Open Journal System (OJS) Universitas Bumigora
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Computerpedia (Sistem Informasi E-Commerce) dalam Pembelajaran MSIB di Perusahaan PT. Nurul Fikri Cipta Inovasi
Full text linkPerkembangan teknologi informasi telah mendorong perubahan signifikan dalam pola transaksi jual beli, termasuk di sektor penjualan produk elektronik. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi e-commerce bernama Computerpedia yang berfungsi sebagai media penjualan dan penyedia informasi produk elektronik seperti PC, laptop, dan handphone. Sistem dibangun menggunakan framework Laravel, database MySQL, serta perancangan antarmuka berbasis UI/UX untuk memberikan kemudahan bagi pengguna dalam mencari, memesan, dan melakukan pembayaran produk secara daring. Metode pengembangan yang digunakan meliputi analisis kebutuhan, perancangan sistem menggunakan UML, implementasi, dan pengujian. Hasil implementasi menunjukkan bahwa sistem yang dibuat dapat mempermudah pengguna dalam memperoleh informasi dan melakukan transaksi, serta memudahkan pengelola dalam mengelola produk, pesanan, dan laporan penjualan. Ke depannya, pengembangan fitur keamanan, integrasi dengan platform eksternal, dan peningkatan layanan interaktif direkomendasikan agar sistem dapat bersaing secara kompetitif di pasar e-commerce
Perancangan Antarmuka untuk Aplikas HeRe (Your Health Record HeRe) Berbasis Android
Full text linkProgram Bangkit Academy merupakan inisiatif dari Google bersama dengan mitra industri dan Pendidikan (MSIB) untuk mengembangkan talenta digital unggul di Indonesia. Program ini berlangsung selama enam bulan dan menawarkan tiga jalur pembelajaran utama, yaitu Machine Learning, Mobile Development, dan Cloud Computing, dengan pendekatan pembelajaran berbasis proyek dan kolaborasi tim lintas disiplin. Dalam penelitian ini, penulis menjelaskan pengalaman dalam mengerjakan proyek akhir (capstone project). Proyek akhir yang dikerjakan berjudul "HeRe (Your Health Record HeRe!)" yang bertujuan untuk memudahkan pengguna dalam mengelola dan mengakses rekam kesehatan pribadi secara digital dengan aman dan praktis. Penelitian ini bertujuan untuk merancang antarmuka aplikasi HeRe (Your Health Record HeRe) berbasis Android yang berfungsi sebagai media pencatatan, penyimpanan, dan pengelolaan rekam medis pribadi secara terpusat dan mudah diakses
Optimization of Content Recommendation System Based on User Preferences Using Neural Collaborative Filtering
Full text linkRecommender systems play a crucial role in enhancing user experience across various digital platforms by delivering relevant and personalized content. However, many recommender systems still face challenges in providing accurate recommendations, especially in cold-start situations and when user data is limited. This study aims to address these issues by optimizing content recommendation systems using Neural Collaborative Filtering (NCF), a deep learning-based approach capable of capturing non-linear relationships between users and items. We compare the performance of NCF with traditional methods such as Matrix Factorization (MF) and Content-Based Filtering (CBF) using the MovieLens-1M dataset. The research method employed is a quantitative approach that encompasses several stages, including preprocessing, model training, and evaluation using metrics such as Root Mean Squared Error (RMSE) and Precision@K. The results of this research are significant, demonstrating that NCF achieves the lowest RMSE of 0.870, outperforming MF with an RMSE of 0.950 and CBF with an RMSE of 1.020. Additionally, the Precision@K achieved by NCF is 0.73, indicating the model’s superior ability to provide more relevant recommendations compared to baseline methods. Hyperparameter tuning reveals that the optimal combination includes an embedding size of 16, three hidden layers, and a learning rate of 0.005. Despite its excellent performance, NCF still faces challenges in handling cold-start cases and requires significant computational resources. To address these challenges, integrating additional metadata and exploring regularization techniques such as dropout are recommended to enhance generalization. The implications of the findings from this study suggest that NCF can significantly improve prediction accuracy and recommendation relevance, thus having the potential for widespread application across various domains, such as e-commerce, streaming services, and education, to enhance user experience and the efficiency of recommendation systems. Further research is needed to explore innovative solutions to address cold-start challenges and reduce computational demands
Square Transposition Method with Adaptive Key Flexibility and Strong Diffusion Performance
