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All Journal Technomedia Journal Aptisi Transactions on Technopreneurship (ATT) Jurnal Kajian Ilmiah Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain
Henderi
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Aljabar Relational dan Implementasi kedalam Bahasa Query dalam Perancangan Database Relational Setiyadi, Didik; Henderi
Jurnal Kajian Ilmiah Vol. 20 No. 2 (2020): Mei 2020
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (359.337 KB) | DOI: 10.31599/jki.v20i2.164

Abstract

Abstract Relational algebra (AR) is a procedural query language consisting of a set of operations in which the input is one or two tables which output a new table from the results of the operation performed. Basic AR operations include: SELECT, project, union, set difference and Cartesian product, including additional operations such as set intersection, natural join, Division and Theta join. SQL (Structured Query Language) consists of a simple syntax in the form of instructions in conducting data manipulation, such instructions are often referred to by the Query. As for the query process is the ability to search data from the database, the data displayed can be from one or more tables, where the selected columns can be set by ourselves. At this writing will be discussed about the correlation between the operation process with relational algebra and query by using SQL Server 2008. The first step is to take a case study database Teaching Schedule that has been formed diagramin and the content of the data. Next how to perform operations by using relational algebra and subsequent comparison by using a query by using DBMS SQL Server 2008. Keywords: SQL, Query, SQL Server 2008, Entity Relationship Diagram, Teaching Schedule. Abstrak Aljabar Relasional (AR) merupakan bahasa query prosedural yang terdiri dari sekumpulan operasi dimana inputannya adalah satu atau dua tabel yang outputnya berupa tabel baru dari hasil operasi yang dilakukan. Operasi-operasi dasar AR meliputi : select, project, union, set difference serta cartesian product, termasuk terdapat operasi tambahan seperti set intersection, natural join, division dan theta join. SQL (Structured Query Language) terdiri dari sintaks sederhana dalam bentuk instruksi-instruksi dalam melakukan manipulasi data, instruksi tersebut sering disebut dengan query. Sedangkan untuk proses query merupakan kemampuan untuk melakukan penelusuran data dari basis data, data yang ditampilkan bisa dari satu atau lebih tabel, dimana kolom-kolom yang dipilih bisa kita tentukan sendiri. Pada penulisan ini akan dibahas tentang korelasi antara proses operasi dengan aljabar relasional dan query dengan menggunakan SQL Server 2008. Langkah awal yang dilakukan adalah dengan mengambil studi kasus database Jadwal Mengajar yang telah terbentuk diagrammnya beserta isi datanya. Selanjutnya bagaimana melakukan operasi dengan menggunakan aljabar relasional dan selanjutnya diperbandingan dengan menggunakan query dengan menggunakan DBMS SQL Server 2008. Kata Kunci: Aljabar Relasional, SQL, Query, Sql Server 2008, Diagram, Jadwal Mengajar.
Rancang Bangun Laman Penyetaraan Ijazah Menggunakan Metode Reuse-Based Software Development Kresnala, Dany Prima; Padri, Abdul Robi; Henderi
Technomedia Journal Vol 8 No 2 Oktober (2023): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i2.2116

Abstract

Teknologi informasi telah memberikan banyak manfaat bagi masyarakat dalam mengakses layanan publik, termasuk penyetaraan ijazah dan konversi nilai indeks prestasi kumulatif (IPK) bagi lulusan perguruan tinggi luar negeri. Namun demikian, terdapat tantangan operasional dalam menghasilkan laporan yang dibutuhkan, karena masalah database. Hal ini menyebabkan keterlambatan dalam perbaikan dan pemenuhan Service Level Agreement (SLA). Untuk mengatasi hal ini, diusulkan sebuah Sistem Informasi baru dengan menggunakan metode Reuse Based Software Development. Tujuannya adalah untuk menunjukkan bahwa pendekatan ini dapat mempercepat pengembangan platform penyetaraan ijazah dan konversi nilai IPK dengan memastikan layanan yang sudah ada tidak terganggu  dan dapat memenuhi SLA dengan meningkatkan efisiensi serta efektifitas proses bisnis yang ada. Platform baru ini tidak hanya akan menyederhanakan proses tetapi juga memperkenalkan elemen-elemen inovatif seperti Application Programming Interface (API), yang dapat digunakan oleh para pembuat kebijakan lainnya, bahasa pemrograman yang terstandar sehingga mudah ketika ada pergantian tim pengembang.
Blockchain in Indonesia University: A Design Viewboard of Digital Technology Education Dudhat, Amitkumar; Lestari Santoso, Nuke Puji; Henderi; Santoso, Sugeng; Setiawati, Riri
Aptisi Transactions On Technopreneurship (ATT) Vol 3 No 1 (2021): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v3i1.146

