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Jurnal Teknimedia: Teknologi Informasi dan Multimedia
Published by STMIK Syaikh Zainuddin Nahdlatul Wathan Anjani
ISSN : 27226263     EISSN : 27226271     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
JURNAL TEKNIMEDIA : Teknologi Informasi dan Multimedia terbitan berkala ilmiah nasional diterbitkan oleh STMIK Syaikh Zainuddin NW Anjani. Tujuan diterbitkannya Jurnal TEKNIMEDIA adalah untuk memfasilitasi publikasi ilmiah dari hasil penelitian-penelitian di Indonesia serta ikut mendorong peningkatan kualitas dan hasil penelitian untuk akademisi dan peneliti. Jurnal TEKNIMEDIA terbit 2 (dua) kali dalam satu tahun (lima bulan sekali) pada bulan Januari-Mei dan Juni-Desember dengan ruang lingkup bidang ilmu Informatika, Telekomunikasi dan rumpun Komputer Sains.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 202 Documents
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MODEL SKORING ADAPTIF KINERJA UMKM BERBASIS KPI MENGGUNAKAN QUANTILE CLIPPING DAN DATA-DRIVEN WEIGHTING Abdul Halim; Nurul Chafid; Mochammad Darip
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.368

Abstract

Monitoring the performance of Micro, Small, and Medium Enterprises (MSMEs) is a challenge for local governments due to the large number of business actors, heterogeneity of business scale, and variations in financial indicators that often contain extreme values. These conditions cause Key Performance Indicators (KPI)-based evaluations to be susceptible to bias when using conventional normalization and weighting. This study aims to develop an adaptive scoring model for MSME performance based on KPIs that is robust to outliers and more objective in indicator weighting. The proposed method integrates quantile clipping at the P5–P95 percentiles to stabilize the KPI distribution, followed by min–max normalization to the range 0–100. Furthermore, KPI weights are determined in a data-driven manner using standard deviation (adaptive weighting) to represent the indicator's contribution based on actual data variations. Experiments were conducted on a dataset of 1,000 MSMEs in Serang City using three main KPIs, namely ROI, Profit Margin, and Growth Rate. The results show that the adaptive weights obtained are ROI 0.308, Profit Margin 0.353, and Growth Rate 0.339. A ranking comparison between fixed weighting and adaptive weighting yielded a Spearman correlation of 0.9879, and two entities changed in the Top 10. These findings indicate that the adaptive method maintains ranking stability while increasing evaluation objectivity. The proposed model is computationally efficient and has potential for application in multi-indicator-based performance monitoring systems.
EVALUATING OF DEEP LEARNING MODELS FOR EARLY DETECTION IN MEAT CLASSIFICATION: A STUDY ON BEEF AND PORK DETECTION Taopik Hidayat; Faruq Aziz; Daniati Uki Eka Saputri; Nurul Khasanah
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.370

Abstract

Accurate classification of beef and pork images is crucial for developing reliable automated food inspection systems, particularly due to their visual similarity in color, texture, and muscle fiber patterns. This study aims to comparatively evaluate the performance of multiple deep learning models for binary meat image classification using RGB digital images. Four Convolutional Neural Network (CNN) architectures, namelyInceptionV3, VGG16, ResNet50, and Xception were assessed under identical preprocessing pipelines and hyperparameter settings to ensure a fair comparison. The dataset underwent cropping, resizing to 224×224 pixels, normalization, and augmentation to enhance variability and improve generalization performance. Model effectiveness was measured using accuracy, precision, recall, and F1-score on unseen test data. Experimental results show that InceptionV3 achieved the most balanced classification performance, with a test accuracy of 72% and an F1-score of 0.7. Although Xception obtained higher training accuracy, it exhibited overfitting during testing, while VGG16 and ResNet50 demonstrated comparatively lower classification capability. These findings indicate that InceptionV3 provides a more stable and generalizable architecture for beef and pork image classification. The study highlights the importance of cross-architecture evaluation in developing robust CNN-based systems for automated meat classification.
A MACHINE LEARNING SYSTEM ARCHITECTURE FOR PROACTIVE CUSTOMER CHURN PREDICTION Ricky Pieter Palembangan; Ahmad Nurul Fajar
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.377

