Kemajuan teknologi yang semakin pesat membuat banyak bidang mengalami perubahan termasuk didalamnya bidang investasi asset digital terutama crypto. Ada banyak cara yang dilakukan oleh para trader maupun investor dalam melakukan perdagangan Bitcoin yang merupakan salah satu asset digital di dunia crypto. Indodax merupakan salah satu platform buatan local Indonesia yang melayani transaksi perdagangan asset digital. Analalisis teknikal dan fundamental dilakukan untuk memprediksi pergerakan harga bitcoin, namun volatilitas yang tinggi menyebabkan pergerakan bitcoin sulit untuk diprediksi. Penggunaan Reccurrent Neural Network yang merupakan sub bidang ilmu dari Machine Learning merupakan salah satu cara untuk dapat melakukan prediksi terhadap bitcoin.Kata Kunci : RNN, LSTM, Bitcoin, Indodax, Training, Testing
Abstract: The Abstract contains a brief description of the purpose of writing, the method used, and the results of the study (if the results of the research). Abstract contains 200-300 words. Abstract written in Indonesian and English. Abstract typing is done single-spaced with narrower margins than the right and left margins of the main text. Keywords need to be included to describe the area of the problem being studied and the main terms that underlie the implementation of the research. Key words can be single words or combinations of words. Number of keywords 3-5 words. These keywords are required for computerization. Searching for research titles and abstracts is made easier with these key words. Abstrak: Abstrak memuat uraian singkat mengenai tujuan penulisan, metode yang digunakan, dan hasil penelitian (bila hasil dari penelitian). Abstrak berisi 200-300 kata. Abstrak ditulis dalam Bahasa Indonesia dan Bahasa Inggris. Pengetikan abstrak dilakukan dengan spasi tunggal dengan margin yang lebih sempit dari margin kanan dan kiri teks utama. Kata kunci perlu dicantumkan untuk menggambarkan ranah masalah yang diteliti dan istilah-istilah pokok yang mendasari pelaksanaan penelitian. Kata-kata kunci dapat berupa kata tunggal atau gabungan kata. Jumlah kata-kata kunci 3-5 kata. Kata-kata kunci ini diperlukan untuk komputerisasi. Pencarian judul penelitian dan abstraknya dipermudah dengan kata-kata kunci tersebut.
Pandemi COVID-19 yang belum berhenti menyebabkan kondisi ekonomi Indonesia kian memburuk. Masyarakat yang terkena dampak pemotongan upah akibat pandemi harus mencari cara untuk mendapatkan pendapatan pasif. Salah satu cara untuk mendapatkan hal tersebut adalah berinvestasi. Cryptocurrency adalah salah satu instrumen investasi berbasis aplikasi yang memiliki return tinggi. Aplikasi Pintu adalah aplikasi pertama yang menyediakan fasilitas mobile apps pada penggunanya. Aplikasi yang dirilis pada tahun 2020 ini sudah memiliki banyak ulasan yang diberikan oleh penggunanya. Ulasan ini dibutuhkan untuk mengetahui apakah ulasan yang diberikan bersifat positif atau negatif. Analisis sentimen pada aplikasi Pintu dipilih untuk melihat sentimen pengguna yang akan dibagi menjadi dua kelas sentimen yaitu positif dan negatif. Klasifikasi dilakukan dengan algoritma Maximum Entropy dengan perbandingan metode pembobotan kata Term Frequency (TF), Term Frequency-Inverse Document Frequency (TF-IDF) dan Binary. Model klasifikasi terbaik dilihat berdasarkan nilai akurasi yang dievaluasi dengan 5-Fold Cross Validation. Hasil klasifikasi model Maximum Entropy dengan Binary memiliki tingkat akurasi sebesar 83,21% sedangkan hasil klasifikasi model Maximum Entropy dengan Term Frequency hanya sebesar 83,01% dan model Maximum Entropy dengan Term Frequency-Inverse Document Frequency hanya sebesar 83,20%. Hal ini menunjukkan bahwa tidak terdapat perbedaan yang signifikan pada model algoritma Maximum Entropy dengan metode pembobotan kata Term Frequency (TF), Term Frequency-Inverse Document Frequency (TF-IDF) dan Binary. Keywords: Cryptocurrency, Binary, Term Frequency, Term Frequency-Inverse Document Frequency, Maximum Entropy
