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All Journal SEMINAR TEKNOLOGI MAJALENGKA (STIMA)
Bastian , Ade
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Computer Science & IT Control & Systems Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Journal : SEMINAR TEKNOLOGI MAJALENGKA (STIMA)

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RANCANG BANGUN MODEL PENGENALAN EMOSI SUARA UNTUK PROMOSI PARIWISATA DI MAJALENGKA Rifki, Muhammad; Bastian , Ade; Mardiana, Ardi
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 9 (2025): Seminar Teknologi Majalengka (STIMA) 9.0 Tahun 2025
Publisher : Universitas Majalengka

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Emotion plays a crucial role in human communication, and recognizing emotions from speech (Speech Emotion Recognition or SER) has broad applications in various fields. This study designs and implements a speech emotion recognition application to support tourism promotion events in Majalengka. A 1D Convolutional Neural Network (CNN) model is developed using public SER datasets (RAVDESS, CREMA-D, SAVEE, TESS) combined and augmented to improve cultural generalization. Key audio features, such as Mel Frequency Cepstral Coefficients (MFCC), are extracted for effective emotion classification. The resulting system achieves an accuracy of 74.4% on test data, successfully recognizing emotions like angry, sad, neutral, and happy with good precision. This automated emotion analysis assists judges in evaluating participants’ speeches objectively and efficiently. The integration of SER technology in tourism events demonstrates an innovative strategy to enhance the promotion of local culture and improve the overall visitor experience in Majalengka.
PERANCANGAN WEBSITE PROFIL TOKO DAN KATALOG PRODUK DI ALFANET COMPUTER Rahayu, Syifaa Puspita; Bastian , Ade
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 9 (2025): Seminar Teknologi Majalengka (STIMA) 9.0 Tahun 2025
Publisher : Universitas Majalengka

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This practical work report discusses the design and implementation of a company profile website and product catalog for Alfanet Computer. The main objective of this project is to create an online platform that provides complete and structured information about the store, product specifications, availability, and prices. The research was conducted using the Waterfall development method, starting from requirements analysis, system design with UML, implementation using HTML, CSS, JavaScript, and PHP, to testing through the black-box method. The website enables store owners to manage product data efficiently and allows customers to access product information anytime and anywhere without visiting the store. The results of this project show that the developed website successfully displays store profiles and product catalogs in a more systematic and user-friendly manner. This system is expected to help Alfanet Computer improve service quality and support business development by expanding access to information through digital media.
ANALISIS KOMPARATIF YOLOV8: AUGMENTASI VS. DATA SINTETIS UNTUK DETEKSI RITEL TERBATAS Fernanda, Billy Adrian; Bastian , Ade
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 9 (2025): Seminar Teknologi Majalengka (STIMA) 9.0 Tahun 2025
Publisher : Universitas Majalengka

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Object detection models are pivotal for retail automation but require vast annotated datasets, which are costly and time-consuming to acquire. This creates a significant challenge in few-shot learning scenarios where data is scarce, leading to models with poor generalization. This study investigates strategies to overcome data limitations by training a YOLOv8 object detection model on a custom dataset of 152 retail product images across 28 classes. We conduct a comparative analysis of three training protocols: (1) a baseline model trained on the original data, (2) a model enhanced with advanced data augmentation techniques, and (3) a model supplemented with synthetically generated data. Performance is evaluated using mean Average Precision (mAP@50−95), Precision, and Recall. The synthetic data approach significantly outperformed the other methods, achieving the highest mAP@50−95 of 0.699 and the highest Recall of 0.856. While the data augmentation model yielded the highest Precision (0.875), its lower Recall (0.714) resulted in a suboptimal mAP. Furthermore, training with synthetic data demonstrated markedly faster and more stable convergence. Our findings indicate that for few-shot object detection in specialized domains like retail, supplementing training with synthetic data is a more effective strategy than relying solely on traditional augmentation.
GAME EDUKATIF BERBASIS CONSTRUCT 3 SEBAGAI MEDIA PEMBELA-JARAN INTERAKTIF UNTUK ANAK USIA DINI DI RA-ALFARISI Rusmanto, Ayu Hafidzah; Zaliluddin, Dadan; Bastian , Ade
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 9 (2025): Seminar Teknologi Majalengka (STIMA) 9.0 Tahun 2025
Publisher : Universitas Majalengka

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Abstract

The advancement of multimedia technology has fostered the emergence of interactive learning media that can enhance students’ interest and comprehension, particularly for early childhood education. This study aims to develop an educational Game using Construct 3 as an interactive learning medium at RA Al-Farisi. The development process applied the Single Development Life Cycle (SDLC) with a Rapid Prototyping approach, which included needs analysis, design, prototyping, testing, and evaluation. The Game content integrates basic educational materials such as the introduction of animals, the solar system, family members, communication tools, and religious values. The usability testing involved teachers and students of RA Al-Farisi using the System Usability Scale (SUS) instrument. The results indicate that the developed educational Game demonstrates good usability, is easy to understand, and engaging for young learners. Therefore, this Game is effective as an alternative interactive learning medium that stimulates children’s cognitive and motor development while enhancing their learning motivation.
Co-Authors Ardi Mardiana Dadan Zaliluddin Fernanda, Billy Adrian Muhammad Rifki Rahayu, Syifaa Puspita Rusmanto, Ayu Hafidzah