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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Pengabdian UNDIKMA Scientechno: Journal of Science and Technology
Mirza Ardiana
Politeknik Perkapalan Negeri Surabaya
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Pelatihan Dasar Robotika Berbasis STEM bagi Siswa Sekolah Dasar Al-Islah Surabaya Yudi Andika; Mirza Ardiana; Aulia Rahma Annisa; Dwi Sasmita Aji Pambudi; Mustika Kurnia Mayangsari; Sholahuddin Muhammad Irsyad
Jurnal Pengabdian UNDIKMA Vol. 7 No. 1 (2026): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v7i1.18201

Abstract

This community service program aims to enhance elementary school students’ understanding and basic skills in STEM-based robotics (Science, Technology, Engineering, and Mathematics) at SD Al-Islah Surabaya, thereby fostering adaptive, creative, and innovative character development in response to the challenges of globalization. The program implementation included the preparation of instructional modules, delivery of theoretical materials, basic programming activities, equipment demonstrations, hands-on practice, and evaluation using observation sheets to assess participant performance. The activity was conducted at SD Al-Islah Surabaya and involved 94 third- and fourth-grade students accompanied by their homeroom teachers. The results indicate that 50% of the students were able to operate the robots they assembled. In addition, students demonstrated high levels of enthusiasm throughout the activities, actively asked questions, and were able to independently attempt and operate simple robotic systems. Overall, the program effectively improved students’ problem-solving skills and critical thinking abilities, while also developing their foundational understanding of STEM concepts and robotics techniques. This initiative is expected to serve as an initial step toward integrating robotics education into the curriculum of the partner school.
Hyperparameter Optimization of CNN Based Open Set Speaker Verification Using MFCC and Speaker Embedding for Voice Biometric Security Mirza Ardiana; Mat Syai’in; Alief Nur Aisyi Maulidhia; Aulia Rahma Annisa; Yudi Andika; Sholahuddin Muhammad Irsyad; Fauzan Izzul Haq
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13027

Abstract

The development of voice based biometric security systems has increased the demand for authentication methods capable of operating accurately and securely in open set speaker verification scenarios. In this scenario, the system is required not only to recognize registered users but also to reject unknown users who are not included in the system database. This study focuses on hyperparameter optimization in a Convolutional Neural Network Embedding based speaker verification system using Mel Frequency Cepstral Coefficient (MFCC) features and speaker embeddings. The optimization process was conducted through several experimental stages, including MFCC parameter tuning, CNN architecture tuning, embedding dimension tuning, and audio augmentation analysis. The dataset consisted of Indonesian speech recordings from 8 registered speakers and 1 unknown speaker, sampled at 16 kHz under controlled recording conditions. The dataset was divided into training, enrollment, and testing subsets to support open set speaker verification evaluation and reduce data leakage. System performance was evaluated using accuracy, validation loss, False Acceptance Rate (FAR), False Rejection Rate (FRR), best threshold, and inference time. The experimental results show that the best configuration was achieved using the MFCC-C parameters (N_MFCC = 40, N_FFT = 1024, HOP_LENGTH = 256, N_MELS = 40), the CNN-E architecture with three convolution blocks (32-64-128), an embedding dimension of 64, and lightweight augmentation consisting of noise injection, pitch shifting, and time stretching. This configuration achieved stable system performance with a test accuracy of 96.43% and a FAR of 8.7%, while maintaining lightweight computational complexity and real time inference capability. The results also indicate that excessive augmentation may increase embedding overlap between speakers, thereby reducing system security performance. However, the study was conducted on a limited scale dataset and has not yet evaluated robustness against spoofing attacks, replay attacks, or adversarial synthesized voice attacks. Overall, the study indicates that hyperparameter optimization influences the balance between accuracy, computational efficiency, and biometric security performance in lightweight CNN based voice biometric authentication systems under limited scale evaluation conditions.
DEVELOPMENT OF CONTAINER RENTAL STRATEGY FOR BUMN SHIPYARDS SUBCONTRACTORS IN SURABAYA USING QSPM APPROACH Danis Maulana; Gabriela Surya Erinda; Ovi Prina Gastriani; Mirza Ardiana; Muhammad Lukman Arif
Scientechno: Journal of Science and Technology Vol. 5 No. 4 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v5i4.3758

Abstract

This study formulates a container rental development strategy for subcontractors operating in state-owned shipyards in Surabaya. A mixed-method design was applied through tenant questionnaires, interviews with internal managers, expert judgement, and document review. The strategic formulation process integrated the IFE, EFE, IE, SWOT, BCG, and QSPM matrices in sequential stages: identifying internal and external factors, determining the business position, generating alternative strategies, comparing business-unit portfolios, and prioritizing the most attractive strategy. The IFE score of 2.84 indicates that the company has a moderate-to-strong internal position, while the EFE score of 2.70 shows a moderate response to external opportunities and threats. The IE Matrix places the company in Cell V, suggesting a Hold and Maintain orientation. SWOT analysis generated market penetration and product development as the most relevant alternatives, while BCG analysis indicated a declining portfolio condition that requires more active market action. The QSPM result shows that market penetration obtained the highest Total Attractiveness Score of 5.07, compared with 4.72 for product development. Therefore, market penetration is recommended through digital promotion, responsive customer service, simplified rental procedures, and customer expansion.
Co-Authors Alief Nur Aisyi Maulidhia Aulia Rahma Annisa Dwi Sasmita Aji Pambudi Fauzan Izzul Haq Gabriela Surya Erinda Mat Syai’in Muhammad Lukman Arif Mustika Kurnia Mayangsari Ovi Prina Gastriani Sholahuddin Muhammad Irsyad Yudi Andika