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All Journal Jurnal Sarjana Teknik Informatika Journal Sensi: Strategic of Education in Information System Jurnal Abdimas Edu Komputika Journal
Sudarni, Ajeng Rahma
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Social Sciences

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Benchmarking YOLOv3 and SSD: A Performance Comparison for Multi-Object Detection Prasetyo, Septian Eko; Atmaja, Chandra; Ardian, Muhammad; Ardhiansyah, Alfian; Sudarni, Ajeng Rahma; Khaira, Mulil
Edu Komputika Journal Vol. 11 No. 2 (2024): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v11i2.28005

Abstract

Multiple object detection remains a significant challenge in the field of computer vision. One of the key factors affecting detection performance is the feature extraction process, especially when objects are relatively small or positioned closely together. This study aims to compare the effectiveness of two popular object detection models, YOLO (You Only Look Once) and Single Shot MultiBox Detector (SSD), in detecting multiple objects within images. These models were selected due to their reported high accuracy and real-time processing capabilities, outperforming traditional methods such as the Hough Transform, Deformable Part-based Models (DPM), and conventional CNN architectures. The models were evaluated using a subset of the PASCAL VOC dataset, which includes object categories such as aircraft, faces, cars, and others, with a total of 1,447 annotated images used in training and testing. The evaluation metric used was mean Average Precision (mAP) to assess detection accuracy. Experimental results indicate that YOLO achieves a mAP of 82.01%, while SSD achieves 70.47%. These findings demonstrate that YOLO provides better performance in detecting multiple objects under the same conditions. Overall, this study confirms the advantages of YOLO in scenarios requiring fast and accurate multi-object detection, highlighting its potential for deployment in real-time applications such as autonomous vehicles, surveillance systems, and robotics. The main contribution of this study lies in providing a comparative performance benchmark between YOLO and SSD on a standard multi-object dataset to guide practical model selection in real-time computer vision tasks.
Ontology Engineering for Modeling National Student Achievements in Higher Education Sudarni, Ajeng Rahma; Prasetyo, Septian Eko; Ardhiansyah, Alfian; Khaira, Mulil
Edu Komputika Journal Vol. 11 No. 2 (2024): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v11i2.28254

Abstract

The need for structured and semantically rich data in higher education underscores the role of ontology-based knowledge modeling. This study develops an ontology to represent national-level student achievements, covering key aspects such as institution, achievement field, category, year, level, and student status. Using a formal ontology engineering approach, the ontology was developed in Protégé and encoded in OWL. Evaluation involved technical validation and reasoning tests including class subsumption, consistency checking, instance classification, and rule-based inference to assess logical soundness and semantic correctness. Description Logic (DL) queries were also executed based on competency questions to evaluate the ontology’s ability to support semantic querying. The results demonstrate that the ontology effectively supports knowledge inference and structured data retrieval, offering strong potential for integration within semantic web environments. This provides a foundation for data interoperability and knowledge sharing across educational systems at the national level. Future work includes expanding the ontology to incorporate dynamic achievement updates and linking with external educational data sources.
Decision Support System for Employee Bonus Recommendation Using Fuzzy Logic Ardhiansyah, Alfian; Sudarni, Ajeng Rahma; Khaira, Mulil; Prasetyo, Septian Eko
Journal Sensi: Strategic of Education in Information System Vol 11 No 2 (2025): Journal SENSI
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v11i2.4069

Abstract

A decision support system is indeed something that should be used to make it easier for organizations to determine a policy. With the existence of information technology, all data analysis and calculation is carried out automatically through computers. Similarly, in making recommendations to give bonuses to an employee in a company or institution. To speed up the decision-making process, a system is needed that can provide recommendations like calculations made by human intelligence. The system was developed using the fuzzy logic method that expresses classical logic into linguistic forms. The advantage offered by this logic is that it produces a more just and humane decision such as a decision that results from human feelings and thoughts. This system uses four variables used to determine the receipt of bonus wages, namely the age of the employee, the length of service, the amount of salary and productivity in one month. Each of these variables has a linguistic variable that is used to represent a certain state or condition that utilizes natural language. This research produces a system that can provide recommendations for organizations or companies to use in determining the receipt of bonus wages in accordance with the rules applied.
Beauty for All: Tata Rias Wajah dan Strategi Pemasaran Berbasis Teknologi untuk Penyandang Disabilitas Maghfiroh, Anik; Ihsani, Ade Novi Nurul; Setyowati, Erna; Afifah, Indah Indi; Sudarni, Ajeng Rahma; Tumangger, Mia Hafizah
Jurnal Abdimas Vol. 29 No. 2 (2025): December 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v29i2.31475

