e-Journal of Hamzanwadi University
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Analisis Konsep Fisika pada Kearifan Lokal Permainan Tradisional: Etnofisika Gasing Lombok
Get PDFLombok adalah salah satu pulau yang kaya akan tradisi, salah satu tradisi yang ditemukan adalah permainan gasing. Gasing lombok memiliki keunikan tersendiri dibanding gasing-gasing lain, sehingga menarik untuk dikaji lebih mendalam. Penelitian terkait konsep fisika pada permainan tradisional gasing telah dilakukan oleh beberapa peneliti, namun, belum pernah dilakukan penelitian secara mendalam mengenai konsep fisika dalam permainan gasing tradisional khas Lombok, terutama Gasing Lengker. Gasing Lombok memiliki ciri khas yang berbeda dibandingkan gasing pada umumnya, yaitu penggunaan lapisan atau plat baja yang cukup tebal. Penelitian ini bertujuan untuk menganalisis konsep fisika pada kearifan lokal permainan tradisional gasing di Lombok. Penelitian ini termasuk penelitian kualitatif dengan objek penelitiannya adalah gasing lengker khas Lombok. Teknik pengumpulan data yang digunakan berupa wawancara, observasi dan dokumentasi. Penelitian ini menggunakan teknik analisis data deskriptif kualitatif. Analisis konsep fisika dimulai saat akan melepas hingga gasing berhenti berputar. Hasil penelitian menunjukkan bahwa terdapat banyak konsep fisika pada kearifan lokal permainan tradisional gasing Lombok. Saat akan melepas gasing, terdapat konsep-konsep fisika berupa energi potensial elastis, tegangan tali, gaya gesek, torsi, dan momen inersia. Sedangkan, saat gasing berputar hingga berhenti, terdapat konsep-konsep fisika berupa transformasi energi, energi kinetik translasi dan rotasi, momentum sudut, efek giroskopik, serta fenomena presesi dan nutasi. Hasil penelitian ini dapat memberikan kontribusi baru dalam pengembangan media pembelajaran fisika berbasis etnofisika, dengan kasus studi yang relevan dan kontekstual bagi siswa di Lombok dan sekitarnya
Sistem Pendukung Keputusan berbasis Web dalam Pengangkatan Pekerja PKWT Menjadi Pekerja Tetap
Get PDFThe uncertainty of the status of certain time work agreement (PKWT) workers, the appointment of which is still done manually, takes a long time, thus causing certainty problems among workers at CV. Pelita Berjaya Bersama. This study aims to design a decision support system for the appointment of non-permanent workers to permanent workers using the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. This research chose a structured and linear waterfall development model, ensuring each stage of development is completed sequentially with complete documentation. The system was developed by going through the stages of requirements gathering, architecture design (database, interface, AHP, and SAW algorithms), design realization (PHP code writing and MySQL database development), and testing using a black box to ensure the system functions properly. The result of our findings is a decision support system that can help companies in making decisions objectively and simplify the appointment process. The system produces output data in the form of ranking results from each alternative so that it is easy to understand. The use of AHP and SAW algorithms in the system is expected to increase accuracy in the selection process. The results of system testing using black box are declared successful starting from the login to logout process. With this system, the company can appoint PKWT workers to become permanent workers
IKN Public Opinion on TikTok Before and After Efficiency Policy: CNN-LSTM on Imbalanced Data
Get PDFGrowing polarization in Ibu Kota Nusantara (IKN) stems from conventional sentiment analysis tools’ inability to decode TikTok’s contextual complexities, particularly multimodal sarcasm and vernacular-policy relationships (e.g., mangkrak for project cancellations). This study develops a policy-aware hybrid model (CNN-BiLSTM + Policy Knowledge Graph) to decode TikTok’s multimodal sarcasm and vernacular-policy links (e.g., mangkrak), enabling: youth sentiment quantification post-IKN’s 73.3% budget cuts, social criticism-socio-political reality mapping, and evidence-based interventions mitigating Global South strategic project polarization. Using the Knowledge Discovery in Databases framework, we analyzed 2,950 high-engagement TikTok comments (≥10 interactions) from verified accounts (@Polindo.id and @geraldvincentt) across two periods: pre-policy (June-August 2024) and post-policy (January-March 2025). Methodologically, slang normalization, stemming, and minority-class weighting (15×) preceded classification via a CNN-BiLSTM architecture integrated with Policy Knowledge Graphs. Results showed an 18.88% reduction in negative sentiment (83.2%-8.7%), model accuracy of 94.13% (AUC-PR 0.91), and strong correlations between vernacular terms (e.g., mandek [stagnation]) and policy outcomes (r = -0.89; p < 0.01), with investor asing mentions surging 463% post-policy. These validate deep learning-enabled social listening for real-time policy diagnostics, with implications for fiscal transparency dashboards, algorithmic bias mitigation, and context-driven policy communication prioritizing vulnerable groups in SDG infrastructure governance
