Article Per Year (5 Year)
p-Index From 2021 - 2026
2.826
P-Index
This Author published in this journals
All Journal Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I) Al-Jabar : Jurnal Pendidikan Matematika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Jurnal Sistem Cerdas dan Rekayasa Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Yohannes Yohannes
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
Implementasi Virtual Reality pada Game Edukasi Protokol Kesehatan Gerry Jeven Timoti; Yohannes Yohannes; Yoannita Yoannita
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4065

Abstract

In the year of 2020 until now has been a tough year for almost all industries and the general public due to the coronavirus pandemic. However, the increase in cases per day illustrates that the community has not complied with health protocols optimally. The impact of the pandemic has increased gamers in Asia by more than 75%. With a positive impact on society, the role of games can be used as a medium for education. Virtual Reality will be implemented in the health protocol educational game to see the good role of virtual reality in educational game interactions. The implementation of Virtual Reality in the health protocol educational game is carried out using the GDLC (Game Development Life Cycle) approach with stages starting from initiation, pre-production, production, testing, and release. The results of the recapitulation of the questionnaire on the acceptance and satisfaction of the health protocol educational game application showed the results of 44,9.% strongly agree, 44,9% agree, 9,15% are neutral and 1% are not agree that the application has functioned well and can be selected as one of the learning media especially about health protocol to reduce the growth rate of people infected with the coronavirus.
Implementasi Algoritma $P Point Cloud Recognizer pada Pengenalan Angka Berbasis Game Muhammad Farid Athar; Yohannes Yohannes; Yoannita Yoannita
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5472

Abstract

More devices use gestures as their input method. Recognizing these gestures becomes more important for app development. One of the methods used for gesture recognition is Point Cloud Recognizer or $P. Gesture recognition can be used to recognize written characters like numbers or letters. Result of this recognition can be used for education involving apps, like games. This study is done by implementing $P in games to show that $P can be used as one of the methods for gesture recognition when developing games that need such features. In this study $P is implemented with the help of the game engine Unity with C# programming language. 3 sets of numerals 1 to 10 are used as data with $P configured to use 32 points. Total of 100 tests are done in the game resulting in 99% accuracy, showing $P is able to recognize the gesture well.
DETEKSI PLAT NOMOR KENDARAAN MENGGUNAKAN METODE YOLOv8 Putra, Lipi Amanda; Yohannes, Yohannes
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11261

Abstract

Motorized vehicles play a crucial role in daily life, making vehicle management and monitoring increasingly necessary. One common issue arises in parking systems, where current systems only capture photos of vehicles and still require manual input of license plate numbers upon vehicle exit. These systems are not yet capable of automatically detecting and recognizing license plates. Therefore, this study aims to design an application for license plate recognition using the YOLOv8 method to automatically and accurately detect license plates. YOLOv8 is a fast and accurate object detection model. The dataset used consists of 764 images of vehicle license plates, divided into 70% training data, 20% validation data, and 10% test data. he results of the study show a detection accuracy with a precision value of 94.3%, recall of 87.3%, and mAP of 95.3%.
Perangkat Lunak Pendeteksi Jenis Seragam Siswa Jenjang Pendidikan Menengah Menggunakan Yolov8 Dody, Muhammad; Yohannes, Yohannes
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11356

Abstract

In a school environment, policies and regulations play a vital role in teaching students discipline, particularly in adhering to uniform rules. School uniforms help instill discipline by requiring students to dress according to the rules, without modifications, and in compliance with set standards. These regulations foster equality among students, reduce social differences, and support character and moral education. However, enforcing uniform policies can pose challenges for schools. Schools need to regularly monitor compliance to ensure every student follows the uniform rules, a process that often requires significant time and effort. To address this issue, this study developed a student uniform detection system using the You Only Look Once Version 8 (YOLOv8) method. YOLOv8 is a convolutional neural network-based object detection method capable of identifying objects in real-time with high accuracy. The aim of this study is to create a system that can automatically detect student uniforms, improve record-keeping accuracy, and reduce excessive time and energy spent monitoring detection results through cameras. The research methodology includes image data collection, YOLOv8 model training, and system testing. The testing results showed that the developed model achieved a precision of 95.%, a recall of 85%, a mean Average Precision (mAP) of 92.2%.
PELATIHAN PENGGUNAAN WORDPRESS UNTUK MEDIA INFORMASI KPCDI PALEMBANG Al Rivan, Muhammad Ezar; Irsyad, Hafiz; Meiriyama, Meiriyama; Yohannes, Yohannes; Devella, Siska; Wijaya, Novan; Rachmat, Nur
FORDICATE Vol 4 No 2 (2025): April 2025
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v4i2.11572