Abstract

The hyper-competitive credit card industry faces growing challenges from digital disruption and evolving consumer expectations, demanding a shift from reactive to proactive customer retention strategies. Traditional reactive approaches prove ineffective as customer decisions often reach irreversible stages before intervention. This study aims to develop and evaluate a comprehensive data-driven framework for predicting customer churn at PT XYZ, a leading Indonesian banking institution, and design a scalable system architecture with CRM integration and real-time analytics dashboard for operational deployment. Following the CRISP-DM framework, we comparatively evaluate Logistic Regression, Decision Tree, and Random Forest using a dataset of 11,314 customer records. Model performance evaluation encompasses multiple metrics including Accuracy, Precision, Recall, F1-Score, AUC. Random Forest algorithm demonstrated superior performance, achieving an AUC of 0.98 and accuracy of 97 percent. Feature importance analysis revealed customer transaction inactivity and credit utilization patterns as the most critical churn predictors, with transaction count contributing 41.59% importance score. The research successfully establishes a robust foundation for data-driven customer retention strategies, providing PT XYZ with a comprehensive blueprint for institutionalizing proactive retention strategies that can minimize revenue losses and secure competitive advantages in an increasingly dynamic market environment.
DATA QUALITY IMPROVEMENT: CASE STUDY FAST PAYMENT SYSTEM INFRASTRUCTURE Jefree W.L.H Manurung; Yova Ruldeviyani
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.379

Abstract

This study aims to assess the data quality of the Fast Payment System infrastructure application. The assessment employs a specialized framework for financial data, namely the QAFD (Quality Assessment Framework for Data), which focuses on five data quality dimensions. Given the high transaction volume and operational criticality of fast payment systems, ensuring reliable data quality is essential to support reporting, analysis, and policy communication. Data quality assessment was conducted through two approaches: objective and subjective assessment, applied to 34 variables. The objective assessment was based on quantitative measurements of the data, while the subjective assessment involved user or stakeholder perceptions of data quality. The objective assessment results showed that the Accuracy dimension reached 99.99%. The Completeness dimension for mandatory data variables was recorded at 84.41%. For the Uniqueness dimension, the variable sending_customers_id_number_hash achieved 87.34%, while receiving_customers_id_number_hash reached 99.96%. Meanwhile, both the Currency and Timeliness dimensions achieved a 100% rate. A comparison between the objective and subjective assessment results indicated discrepancies in the Completeness and Uniqueness dimensions, while the other dimensions were aligned. These findings indicate that data quality challenges extend beyond technical processing aspects and reflect the importance of continuously improving metadata clarity and business rule alignment governing variable usage and identifier relationships. This study contributes by providing empirical evidence of QAFD implementation in fast payment operational data and emphasizes the value of proactive data governance through metadata enhancement and strengthened validation mechanisms to support reliable reporting and institutional credibility.
COMPARISON OF THE EFFECTIVENESS OF WHATSAPP GROUPS AND WEBSITES AS INFORMATION MEDIA FOR TAM-BASED PPDB Nurul Chafid; Abdul Halim; Mochammad Darip
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.382