Abstract

The challenge that has often occurred in recent years is making access to education using a different learning process path. The presence of technology now provides solutions to problems that often occur such as communication, accessing information, and business or cooperation. Blockchain is a technology that develops an evaluation model for itineraries in the learning process, both individually and in bulk. Currently the Edublocs project has been designed and implemented, which combines elements of peer-to-peer learning and the teaching team. The aim of the Edublocs project is to simplify the process of designing and implementing a system for recording activity results through blockchain technology. This ongoing project is in the process of evaluation. Conforming to some design elements as well as experimental implementation in the context of higher education enables us to further indicate the sustainability and relevance of the application of blockchain technology in education.
Transformation of Payment in Education Use Bitcoin with Reduced Confirmation Times Henderi; Aini, Qurotul; Manongga, Danny; Sembiring, Irwan; Apriliasari, Dwi
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 1 (2023): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i1.285

Abstract

Significant changes in the financial system are prompted by the growth of the national economy, particularly as a form of payment. The means evolved from barter to things or commodities to metal and paper as the base materials for money before arriving at barter. With such significant changes, there is also a need for a transformation in the world of education in order to welcome technological advancements and one way to survive the changes in the increasingly rapid digital era. As the economic need increases, trade transaction methods shift from traditional to internet-based. One of the necessary international online payment options is bitcoin. For many applications where payments are modest and instantaneous approval is required, Bitcoin is inappropriate because of the high transaction fees and long confirmation periods. As a result, despite the introduction of numerous rival cryptocurrencies to address these problems, the Bitcoin network continues to be the most extensively used payment method. Unquestionably, new finding of this research that effectively address the problems of high transaction costs and transaction verification times are needed if the company is to benefit from its user network. The Lightning Network (LN), which makes use of off-chain bidirectional payment channels between participants, is one of the most recent payment network concepts to be proposed.
Penerapan E-Learning sebagai Media Pembelajaran Berbasis Aplikasi Android Menggunakan Metode Research and Development Jahiri, Muhamad; Diana Yusuf, Inayatul Izzati; Henderi; M.Kom, Henderi
Technomedia Journal Vol 8 No 2 Special Issues (2023): Special Issue: Sistem Informasi Manajemen Dalam Menunjang Teknolog
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i2SP.2096

Abstract

The current development of information technology, especially the internet, can present virtual interaction spaces that are able to provide an unlimited number of sources or resources and can be accessed quickly anywhere and anytime. Currently, Indonesia is entering the era of the industrial revolution 4.0 which prioritizes technology in all fields including learning. But unfortunately the existence of learning media is still lacking, especially in vocational high schools, very few teachers use technology as learning media. E-learning is a type of teaching and learning that allows teaching materials to be conveyed to students using internet media, or other computer network media. E-learning needs to be used to familiarize students with technology. The research model on ADDIE was carried out with five main stages namely: analysis, design, development, implementation and evaluation. Data obtained by questionnaire. The data is then analyzed while the suggestions are used as the basis for revising the product. This study aims to: (1) Make E-learning using Flash Cs 6 at SMK Yanisba Boarding School (2) Determine the feasibility of E-learning using Flash Cs 6 at SMK Yanisba Boarding School. Evaluation of 4 validators on E-learning using Flash Cs 6.
Comparative Analysis of Sentiment Classification Techniques on Flipkart Product Reviews: A Study Using Logistic Regression, SVC, Random Forest, and Gradient Boosting Henderi; Siddique, Quba
Journal of Digital Market and Digital Currency Vol. 1 No. 1 (2024): Regular Issue June 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v1i1.4