Full text linkThe Square Transposition method has notable potential in enhancing diffusion within block encryption systems; however, its application is typically limited to perfect square key lengths. The objective of this study is to reconstruct the method to accommodate non-square key lengths by utilizing two square matrices. To assess the effectiveness of the proposed approach, the method of this study uses a comparative analysis conducted against the transposition structures found in DES and AES algorithms, both of which are cryptographic standards established by NIST. The comparison is strictly limited to the transposition component, excluding other components of the full encryption framework. The evaluation involves Monobit, Block Bit, and Run Tests, along with Pearson correlation analysis between plaintext and ciphertext. Tests are conducted on 16 input variations across three key sizes: 128-bit, 256-bit, and 512-bit. The results of this study show that the proposed method achieves lower correlation values (r = 0.02) compared to DES (r = 0.07) and AES (r = 0.05). The conclusion of this study is that these findings indicate the approach offers improved key flexibility and diffusion capability, making it a promising transposition component for block cipher encryption systems. This reconstruction contributes a novel transposition structure that is compatible with non-square key sizes, thereby enhancing both diffusion strength and adaptability in modern cryptographic applications
Comparative Evaluation of Data Clustering Accuracy through Integration of Dimensionality Reduction and Distance Metric
Full text linkThe primary issue in clustering analysis of multivariate data is the low accuracy resulting from a mismatch between the Distance Metric used and the characteristics of the data. This study aims to comprehensively evaluate the effect of eight Distance Metric in the KMeans algorithm integrated with the Principal Component Analysis (PCA)dimension reduction technique. The analysis process was conducted by transforming the data into two principal components using PCA, then applying K-Means to each Distance Metric. Performance evaluation was conducted based on five internal metrics: Silhouette Score, Davies-Bouldin Index, Sum of Squared Errors, Calinski-Harabasz Index, and Dunn Index. The results show that the Bray-Curtis formula provides the best performance, with a Silhouette Score of 0.4291 and SSE of 30.3673. This is followed by Euclidean and Minkowski, which yield the highest Calinski-Harabasz Index value of 2239.85 and Dunn Index of 0.0108, respectively. In contrast, Hamming’s formula yielded the lowest performance across all metrics, with a Silhouette Score of 0.0000 and an SSE of 1996.00. The ANOVA test revealed significant differences between the Distance Metric, with a p-value of ¡0.000 for all metrics, which was further supported by the Tukey HSD follow-up test results. The implications of these findings confirm the importance of selecting an appropriate Distance Metric in the clustering process to ensure the validity, efficiency, and interpretability of multivariate data analysis results
Pelatihan Kesejahteraan Siswa Boarding School Untuk Penggalakan Kewirausahaan Minuman Telang
Full text linkCommunity service is carried out for boarding school students at SMA Unggul Aceh Timur to have independence as the key to success in economic independence. The purpose of community service that will be carried out the form of several things given to partners such as the target of community service to be able to be independent in conducting micro-businesses related to telang drinks; partners will be introduced to insights related to procedures and information regarding processing and marketing telang drinks both offline and digital; telang drink products will be used by partners to be used for entrepreneurship as an additional little economy utilizing telang which is easy to cultivate in the partner\u27s environment into ready-to-sell products and promising economy; the products produced are products that can be used for partners to be able to compete competitively regarding micro-scale packaged telang drinks. The uses a participatory action research approach. The stages begin with preparation, then continue with the implementation of community service, and continue with evaluation and material is presented in the form of lectures, demonstrations/practices and questions and answers/discussions. The results of the training evaluation were successful in encouraging telang drink entrepreneurship for boarding school students
Transformasi Desa Nyitdah Menuju Mandiri Digital Dengan Literasi Digital Pada Masyarakat
Full text linkDesa Nyitdah memiliki sebaran penduduk desa ini hampir merata antara jumlah penduduk Laki-laki dan perempuan. Dari sumber data yang sama juga, diperoleh kategori kelompok masyarakat berdasarkan jenis pekerjaannya, dimana empat kelompok terbesar dimiliki oleh kelompok pelajar, wiraswasta, karyawan swasta dan juga kelompok yang tidak bekerja. Dalam dunia digital, kelompok-kelompok inilah yang merupakan kelompok yang dekat dengan teknologi, namun juga cukup rentan terhadap masalah yang akan ditimbulkan jika tidak memiliki pengetahuan akan perkembangan teknologi yang sesuai. Tujuan pelaksanaan kegiatan Transformasi Desa Nyitdah melalui Pojok Digital adalah untuk mendorong kemandirian desa di era digital dengan meningkatkan literasi teknologi dan kapasitas sumber daya manusia melalui inovasi digital yang tepat guna. Fokus pengabdian kepada masyarakat dalam kegiatan ini adalah mampu memanfaatkan teknologi digital lebih optimal, menciptakan ekosistem digital yang mendukung pengembangan potensi lokal, serta meningkatkan kemampuan masyarakat secara berkelanjutan di bidang teknologi digital khususnya di Desa Nyitdah