Abstract

The development of digital technology has encouraged schools to utilize various platforms to deliver information, particularly in the new student admission process, commonly referred to as PPDB. MIN 7 Tangerang uses WhatsApp Groups and the school website as the primary media for disseminating PPDB information; however, the effectiveness of these two media has not been determined. This study aims to compare the effectiveness of WhatsApp Groups and the website as media for PPDB information using the Technology Acceptance Model (TAM) approach. The study employed a quantitative method supported by qualitative data. Data were collected from 136 parents of admitted students who passed the PPDB selection for the 2024/2025 academic year, all of whom had accessed and used both media. The research instrument consisted of a Likert-scale questionnaire based on TAM constructs along with additional variables. Cronbach’s Alpha was used to test the reliability of the instrument, while validity testing was conducted using Exploratory Factor Analysis (EFA). Furthermore, a paired sample t-test was applied to compare two related conditions, and regression analysis was employed to examine the effect of Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) on technology acceptance. The results indicate that WhatsApp Groups are superior in terms of ease of use, whereas the website demonstrates superiority in terms of usefulness, trust, and user satisfaction. The regression analysis confirms that both PEOU and PU significantly influence technology acceptance, with PU exerting a more effect. In conclusion, WhatsApp Groups and the website play complementary roles in delivering PPDB information.
PENGEMBANGAN DAN EVALUASI EKSPERIMENTAL SISTEM DETEKSI KUALITAS TELUR REAL-TIME BERBASIS PENGOLAHAN CITRA DIGITAL DAN MODEL YOLO PADA PERANGKAT EDGE Iqbal May Aryanto; Syaiful Mansur; Ayu Sintianingrum; Ayang Kinasih; Eko Hari Tiarto
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.384

Abstract

The demand for chicken eggs as a nutritious protein source continues to rise, yet automated inspection technology in small-scale farms remains limited due to high costs. This study develops a standalone, low-cost real-time egg quality detection prototype based on the edge computing paradigm. The system is implemented on a Raspberry Pi 4 Model B using the YOLOv8n deep learning model to classify eggs into three categories: Good, Cracked, and Broken. Visual data is acquired via a Raspberry Pi Camera Module 3 supported by controlled white LED ring lighting at a fixed distance of 20 cm to mitigate environmental light variations. Experimental evaluation using 1,080 samples indicates that the system achieves an optimal accuracy of 91.30% at 320x320 resolution under controlled lighting. Technically, the system demonstrates stable performance with CPU usage ranging from 43% to 76%, while maintaining temperatures at 48-510C. Despite a processing speed of 0.5-0.6 FPS, the system's independence from cloud connectivity makes it a highly applicable objective inspection solution for small-scale farmers in regions with limited digital infrastructure.
IMPLEMENTASI DAN ANALISIS AUGMENTED REALITY (AR) SEBAGAI MEDIA PEMBELAJARAN DI WILAYAH 3T: STUDI KASUS PADA SMA NEGERI 1 ROTE BARAT Andreas Niko Priyohutomo; Viany Utami Tjhin
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.387

Abstract

This study explores the implementation and effectiveness of Augmented Reality (AR) technology as an innovative educational solution for overcoming learning challenges in Indonesia's 3T regions (Tertinggal, Terdepan, dan Terluar - Remote, Frontier, and Underdeveloped areas). Conducted at SMA Negeri 1 Rote Barat, East Nusa Tenggara, this research employs a mixed-methods approach combining qualitative and quantitative data collection through in-depth interviews, classroom observations, student questionnaires (n=60), and documentation analysis over six months (May-October 2025). The study develops a comprehensive research model incorporating Technology Acceptance Model (TAM) variables including Perceived Usefulness, Perceived Ease of Use, Interactivity, Technical Barriers, and Social-Cultural Support as independent variables, with Student Satisfaction as a mediating variable and Continuance Intention as the dependent variable. Results demonstrate that AR implementation significantly enhances student engagement, motivation, and understanding of complex concepts despite infrastructure limitations typical of 3T regions. Social-cultural adaptation and teacher support emerge as critical success factors. The research provides valuable insights for educational policymakers and institutions seeking to implement technology-enhanced learning in underserved areas while addressing unique challenges of remote educational contexts.
ANALYSIS OF FACTORS INFLUENCING CONTINUANCE INTENTION OF DIGITAL BANK USERS IN JABODETABEK: A STUDY ON USERS OF JENIUS, NEOBANK, DIGIBANK, AND TMRW APPLICATIONS Stephani Elmanta Ratri; Tanty Oktavia
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.393

