Online Journal Systems UNPAM (Universitas Pamulang)
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PERANCANGAN DAN IMPLEMENTASI SISTEM PAKAR BERBASIS WEB UNTUK REKOMENDASI JURUSAN KULIAH BAGI SISWA SMAN 6 KABUPATEN TANGERANG.
No full textABSTRACT
The selection of a college major is a crucial decision for high school students and often causes anxiety due to limited self understanding and lack of information about study programs. This community service activity aims to design and implement a web based expert system at SMAN 6 Kabupaten Tangerang to help students choose majors that match their interests, talents, and academic abilities. The implementation method includes needs analysis, system design using the Forward Chaining method, socialization, and training on system usage for students and guidance counseling teachers. The results show that the expert system is able to provide accurate recommendations based on user input. Evaluation through questionnaires indicates an 85 percent increase in students’ understanding in determining their academic career choices.
Keywords: Expert System, Major Recommendation, Web, Community Service, SMAN 6 Kabupaten Tangerang
Pemanfaatan Informasi BMKG untuk Peningkatan Kapasitas Mitigasi Gempa dan Tsunami Berbasis Komunitas
No full textIndonesia merupakan wilayah rawan bencana gempa bumi dan tsunami karena berada pada pertemuan lempeng tektonik aktif. Di Jawa Barat, keberadaan Sesar Lembang berpotensi memicu gempa bumi dengan magnitudo menengah yang dapat berdampak signifikan pada wilayah padat penduduk. Sementara itu, wilayah pesisir selatan Jawa berada pada zona subduksi aktif yang berpotensi memicu gempa besar dan tsunami. Rendahnya tingkat pemahaman dan kesiapsiagaan masyarakat menjadi salah satu faktor meningkatnya risiko korban saat bencana terjadi. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kapasitas mitigasi gempa dan tsunami berbasis komunitas melalui pemanfaatan informasi resmi dari Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Metode pelaksanaan meliputi sosialisasi, pelatihan kebencanaan, pendampingan penggunaan aplikasi informasi kebencanaan, penyusunan peta evakuasi berbasis partisipasi masyarakat, serta simulasi evakuasi mandiri. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan kesiapsiagaan masyarakat dalam menghadapi ancaman gempa dan tsunami. Pendekatan berbasis komunitas dan penggunaan sumber informasi resmi dinilai efektif dalam mendukung upaya pengurangan risiko bencana.
Kata kunci: mitigasi bencana; kesiapsiagaan masyarakat; gempa bumi; tsunami; BMK
SOSIALISASI ETIKA KECERDASAN ARTIFISIAL DAN PEMANFAATAN DALAM BIDANG PEMBELAJARAN DI ORGANISASI MASYARAKAT GENERASI REMAJA (GEMA)
No full textDi era kemajuan teknologi, termasuk di bidang pendidikan, kecerdasan artifisial (AI) semakin penting. Namun, masih ada beberapa hal yang perlu ditangani sebagai tindak lanjut penerapan teknologi AI, terutama pemahaman dasar, etika, dan penerapan praktis. Organisasi GEMA belum pernah mengikuti kursus maupun sosialisasi mengenai etika kecerdasan buatan. Sebagai tindak lanjut, Tim PKM S2 Teknik Informatika Universitas Pamulang menyelenggarakan kegiatan yang berjudul "Sosialisasi Etika Kecerdasan Artifisial dan Pemanfaatannya dalam Bidang Pembelajaran" pada tanggal 19 Oktober 2025. Filosofi moral, cara menggunakan ChatGPT untuk menulis ilmiah, dan perkembangan kecerdasan buatan akan dibahas dalam kegiatan ini. Hasil evaluasi yang dilakukan terhadap peserta sosialisasi menunjukkan tingkat penerimaan yang dapat diterima secara positif, baik dari segi penyelenggaraan, materi, instruktur dan daya kreatif. Peserta diharapkan belajar menggunakan AI dengan bijak, kreatif, dan bertanggung jawab melalui pendekatan interaktif
Human Capital as the Key to Successful Marketing Strategy Implementation: A Human Resource Policy and Development Perspective