Abstract

Penguasaan teknologi informasi menjadi kebutuhan penting bagi organisasi berbasis komunitas dalam menyebarluaskan informasi secara cepat dan terstruktur. Komunitas Pasien Cuci Darah Indonesia (KPCDI) Palembang membutuhkan sarana digital yang dapat menunjang komunikasi dan edukasi antaranggota. Kegiatan pengabdian ini bertujuan untuk memberikan pelatihan penggunaan WordPress sebagai media informasi komunitas. Pelatihan dilaksanakan di Rumah Sakit RK Charitas Palembang dengan metode ceramah, demonstrasi, dan praktik langsung. Materi pelatihan mencakup pengelolaan konten situs, pengunggahan media, dan pengaturan tampilan dasar website. Peserta dibimbing secara bertahap agar mampu memahami penggunaan platform meskipun berasal dari latar belakang non-teknis. Hasil kegiatan menunjukkan bahwa peserta antusias dan mampu mengikuti alur pelatihan dengan baik. Kegiatan ini diharapkan dapat memperkuat kapasitas digital KPCDI Palembang dalam pengelolaan media informasi secara mandiri dan berkelanjutan
Enhancing Mathematical Problem-Solving Skills of Indonesian Junior High School Students through Problem-Based Learning: a Systematic Review and Meta-Analysis Suparman, Suparman; Yohannes, Yohannes; Arifin, Nur
Al-Jabar: Jurnal Pendidikan Matematika Vol 12 No 1 (2021): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v12i1.8036

Abstract

Many researchers have conducted previous meta-analysis studies regarding problem-based learning (PBL) to enhance problem-solving skills. However, their research does not focus on mathematical problem-solving skills (MPSS). This study aims to summarize, estimate, and evaluate PBL implementation's effect in enhancing the MPSS of Indonesian junior high school (JHS) students and investigate the study characteristics that affect the heterogeneous effect size data. Twenty-nine relevant primary studies published in national and international journals and proceedings during 2011 – 2020 were analyzed using the systematic review and meta-analysis. The analysis tool used the Comprehensive Meta-Analysis (CMA) software by selecting the formula of Hedge to determine its effect size. The result showed that the overall PBL implementation had a medium positive effect (g = 0,743; p less than 0,05), significantly enhancing the MPSS of Indonesian JHS students based on the random effect model. Also, the characteristics of sample size, research area, sampling technique, and publication year did not affect the heterogeneous effect size data. These results suggest that Indonesian JHS mathematics teachers should select PBL as one of the best solutions in implementing mathematics learning in the classroom to enhance students' MPSS.
Klasifikasi Sampah Daur Ulang Menggunakan Dukungan Vektor Machine Dengan Fitur Pola Biner Lokal Leonardo, Leonardo; Yohannes, Yohannes; Hartati, Ery
Algoritme Jurnal Mahasiswa Teknik Informatika 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 (1263.533 KB) | DOI: 10.35957/algoritme.v1i1.440

Abstract

Garbage is one of the problems that always arise in Indonesia and even in the world. Increasingly, the production of waste is increased along with the increase in population and consumption. Therefore, need a prevention to stop wasting or producing garbage through recycle. This research do garbage recycle classification of cardboard, glass, metal, paper and plastic by using Local Binary Pattern (LBP) texture feature extraction methode and Support Vector Machine (SVM) as classification methode. For examination technic and dataset distribution is using K-Fold Cross Validation methode type Leave One Out (LOO). From examination result had been done were using fold 5 until fold 10. Polynomial kernel get highest accuracy result from every fold used with mean point 87.82%. Based on SVM classification examination result whether linear kernel, polynomial nor gaussian by using fold 5 until fold 10. The best accuracy point for cardboard garbage is 96.01%. For glass garbage, the best accuracy point is 90.62%. Then, metal garbage get the best accuracy point 89.72%. While paper garbage with highest accuracy point 96.01%. And plastic garbage with highest accuracy point 87.64%.
Rancang Bangun Aplikasi Permainan EscapeMenggunakan Logika Fuzzy Dan Algoritma Floyd Warshall Prabowo, Adrianus; Devella, Siska; Yohannes, Yohannes
Algoritme Jurnal Mahasiswa Teknik Informatika 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 (1411.428 KB) | DOI: 10.35957/algoritme.v1i2.894