Bitcoin merupakan mata uang digital yang menggunakan sistem kriptografi pertama di dunia. Tujuan utama diciptakannya Bitcoin adalah memungkinkan kedua belah pihak untuk melakukan transaksi secara langsung tanpa campur tangan pihak ketiga. Meskipun Bitcoin merupakan sebuah mata uang, banyak orang yang menggunakan Bitcoin sebagai alat untuk berinvestasi karena harganya cenderung naik cepat dalam waktu singkat. Namun, bukan berarti tidak memiliki risiko. Berinvestasi ke Bitcoin memiliki risiko yang tinggi karena volatilitas harganya sangat tinggi. Penelitian ini bertujuan untuk membandingkan algoritma yang digunakan untuk memprediksi harga Bitcoin. Dalam penelitian ini akan dilakukan prediksi terhadap harga Bitcoin dengan membandingkan empat model algoritma yaitu Linear Regression , Neural Network , Deep Learning , dan k-Nearest Neighbor (k-NN) . Tingkat akurasi dari tiap model algoritma akan diuji dengan metode validasi K-Fold Cross Validation dan dievaluasi menggunakan Root Mean Square Error (RMSE). Hasil dengan uji T-Test dalam penelitian ini menyimpulkan bahwa model terbaik untuk memprediksi harga Bitcoin adalah model algoritma Linear Regression dan Neural Network , yaitu dengan hasil RMSE 296.227 +/- 60.125 ( micro average : 301.655 +/- 0.000) dan 338.988 +/- 47.837 ( micro average : 342.000 +/- 0.000). Kata kunci: Perbandingan algoritma, Bitcoin, prediksi
Blockchain mining is a power &resource consuming task, which requires multiple-levels of optimization, both at resource &task level. Over the years, a wide variety of mining optimization models are proposed by researchers, but most of them are applicable only to a subset of mining types. For instance, mining models used for Proof-of-Work (PoW) consensus-based mining, are not applicable for Delegated Proof-of-Stake (DPoS), and other consensus types. This limits the scalability of these models, which reduces their adoptability for dynamic blockchain systems (DBSes). These DBSes utilize different consensus models as per context of data storage, and are widely used by blockchain designers to deploy high-efficiency, and low delay storage solutions. A standard mining optimization solution is not available for such scenarios, due to which researchers & system designers opt for deployment-specific optimizations, which need to be redesigned for each blockchain system. To remove this drawback, a standard blockchain mining optimization model is proposed in this text. This model uses a combination of Genetic Algorithm (GA) & Particle Swarm Optimization (PSO) for solving two different issues. The GA model is used to optimize miner set selection, which will be used for consensus, while the PSO model optimizes the responses from these miner sets depending upon their temporal mining performance. Due to optimum miner set selection, only higher efficiency miner nodes are used for mining the blockchain. While due to performance optimization of these miner nodes, their internal mining efficiency is improved.This efficiency is evaluated in terms of delay & power needed for single block mining w.r.t. blockchain length. It was observed that a combination of these models is capable of enhancing mining speed, with reduced power consumption, and higher mining throughput. Due to this improvement the proposed HBSBA model outperforms most of the recently proposed blockchain mining models. The model was evaluated on DPoS, Proof-of-Authority (PoA), Proof-of-Stake (PoS), and PoW based consensus models, and a delay reduction of 14.5%, throughput improvement of 8.3%, and reduction in energy consumption by 4.6% when compared with various state-of-the-art models. Due to this improvement, the proposed model is applicable for a wide variety of medium to large scaled blockchain mining applications.