No full textIn the dynamic contemporary business environment, characterized by global competition and digital transformation, the successful implementation of marketing strategy is highly dependent on the quality of its on-the-ground execution. A significant gap often exists between strategy formulation and its realization, where human capital comprising employee competence, learning agility, and commitment, emerges as the primary determinant. This study aims to comprehensively analyze the strategic role of Human Resource (HR) policies and development in shaping superior human capital as the key to successful marketing strategy implementation. Using a literature review approach, this article identifies, evaluates, and synthesizes the relevant body of research to construct a conceptual framework. The analysis confirms that a close alignment between HR policies and marketing strategy objectives is fundamental. It is found that specific mechanisms such as competency-based recruitment, adaptive continuous training, performance-based reward systems, and the development of transformational leadership directly enhance motivation, digital capabilities, and employee engagement in the execution of marketing strategy. The primary implication of this study is the necessity of a paradigm shift: human capital management can no longer be viewed as a supporting operational function. Instead, it must be positioned as an integral strategic partner in the planning and execution of marketing strategies to create a sustainable and inimitable competitive advantage.Keywords: human capital, marketing strategy, HR policy, HR development, competitive advantag
Implementation of Green HRM and Ethical Talent Development in the Automotive After-Sales Sector in Indonesia: A Step Toward Environmentally Friendly Production and Integrity-Based Human Resources
No full textThis study aims to examine the implementation of Green Human Resource Management (Green HRM) and ethical talent development in Indonesia’s automotive after-sales sector as a strategic response to the growing demand for environmentally responsible business practices. The main problem identified is the lack of alignment between environmental awareness and employee integrity in operational activities. The study uses a qualitative descriptive method with case studies in several major automotive service centers as data objects. The analysis explores how Green HRM practices, including eco-oriented recruitment, green training, and sustainable performance evaluation, integrate with ethical principles in talent development. The results show that this integration enhances environmental performance, operational efficiency, and employee commitment, while strengthening corporate reputation and customer trust. Data were obtained through interviews and document analysis conducted in selected automotive service centers to support the qualitative findings The study concludes that implementing Green HRM with ethical values is an effective solution for building a sustainable and integrity-based human resource system in the automotive after-sales industry.Keywords: after-sales service; automotive industry; ethical talent development; Green HRM; sustainability
Penerapan Metode Learning by Doing Untuk Meningkatkan Keterampilan dan Kepercayaan Diri Peserta Kursus Dalam Berwirausaha LKP DINA Depok
No full textThis Community Service (PKM) project aims to implement the findings of a research study titled "The Impact of Accreditation in Improving the Management Quality of the DINA Vocational Training Center (LPK) Depok." One of the key findings indicated that while the quality of graduates is already commendable, there is a significant lack of interest in entrepreneurship. This condition is inconsistent with the objectives of government-funded training grants provided through the Department of Education and Culture. Independent entrepreneurship is the primary target of the Beauty Cosmetology training at LKP DINA, which is designed to foster independent family economic welfare. Theoretical studies suggest that one way to enhance skills and self-confidence in learning is by applying the "learning by doing" method—a learning approach characterized by direct demonstration and practice. The objective of this PKM is to improve the entrepreneurial skills and self-confidence of LKP DINA Depok participants through the implementation of the "learning by doing" method. The program targets 20 participants, with the goal of increasing their competence and confidence to pursue independent entrepreneurship. The intended output of this project is a scientific publication in a community service journal.