Pelatihan Peningkatan Literasi Data Melalui Visualisasi Data Menggunakan Microsoft Excel Dan Google Colab DI Jawa Tengah
Full text linkLiterasi data menjadi hal penting dalam membaca, mengolah maupunmenganalisis data. Dalam literasi data terdapat cara interpretasi data yang disebut dengan visualisasi data. Dalam era digital 5.0 penguasaan teknologi menjadi keterampilan penting bagi tiap individu. Salah satu tools yang digunakan dalam visualisasi data adalah Microsoft Excel dan Google Colab. Microsoft Excel menjadi platform yang familiar bagi penggunanya, akan tetapi kurang dalam hal fleksibel penggunaannya. Oleh karena itu, platform yang dapat digunakan adalah Google Colab yang berbasis Python. Kurangnya pengetahuan dan keterampilan penguasaan teknologi dalam visualisasi data menyebabkan adanya kegiatan pelatihan ini. Hal tersebut didukung oleh hasil pengamatan tim dengan menggunakan sampling beberapa mahasiswa. Tujuan dari kegiatan ini adalah untuk meningkatkan pengetahuan peserta tentang visualisasi data dan meningkatkan keterampilan peserta dalam penguasaan teknologi untuk visualisasi data khususnya Microsoft Excel dan Google Colab. Peserta kegiatan ini adalah mahasiswa dan masyarakat umum di wilayah Jawa Tengah. Pelatihan ini menggunakan metode penyampaian materi dan simulasi penggunaan Microsoft Excel dan Google Colab oleh pemateri dan selanjutnya evaluasi melalui pemberian tugas kepada peserta. Hasil dari pelatihan ini, peserta sangat antusias dalam mengikuti kegiatan ini. Selain itu, peserta aktif dalam pengerjaan tugas implementasi visualisasi data dengan baik
Kolaborasi Pemerintah Desa dan Akademisi dalam Penguatan UMKMKembangGoyangdi Desa Talagasari Balaraja Kabupaten Tangerang
Full text link Artikel ini menganlisis upaya penguatan Usaha Mikro Kecil dan Menengah (UMKM) di Desa Talagasari Kecamatan Balaraja Kabupaten Tangerang Banten melalui kolaborasi antara akademisi dan pemerintah desa. UMKM memainkan peran penting dalam perekonomian desa, namun mereka sering menghadapi berbagai kendala, seperti keterbatasan modal, pemasaran, sertifikasi halal, dan kapasitas produksi yang rendah. Program ini melibatkan metode empat langkah PR untuk menganalisis situasi, merencanakan program, mengimplementasikan solusi, serta mengevaluasi hasilnya. Hasil dari kolaborasi ini menunjukkan pentingnya sinergi pemerintah desa dan akademisi dalam menguatkan UMKMpedesaan. Pemerintah berkontribusi pada peningkatan kapasitas produksi melalui pemberian alat produksi yang lebih besar dan modern, akademisi berkontribusi pada bantuan pendampingan proses sertifikasi halal dan pembuatan konten pemasaran yang lebih menarik. Dukungan dari pemerintah dan Pendampingan oleh akademisi desa membantu UMKM mengatasi berbagai kendala yang dihadapi dan menjadi lebih kompetitif di pasar lokal. Program ini juga menunjukkan pentingnya sinergi antara akademisi dan pemerintah desa dalam memberdayakan UMKM sebagai motor penggerak ekonomi lokal
Bidirectional Encoder Representations from Transformers Fine-Tuning for Sentiment Classification of Cek Bansos Reviews
Full text linkSocial assistance programs are essential government initiatives aimed at supporting underprivileged communities. One such program is facilitated through the Cek Bansos application, which enables users to check their eligibility for social aid. However, user experiences with the application vary, leading to various sentiments in their reviews. Understanding these sentiments is crucial for improving the application’s functionality and user satisfaction. This study focuses on sentiment analysis of user reviews of the Cek Bansos application by leveraging a fine-tuned Indonesian-language Bidirectional Encoder Representations from Transformers (BERT) model. This research aims to evaluate the BERT model\u27s effectiveness in classifying sentiments in user reviews and provide insights that could improve the Cek Bansos application. This research method is the BERT model was fine-tuned using hyperparameters such as a learning rate of 3e-6, batch size of 16, and 9 epochs. The dataset consisted of 8,000 reviews, divided into training (70%), validation (20.1%), and test (9.9%) sets. Review scores were manually categorized, where ratings of 1 to 2 were classified as negative sentiment, 3 as neutral, and 4 to 5 as positive. The results of this research are as follows: the fine-tuned model achieved an accuracy of 77%, with additional evaluation metrics such as precision, recall, and F1 score, demonstrating the model\u27s effectiveness in identifying positive, negative, and neutral sentiments separately. This study concludes that the BERT model provides a reliable method for sentiment classification of user reviews, which could support developers and policymakers in refining the Cek Bansos application to enhance user experience. Additionally, a web-based application developed using Streamlit allows government officials to visualize sentiment trends in real time, improving their understanding of user feedback. Future research could further explore alternative machine learning models and additional linguistic features to improve sentiment classification accuracy and the overall user experience