Quality Evaluation of The SITASI Final Project System using Selected McCall Software Quality Factors
Get PDFThe Final Project Information System (SITASI) was developed to support academic administration processes. However, performance and usability issues continue to hinder its effectiveness, particularly during peak usage. This study aims to evaluate the quality of SITASI using the McCall Software Quality Model by focusing on five relevant operational factors: correctness, reliability, efficiency, integrity, and usability. The research employed a descriptive quantitative approach by distributing a validated user perception questionnaire to 72 students with active experience using SITASI. The instrument was tested for validity and reliability, with data analyzed using descriptive statistical techniques to evaluate the quality of the SITASI system. The results show that usability scored the highest at 86%, followed by correctness at 67.6%, reliability at 64.2%, integrity at 50.8%, and efficiency at 43.5%. These findings reveal strong user interface performance but expose technical limitations in speed and data security. The study concludes that while SITASI performs well in terms of usability, it requires substantial improvements in system responsiveness and integrity features. The results offer a structured evaluation of software quality and provide practical recommendations for developers to optimize performance and strengthen data protection. This study contributes a replicable framework for evaluating academic information systems in higher education environments
Enhanced Data Security in Video Media using RSA-LSB Hybrid Technique
Get PDFSecuring structured documents in dynamic digital media such as video remains a challenge, especially under threats like unauthorized access, format conversion, and compression. This research aims to build a secure and hidden digital document insertion system into video media using a hybrid approach between RSA cryptography algorithm and Least Significant Bit (LSB) steganography. This research developed a steganography system using the prototype method to embed complex documents into video media securely. It uses Python with libraries like OpenCV and PyCryptodome, embedding data into the blue channel's LSB bit to maintain visual quality. The system was tested using various video samples and documents to ensure error-free embedding and 100% accurate extraction, with no file corruption. Robustness against compression and format conversion was also evaluated using metrics like PSNR, SSIM, and BER. The study successfully created a secure system for embedding complex digital documents into video media. Evaluation confirmed high visual quality (PSNR 45.3-63.2 dB), 100% data recovery, and resilience to post-processing, a significant advance over methods that handle only simple payloads
Integrasi Algoritma Apriori dan K-Means untuk Optimalisasi serta Analisis Pola Pemasaran Suku Cadang Otomotif
Get PDFThe automotive parts industry in Indonesia faces challenges of inefficient inventory management and a lack of understanding of customer purchasing patterns, resulting in overstocking or stockouts that cause financial losses. This study aims to apply association rule mining and K-Means clustering to automotive parts retail transaction data to uncover purchasing patterns and product segmentation to support effective inventory management and marketing strategies. Our research is quantitative in nature with a dataset of 14,165 transactions analyzed using Google Colab-Python. The Apriori algorithm was applied with a minimum support of 1% and confidence of 50%, while K-Means clustering was used for product segmentation with normalized numerical attributes. Association rule mining identified 15 significant rules with the strongest pattern between differential oil and brake fluid (confidence 73.5%, lift ratio 5.515). K-Means produced seven optimal clusters (silhouette score 0.68) that categorized products into premium, fast-moving, slow-moving, and other specific characteristics. The main contribution is an integrated framework that combines clustering to enrich the interpretation of association rules, enabling effective bundling strategies. Practical implications include a cross-selling recommendation system (15-20% revenue increase), differential pricing per cluster, and stock predictions that reduce overstocking by 25% and avoid stock-outs, supporting the digital transformation of data-driven retail management
Algoritma Simple Additive Weighting pada SPK Penerima BPNT: Validasi Lapangan dengan Kriteria Nasional