Keywords: learning by doing, skills, self-confidence, entrepreneurshi
Penerapan Model T5-Small untuk Abstractive Text Summarization pada Berita Olahraga
No full textSports news is characterized by its length and dense information, so readers often have difficulty quickly obtaining the main information. Manual summary creation is inefficient, while research on automatic summary systems in Indonesian, especially in the sports domain, is still very limited. This study develops an abstractive text summarization model based on the Transformer architecture (T5-Small) to generate summaries of Indonesian sports news. The dataset was obtained from Kaggle and then went through a pre-processing stage including data cleaning, text normalization, tokenization using T5Tokenizer, and the application of padding and truncation to match the model's input format. The model was trained using a data split of 80% for training, 10% for validation, and 10% for testing. Performance evaluation was conducted using the ROUGE-1, ROUGE-2, and ROUGE-L metrics by comparing the model summary against the reference summary (gold standard). The evaluation results using the ROUGE metric indicate that the model has quite good performance in producing relevant summaries. The ROUGE-1 value of 0.6011 indicates that more than half of the unigrams in the model summary match the reference summary. The ROUGE-2 value of 0.3940 indicates the model's ability to capture relationships between words, or bigrams, with a near 40% agreement rate. Meanwhile, the ROUGE-L value of 0.5411 confirms that the model's sentence sequence structure aligns with the original summary. Overall, these three values confirm the model's ability to produce informative and consistent summaries
Komparasi Kinerja Sistem Rekomendasi Destinasi Wisata Menggunakan Content Based Filtering Dan Retrieval Augmented Generation (RAG)
No full textAdvances in artificial intelligence have driven the development of recommendation systems in the tourism sector, which is characterized by diverse destinations. This condition often makes it difficult for tourists to select destinations that match their preferences. Based on literature studies, Content-Based Filtering (CBF) is widely used due to its efficiency; however, it has limitations in understanding contextual information. In contrast, the Retrieval Augmented Generation (RAG) approach has been developed to improve recommendation quality through semantic understanding. This study aims to compare the performance of CBF and RAG in tourism destination recommendation systems. CBF employs TF-IDF and cosine similarity to measure content similarity, while RAG integrates retrieval and generation processes using the LLaMA 3.2 model and the FAISS vector database. The research methodology includes data collection, text preprocessing, system implementation, and evaluation using context recall, faithfulness, answer relevancy, and similarity metrics. The results indicate that CBF achieved a context recall of 0.317, faithfulness of 1.000, answer relevancy of 0.190, and similarity of 0.293, demonstrating high accuracy with respect to source data but limited contextual understanding. Meanwhile, RAG achieved a context recall of 1.000, faithfulness of 0.783, answer relevancy of 0.617, and similarity of 0.715, indicating superior performance in generating relevant recommendations. In conclusion, RAG outperforms CBF in contextual and semantic aspects, while CBF remains more efficient in processing explicit data. This study is expected to serve as a reference for developing more adaptive and personalized tourism recommendation system
Implementasi Yolov5 Deteksi Mata Lelah Berbasis Android
No full textExcessive screen exposure can trigger digital eye strain, reducing visual comfort, attention, and overall productivity. Prior studies in computer vision indicate that deep learning–based object detection, particularly the YOLO family, can recognize facial and eye-related visual patterns efficiently, making it suitable for early-warning systems on mobile devices. This study aims to implement YOLOv5 to detect signs of eye fatigue in real time using the front camera of an Android smartphone. The novelty of this work lies in deploying a lightweight object-detection model on-device through TensorFlow Lite and integrating an automatic notification mechanism as a preventive intervention. The proposed methodology includes collecting and labeling an eye-image dataset into two classes (awake and drowsy), training a YOLOv5 model in Google Colab, optimizing and converting the trained model to TensorFlow Lite, and integrating it into an Android application for live-camera inference. System performance is evaluated using accuracy, precision, recall, and inference speed (FPS). Experimental results show that the system achieves 95.6% accuracy, 94.3% precision, 96.1% recall, and an Average speed of 22 FPS, enabling responsive detection and timely notifications. In conclusion, the Android-based YOLOv5 implementation is feasible as a preventive solution to help users monitor eye-fatigue symptoms and encourage healthier screen-use habits
Pengaruh Rasio Keuangan Perusahaan Terhadap Prediksi Kebangkrutan (Financial Distress) Menggunakan Model Altman Z-Score dan Zmijewski X-Score
No full textPenelitian ini bertujuan untuk menunjukkan secara eksperimental dampak rasio keuangan terhadap probabilitas kesulitan keuangan pada perusahaan rintisan yang terdaftar antara tahun 2019 dan 2023 di Bursa Efek Indonesia (BEI). Rasio profitabilitas, likuiditas, dan leverage diperiksa menggunakan teknik sampel purposif dan data sekunder yang telah mengalami analisis regresi linier berganda menggunakan SPSS 27. Sebagai pengganti kesulitan keuangan, model Altman Z-Score dan Zmijewski X-Score digunakan. Hasilnya menunjukkan bahwa likuiditas memiliki dampak besar pada kesulitan keuangan, berbeda dengan profitabilitas dan leverage. Namun, ketiga rasio tersebut telah terbukti berkontribusi secara bersamaan terhadap kesulitan keuangan. Lebih lanjut, uji akurasi menunjukkan bahwa model Zmijewski X-Score mengungguli Altman Z-Score karena akurasinya yang lebih besar dan kesalahan yang berkuran