Abstract

Aplikasi permainan ESCAPE merupakan permainan yang mengandalkan player untuk keluar dari labirin tersebut. Penelitian ini menggunakan Logika Fuzzy untuk membuat perilaku komputer menjadi susah ditebak dan Floyd Warshall untuk membuat item jebakan menghalangi player saat bermain. Aplikasi permainan ini dibangun dan dirancang dengan menggunakan Unity 3D dan menggunakan metodologi prototype. Hasil uji dari data sampel menunjukkan bahwa logika fuzzy berhasil diterapkan dalam menentukan perilaku NPC. Hasil uji dari data sampel yang dilakukan menunjukkan bahwa kemunculan item jebakan berhasil diterapkan pada aplikasi permainan ESCAPE.
Penggunaan Fitur HOG Dan HSV Untuk Klasifikasi Citra Sel Darah Putih Prasthio, Rial; Yohannes, Yohannes; Devella, Siska
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 2 No 2 (2022): April 2022 || 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 (1605.811 KB) | DOI: 10.35957/algoritme.v2i2.2362

Abstract

Sel darah putih (leukosit) merupakan sel pembentuk komponen darah yang diproduksi oleh sumsum tulang dan disebarkan ke seluruh tubuh melalui aliran darah. Sel darah putih merupakan bagian penting dari sistem kekebalan tubuh yang berfungsi untuk menghasilkan antibodi yang dapat membantu tubuh manusia dalam melawan berbagai penyakit. Sel darah putih dibagi menjadi 5 jenis, yaitu neutrofil, limfosit, monosit, eosinofil, dan basophil. Analisis sel darah putih masih dilakukan secara manual yang memakan waktu yang lama dan memiliki tingkat ketelitian dan keakuratan yang rendah. Solusi yang dapat dilakukan salah satunya menggunakan machine learning yaitu SVM (support vector machine) dengan menggunakan fitur HOG dan HSV. Penelitian ini menggunakan dataset hasil mikroskop sel darah putih dari Kaggle yang bersifat public. Jumlah dataset yang digunakan dalam penelitian berjumlah 12.392 gambar dari 4 jenis sel darah putih (Eosinophil, Lymphocyte, Monocyte, dan Neutrophil). Pada perhitungan confusion matrix hasil tertinggi didapatkan oleh Neutrophil dengan accuracy sebesar 88,55%, precision sebesar 100%, dan recall sebesar 54,19%.
Klasifikasi Penyakit Mata Menggunakan Convolutional Neural Network Dengan Arsitektur VGG-19 Marcella, Dewi; Yohannes, Yohannes; Devella, Siska
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 3 No 1 (2022): Oktober 2022 || 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.v3i1.3331

Abstract

This study raised a topic related to the classification by using eye diseases in humans. This study uses two optimizing options, namely SGD and Adagrad. The data used are 601 images consisting of 430 training images, 50 validation images, and 121 test images with a total of 4 classes. The method used in this study is the Convolutional Neural Network (CNN) method with the VGG-19 architecture, with input in the form of images that have gone through a preprocessing process, namely resizing and the CLAHE (Contrast Limited Adaptive Histogram Equalization) method of eye disease images. The test scenario consisted of 8 scenarios with different Optimizer and ClipLimit. The highest test results were obtained in the first scenario using the Adagrad optimizer and clipLimit of 1.0 with an accuracy value of 65.29%, precision of 66.53%, recall of 65.29%, and f1-score of 65. 40%.
Co-Authors Ade Hendri Pandrean Annisa, Adde Ariani, Nisha Aryo Sasmita Azarya, Philips Denny Bumi, Harinu Dadang Juandi Dandy, Dandy Daniel Udjulawa Devella, Siska Dody, Muhammad Famerdi, Farhan Agung Febbiola Febbiola Feristyani, Indah Fransiska Kurniawati Gerry Jeven Timoti Hafiz Irsyad Hartati, Ery Indah Feristyani Johannes Petrus Jordan, Stevianus Karina Yolanda Leonardo Leonardo M Ezar Al Rivan Marcella, Dewi Martin, Rizky Meiriyama, Meiriyama Molavi Arman Muhammad Farid Athar Mustaqim Mustaqim, Mustaqim Novan Wijaya Nur Arifin, Nur Pandi Pandi Pandi Pandi, Pandi Pandrean, Ade Hendri Philips Denny Azarya Prabowo, Adrianus Prasthio, Rial Putra, Lipi Amanda RR. Ella Evrita Hestiandari Sahpira, Mulia Sari, Yulya Puspita Setiawan, Jerry Suparman Suparman Surya Dita Prasetya Tamur, Maximus William Hadisaputra Yoannita Yoannita Yoannita Yoannita, Yoannita Yulya Puspita Sari