanggal 5 Agustus 2018 gempa bumi di Lombok menelan korban sebanyak 259 orang meninggal dunia, dan 1.033 mengalami luka berat. Kurangnya kesiap siagaan dan edukasi mengenai bencana gempa bumi menjadi salah satu faktor penyebab banyaknya jumlah korban. Maka dari itu dibuatlah sebuah aplikasi simulasi yang ditujukan untuk mengedukasi masyarakat supaya dapat mengetahui apa saja yang harus dilakukan pada saat terjadi gempa bumi. Aplikasi ini dibuat menggunakan metode prototyping untuk melakukan identifikasi masalah yang ada pada setiap kejadian gempa bumi. Tujuan dari pembuatan aplikasi ini adalah untuk memberikan pengetahuan tentang bagaimana cara menyelamatkan diri dari gempa bumi. Aplikasi ini berbentuk game yang mempunyai sudut pandang First Person yang mempunyai empat stage dan setiap stage mempunyai beberapa misi. Pemain harus menyelesaikan seluruh misi pada setiap stage agar dapat melanjutkan ke stage selanjutnya. Hasil dari penelitian ini yaitu menghasilkan sebuah aplikasi simulasi dalam cara menyelamatkan diri dari gempa bumi. Berdasarkan uji Black-Box yang telah dilakukan, diperoleh hasil uji coba bahwa aplikasi ini dapat dijalankan dengan baik dan sesuai dengan tujuan.
Klasifikasi Ras Anjing Berdasarkan Citra Menggunakan Convolutional Neural Network Leovincent, Axel; Yoannita, Yoannita
Jurnal Algoritme Vol 3 No 2 (2023): April 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.3389

Abstract

Dogs are mammals that are much loved and kept. Dogs have 355 breeds worldwide. Each race has its own differences, but in certain races have little or almost similar differences. This study classifies 120 dog breeds using the Convolutional Neural Network (CNN) with the ResNet-50 architectural model and the Adam optimizer. The dataset used consists of 20580 images. The dataset is divided into training data, validation data, and test data with a ratio of 60:20:20. The resolution image is 224x224 pixels in size. In this study, it yielded an accuracy of 99,35%.
Pelatihan Desain Grafis Untuk Para Siswi MA Muqimus Sunnah Palembang Pratama, Dicky; Alamsyah, Derry; Gasim, Gasim; Elizabeth, Triana; Yoannita, Yoannita; Tinaliah, Tinaliah
FORDICATE Vol 1 No 1 (2021): November 2021
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.917 KB) | DOI: 10.35957/fordicate.v1i1.1622

Abstract

Community service activity in the form of providing training wereheld on Friday, July 5, 2019 at the MA Muqimus Sunnah School inPalembang. This training aims to conduct graphic design training usingAdobe Photoshop application for 25 students to improve their knowledge inpractice about how to create two dimensional design using Adobe Photoshopapplication such as logo design, poster design, and photo editing. This activityinclude substantial information of the activity, followed by demonstrations inpracticing the application to create designs and testing activities to know howmuch the students can understand the training materials that have beenprovided. At practical session on designing logo and poster, participants weregiven guidance on concepts of how to make good logo such as in choosingcolors, shapes, sizes, and letters or numbers used on logo, The results of thetraining show the students can understand and use tools in Adobe Photoshopapplication to add and organize text, cut and move images, students cancreate logos, posters, and edit images/photos using Adobe Photoshopapplications.
Pelatihan Penggunaan Aplikasi WhatsApp Business Sebagai Media Pemasaran Online pada Toko CCTV Grosir Cabang Palembang Elizabeth, Triana; Alamsyah, Derry; Yoannita, Yoannita
FORDICATE Vol 1 No 2 (2022): April 2022
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (948.352 KB) | DOI: 10.35957/fordicate.v1i2.2409

Abstract

Toko CCTV Grosir Palembang merupakan salah satu toko yang menjual cctv dan menyediakan jasa pemasangan serta perawatan cctv di kota Palembang yang merasakan dampak dari penyakit Covid19. Kekhawatiran akan penyebaran penyakit Covid-19 membuat pemasukan baik dari segi penjualan dan penyediaan jasa pemasangan serta perbaikan cctv menurun. Selain itu, dikarenakan pembatasan oleh pemerintah setempat membuat pelanggan kesulitan jika harus datang langsung ke toko untuk membeli barang. Oleh sebab itu, dibutuhkan sarana baru selain telepon atau datang langsung ke toko sebagai sarana komunikasi dengan pelanggan. Pengabdian ini dilakukan melalui pengadaan pelatihan singkat aplikasi WhatsApp Business beserta fiturfiturnya seperti katalog produk, label, away message, broadcast message, dll. Setelah penggunaan aplikasi WhatsApp Business selama 6 bulan ditemukan peningkatan penjualan berdasarkan produk yang dipromosikan melalui fitur katalog dan broadcast message
Co-Authors Alviando, Muhammad Restu Athar, Muhammad Farid Azarya, Philips Denny Daniel Udjulawa Derry Alamsyah Dicky Pratama gasim, Gasim Krisna Putra, Jelvin Leovincent, Axel M Ezar Al Rivan Marzali, Azizurrahman Maximilliano, Wesley Pandi Pandi, Pandi Putra, Ronaldo Timoti, Gerry Jeven Tinaliah, Tinaliah Triana Elizabeth, Triana Wiwik Handayani Yohannes Yohannes