Abstract

Sentiment analysis plays a crucial role in e-commerce, providing valuable insights from customer reviews on platforms like Flipkart. This study aims to compare the effectiveness of various sentiment classification techniques, specifically Logistic Regression, Support Vector Classifier (SVC), Random Forest, and Gradient Boosting. The dataset, collected from Flipkart, consists of 205,052 product reviews spanning various categories. Key data preprocessing steps included handling missing values, removing duplicates, normalizing text, and applying TF-IDF vectorization for feature extraction. We implemented and tuned the hyperparameters for each algorithm using grid search and randomized search. The data was divided into training and testing sets with an 80-20 split, and cross-validation techniques ensured robust model evaluation. The performance of each model was assessed using several metrics: accuracy, precision, recall, F1-score, and ROC-AUC. The results revealed that Logistic Regression achieved an accuracy of 0.8995, precision of 0.8773, recall of 0.8995, an F1 score of 0.8736, and a ROC AUC score of 0.9105. The SVC model showed slightly higher accuracy at 0.8997, precision of 0.8619, recall of 0.8997, and an F1 score of 0.8738. The Random Forest model, while robust, had lower accuracy (0.7953) and struggled with precision (0.6326), recall (0.7953), and an F1 score of 0.7047, but achieved a ROC AUC score of 0.9037. Gradient Boosting performed comparably to Logistic Regression with an accuracy of 0.8993, precision of 0.8512, recall of 0.8993, an F1-score of 0.8735, and a ROC AUC score of 0.9098. Comparative analysis identified SVC and Logistic Regression as top performers, balancing accuracy and computational efficiency. These findings suggest that implementing these models can significantly enhance sentiment analysis in e-commerce, improving customer insights and business strategies. Future research should explore advanced deep learning techniques and address class imbalances to further refine sentiment analysis capabilities.
Anomaly Detection in Blockchain Transactions within the Metaverse Using Anomaly Detection Techniques Henderi; Siddique, Quba
Journal of Current Research in Blockchain Vol. 1 No. 2 (2024): Regular Issue September
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v1i2.17

Abstract

The rapid expansion of blockchain technology and its integration into the Metaverse has brought about significant opportunities, but also new challenges, particularly in ensuring the security and integrity of transactions. This study explores the application of anomaly detection techniques, specifically the Isolation Forest algorithm, to identify unusual and potentially fraudulent transactions within a blockchain dataset. The analysis focuses on detecting anomalies across various transaction types, such as sales and scams, and regions including Asia and Africa. The dataset, comprising 78,600 transactions, revealed that 3,930 (approximately 5%) were flagged as anomalies. "Sale" and "Scam" transactions were found to be particularly vulnerable, accounting for the majority of anomalies. Geographical analysis highlighted that Asia and Africa had the highest average risk scores, indicating a higher prevalence of high-risk transactions in these regions. Visualizations further emphasized the distribution of anomalous activities, providing valuable insights into regional and transaction-specific risks. The study demonstrates the effectiveness of Isolation Forest in detecting anomalies within blockchain transactions and underscores the importance of targeted security measures. The findings suggest that focusing on high-risk transaction types and regions can enhance blockchain security. Future research is encouraged to explore additional anomaly detection methods and integrate network analysis to further refine the detection of suspicious activities in decentralized networks. This research contributes to the growing body of knowledge on blockchain security, offering practical insights for improving the detection and mitigation of risks in the increasingly complex and interconnected world of the Metaverse.
Co-Authors Apriliasari, Dwi Danny Manongga Diana Yusuf, Inayatul Izzati Didik Setiyadi Dudhat, Amitkumar Irwan Sembiring Jahiri, Muhamad Kresnala, Dany Prima Lestari Santoso, Nuke Puji M.Kom, Henderi Padri, Abdul Robi Qurotul Aini Setiawati, Riri Siddique, Quba Sugeng Santoso