Abstract

The main problems faced by people with disabilities in roemah difabel semarang are the lack of knowledge and skills in applying makeup, limited access to skills education, and economic difficulties. This problem is the main reason for the implementation of this community service activity, with the aim of creating a more productive and sustainable life. This activity aims to provide comprehensive training to people with disabilities in roemah difabel, so that they can understand and apply the right techniques in doing makeup. The methods chosen to implement this community service are as follows: 1) lectures and questions and answers are used when providing material about makeup and technology, 2). practical methods are used when the resource person or speaker practices the steps in applying makeup, then the trainees are asked to practice applying makeup that has been practiced by the resource person with guidance from the resource person and students of the community service team. 3) monitoring and evaluation to assess participants' understanding and skills. The results of this activity ran smoothly and without obstacles, with the enthusiasm of persons with disabilities reflecting increased knowledge and skills in applying makeup. This activity succeeded in improving the quality of makeup according to appropriate techniques, thus having a positive impact on the training participants.
Pengembangan Fitur Activity Leaderboard pada LMS Moodle sebagai Implementasi Pembelajaran berbasis Gamifikasi Syarifah, Dian Farah; Waskito, Deswal; Sudarni, Ajeng Rahma; Djuniadi, Djuniadi
Jurnal Sarjana Teknik Informatika Vol. 13 No. 3 (2025): Oktober
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v13i3.31175

Abstract

Partisipasi aktif peserta didik dalam pembelajaran daring merupakan aspek krusial yang perlu dimonitor dan ditingkatkan. Namun, sistem Learning Management System (LMS) seperti Moodle umumnya hanya menyediakan fitur pelacakan aktivitas secara administratif tanpa memberikan umpan balik yang bersifat motivasional. Penelitian ini bertujuan untuk mengembangkan fitur Activity Leaderboard pada LMS Moodle sebagai strategi implementasi pembelajaran berbasis gamifikasi. Fitur ini mengintegrasikan data aktivitas peserta didik yang mencakup presensi, laporan aktivitas oleh peserta didik, pengumpulan tugas, kuis, partisipasi forum, serta keterlibatan dalam pertemuan daring seperti Zoom meeting. Seluruh data tersebut dikonversi secara otomatis menjadi skor melalui algoritma pembobotan yang mempertimbangkan ketepatan waktu, partisipasi aktif, dan konsistensi keterlibatan. Fitur disajikan dalam bentuk peringkat visual untuk mendorong keterlibatan belajar secara kompetitif. Visualisasi leaderboard ditampilkan secara adaptif menggunakan elemen gamifikasi seperti progress bar, lencana digital, dan peringkat warna gradasi untuk menciptakan prestige effect. Pengembangan sistem dilakukan menggunakan model ADDIE, meliputi analisis kebutuhan pengguna, perancangan antarmuka plugin sebagai modul block, pengembangan integrasi dengan database Moodle, implementasi lokal, serta evaluasi fungsional melalui pengujian black-box. Hasil pengujian menunjukkan bahwa sistem berjalan efisien dengan dukungan cache selama 15 menit, mampu menampilkan hasil secara real-time, serta berpotensi meningkatkan atensi peserta didik terhadap keterlibatannya di LMS. Evaluasi juga menunjukkan keandalan kalkulasi skor, kompatibilitas antarmuka pada berbagai perangkat, serta dukungan konfigurasi yang memudahkan integrasi oleh pengajar. Sistem ini dirancang dengan pendekatan modular agar mudah diperluas dan disesuaikan, sehingga dapat diterapkan dalam berbagai konteks pembelajaran digital. Fitur ini sekaligus menjadi instrumen pendukung dalam membentuk perilaku belajar yang positif dan konsisten.
Co-Authors Ade Novi Nurul Ihsani Afifah, Indah Indi Ardhiansyah, Alfian Atmaja, Chandra Djuniadi Djuniadi Erna Setyowati Khaira, Mulil Maghfiroh, Anik Muhammad Ardian, Muhammad Prasetyo, Septian Eko Syarifah, Dian Farah Tumangger, Mia Hafizah Waskito, Deswal