Abstract

The rapid development of digital technology has accelerated the transformation of the banking industry, particularly through the emergence of digital banking applications that enable customers to conduct financial transactions more efficiently and conveniently. This study aims to analyze the factors influencing the continuance intention of digital banking users by examining the roles of perceived ease of use, perceived usefulness, customer service quality, perceived security, and perceived risk in shaping customer satisfaction and customer trust. This research employs a quantitative approach using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. Data were collected through questionnaires distributed to active users of several digital banking applications. The analysis results indicate that perceived ease of use and customer service quality play important roles in increasing customer satisfaction. In addition, perceived risk is identified as a crucial factor in shaping customer trust toward digital banking services. Furthermore, customer satisfaction is found to be a major determinant in encouraging users to continue using digital banking applications, while customer trust also contributes positively to the intention to maintain long-term usage. The structural model demonstrates strong explanatory capability in explaining users’ continuance intention. These findings highlight that improving user experience, strengthening service quality, and managing security and risk effectively are essential strategies for digital banking providers to maintain customer satisfaction, build trust, and encourage sustainable usage of digital banking services in Indonesia.
THE ROLE OF PERSONALIZATION, RECOMMENDATION SYSTEMS, INFORMATION QUALITY, AND E-SERVICE QUALITY IN IMPROVING SHOPEE USER SATISFACTION: AN SEM-PLS APPROACH Graviela Charleen; Elfindah Princes
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.396

Abstract

User satisfaction has become a crucial factor in the success of e-commerce platforms amid increasingly fierce competition, particularly for Shopee as the platform with the highest number of visits in Indonesia. This study aims to analyze the influence of personalization, recommendation systems, information quality, and electronic service quality (e-service quality) on Shopee user satisfaction through the mediation of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) within the Technology Acceptance Model (TAM) framework. The research method employed is a quantitative approach with a survey of 430 active Shopee users in the Jabodetabek area who have completed at least two transactions in the last three months. Data were analyzed using Partial Least Square-based Structural Equation Modeling (SEM-PLS) with SmartPLS software. The results show that the recommendation system is the strongest predictor of PU, while e-service quality is the main determinant of PEOU. PU has the most dominant direct influence on user satisfaction, followed by PEOU. All mediation paths proved to be significant, with the recommendation system having the strongest indirect effect through PU. The research model can explain 73.1% of the variance in user satisfaction. It can be concluded that the integration of intelligent technology and basic service quality simultaneously shapes perceptions of usefulness and ease of use, which become the main pillars of e-commerce user satisfaction in Indonesia.
REKAYASA DIGITAL SISTEM EKONOMI DALAM PENGEMBANGAN EKONOMI SIRKULAR BERBASIS EKONOMI SYARIAH DI KABUPATEN LOMBOK TIMUR irfan azim; Abdul Khalik; Agus Salihin; Nuraenun Nuraenun
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.404

Abstract

The governance of conventional communal waste banks is frequently characterized by managerial inefficiencies and a heavy reliance on manual record-keeping, which fosters information asymmetry. From the perspective of Islamic economics, such conditions manifest as gharar (informational uncertainty), potentially undermining amanah (trust) and ‘adl (fairness in valuation), while simultaneously neglecting the circularity of organic materials—thereby contravening the principle of Hifzh al-Bi’ah (environmental preservation). This study aims to engineer, develop, and evaluate a digital platform ecosystem for waste bank management (SiRKAH) that inherently integrates circular governance with the principles of Maqashid Sharia. Employing the Design Science Research Methodology (DSRM), the system artifact was validated by a multidisciplinary expert panel using the Content Validity Index (CVI) and its efficacy was assessed through field-based operational comparisons (pre- versus post-implementation). The expert validation results confirm a highly robust architectural validity, with an S-CVI score of 0.939. Operationally, the implementation of a digital ijab-qabul protocol (dual authentication) and an immutable ledger has demonstrated significant efficacy disruption: reducing transaction duration by up to 94.2%, completely eliminating (100%) recording errors and balance disputes, and increasing user participation rates by 46.4%. This study contributes to the Green Information Systems (Green IS) literature through the conceptualization of a “Gharar-Free System Architecture,” demonstrating that the fusion of digital technological engineering with religio-communal ethical values constitutes a robust instrument for restoring public trust and accelerating the adoption of a circular economy.

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