Get PDFThe selection of Non-Cash Food Assistance (BPNT) recipients at the village level often suffers from inaccuracies and limited transparency due to reliance on manual, locally defined indicators. This study develops and validates a decision support system (DSS) based on the Simple Additive Weighting (SAW) method, integrating 14 nationally standardized criteria and a Live Ranking feature to enhance public accountability. The system was implemented using the Personal Extreme Programming (PXP) approach, encompassing planning, design, coding, testing, and deployment. Validation involved comparison with manual SAW calculations and black-box and white-box unit testing. Empirical testing with 30 real cases from Lagi-Agi Village demonstrated 100% accuracy, with system rankings fully consistent with manual results. The DSS ensures objective prioritization of recipients, offering a reliable tool to strengthen fairness, accountability, and transparency in BPNT distribution. Scientifically, this work extends the application of Multiple Attribute Decision Making (MADM) methods to social assistance programs, while practically supporting measurable and equitable aid allocation through the Live Ranking mechanism
Analisis Penerimaan Layanan Spaylater Menggunakan Model UTAUT 2 dan Dampaknya Terhadap Perilaku Online Impulse Buying : (Survey pada Pembelian Produk Fashion oleh Gen Z di Kabupaten Garut)
No full textThis study aims to analyze the acceptance of Spaylater using the UTAUT 2 model and evaluate its impact on online impulse buying (OIB) behavior among Gen Z in Garut Regency. A total of 400 Gen Z respondents who had purchased fashion products on Shopee using Spaylater as the payment method participated in this study. The analysis was conducted using Structural Equation Modeling (SEM) with the assistance of SmartPLS. Gen Z is known as a generation highly engaged with digital technology and strongly attracted to tech-based financial services, including Buy Now Pay Later features such as Shopee PayLater. The results show that social influence (SI) and habit (HB) significantly influence behavioral intention (BI). Beside that, habit (HB) and Behavioral Intention (BI) are significantly influence online impulse buying (OIB). Furthermore, hedonic motivation (HM) not influencing Behavioral Intention (BI), also Social Influence (SI) does not influencing Online Impulse Buying (OIB). These findings suggest that habits and peer pressure strongly affect Gen Z’s use of BNPL services, while fun or pleasure is not a major reason they choose to use them
Analisis Pengaruh Social Interaction dan Brand Awareness terhadap Purchase Intention Pada Tiktok : Mediasi oleh Trust
Get PDFThis study aims to analyze the influence of social interaction and brand awareness on purchase intention on the Tiktok platform, with Trust as a mediating variable. The research is motivated by the rapid growth of social commerce in Indonesia, particularly through Tiktok Shop, which facilities direct interaction between consumers and businesses through the utilization of various tiktok features designed to support corporate marketing activities. A quantitative approach was employes using a survey method involving 200 active tiktok users as respondents. Data analysis was conducted using Partial Least Squares Structrural Equation Modeling (PLS-SEM). The resukts show that social interaction and brand awareness have a positive and significant effect on Trust, and Trust significantly mediates the effect of both variables on purchase intention. These findings provide practical implications for businesses in designing marketing strategis based on social engagement and brand awareness to increase consumer purchase intentions on tiktok
Menelusuri Jejak Bibliometrik Digital Entrepreneurial Intention: Peta Tematik dan Distribusi Global 2011–2025
Get PDFResearch on digital entrepreneurial intention (DEI) has grown significantly over the past decade; however, systematic mapping of its trends, scholarly collaborations, and thematic structures remains limited. This study aims to map the development of scientific publications, thematic distribution, and influential contributors in DEI research using a bibliometric approach. A total of 236 articles from the Scopus database covering the years 2011–2025 were analyzed using the PRISMA method, supported by Microsoft Excel, Publish or Perish, and VOSviewer for data visualization. The results indicate a sharp increase in DEI-related publications since 2021, with key themes including digital literacy, self-efficacy, entrepreneurship education, and the Theory of Planned Behavior. Students emerged as the most frequently studied population within this field. Furthermore, the study identifies the most productive countries, authors, and journals contributing to DEI research. These findings provide a comprehensive overview of the intellectual landscape of digital entrepreneurship and offer a foundation for developing policy and educational strategies in digital entrepreneurship