One of the potentials that can be done by smart contracts is the application of buying and selling business in e- commerce. In a study conducted by the British research institute Merchant Machine as reported in databoks.katadata.co.id states that, out of the 10 list of countries that have the fastest e-commerce growth, Indonesia leads the ranks of these countries with growth reaching 78% in the year 2018. As you know, blockchain not only develops cryptocurrency but also in financial services and smart contract payments. Legal arrangements that apply to smart contracts governed by contract and sale and purchase laws in Indonesia have not yet been found, and need to be explored in order to provide certainty regarding legal protection that can guarantee parties who use smart contracts to guarantee legal certainty and fairness in their application. The research that will be conducted in answering these questions uses a systematic review method, the researcher traces the legislation regarding consumer protection, as well as the principles of electronic contract law that can be applied. The results of the study concluded that with the regulations regarding electronic contracts, smart contracts are legal contracts that can be applied in Indonesia.
Many traders believe in and use Twitter tweets to guide their daily cryptocurrency trading. In this project, we investigated the feasibility of automated sentiment analysis for cryptocurrencies. For the study, we targeted one cryptocurrency (NEO) altcoin and collected related data. The data collection and cleaning were essential components of the study. First, the last five years of daily tweets with NEO hashtags were obtained from Twitter. The collected tweets were then filtered to contain or mention only NEO. We manually tagged a subset of the tweets with positive, negative, and neutral sentiment labels. We trained and tested a Random Forest classifier on the labeled data where the test set accuracy reached 77%. In the second phase of the study, we investigated whether the daily sentiment of the tweets was correlated with the NEO price. We found positive correlations between the number of tweets and the daily prices, and between the prices of different crypto coins. We share the data publicly.
Social media news are most important in today's worlds, it puts positive or negative influence on social views. There is a wide propagation of fake news on social media so it will be difficult to believe on the news. Fake news has negative impacts on individuals as well as on society. Information spreads rapidly over the social media and so there is a need of mechanism which detects and stops the spreading of fake news. Therefore, detection of fake news is the need of time and also a challenging problem. The goal of this proposed research work is to detect fake news and minimize spreading of the fake news. In the proposed research a machine learning approach is used for detection of fake news with blockchain framework. In first section a supervised machine learning techniques is design to identify the trustiness of specific news while blockchain framework revoke the malicious activity of spreading fake news. A blockchain environment is created with mining, smart contract as well as Proof of Work (PoW) of consensus. The current systematic review broadly focuses on the various methods to detect fake news in social media. After partial implementation of system, performance evaluation has done with traditional blockchain framework. It is found that 10% less time for transaction verification by consensus in P2P environment over the existing systems.
Silvana Secinaro, Francesca Dal Mas, Valerio Brescia, Davide Calandra
Purpose This study aims to offer a bibliometric and coding analysis of blockchain articles published in the accounting, auditing and accountability fields. Design/methodology/approach The data were collected using the Scopus database and a bibliometric and qualitative coding analysis with the keywords “blockchain” and “accounting” or “auditing” or “accountability.” Of the 514 initial sources, 93 peer-reviewed papers, book chapters and conference proceedings in the areas of business, management and accounting were finally selected. Nonscientific sources such as nonpeer-reviewed books and white papers were excluded. Findings This study reveals a promising and multidisciplinary field of research dominated by scholars and less by practitioners. Qualitative research, especially discourse analysis, is the most used method among authors. This study gives some useful insights about blockchain's definition and characteristics, business models, processes involved, connection with other technologies and relationships with accounting theories. Among the most interesting insights, the results confirm that technology as an external force can create an intersection among several research areas: accounting, auditing, accountability, business, management, computer science and engineering fields. Finally, in terms of research themes, although blockchain has a clear effect on auditing accounting, the links with the area of accountability are less clear and validated. Originality/value This study highlights the current state of the field, combining methodological approaches and providing valuable future research insights. Additionally, it is also a starting point for professionals to fully understand blockchain's characteristics and potential with a constructive and systemic approach.
Similar to decentralized communication systems, a new technology called Blockchain (BC) has the potential to store and manage data in a decentralized manner. By removing the role of third party, all member in the chain has equal access to data. The concept BCT (Blockchain Technology) is not just limited to the cryptocurrencies, but it has been implemented in other areas like e-health, voting, finance, education, smart contract and even in Databases. This paper discusses various Blockchain applications and platforms and then compares these platforms on basis of different parameters. Despite of the advantages, Blockchain faces a significant issue of privacy. This paper examines various security related issues and challenges and presents an account of known possible attacks.
Blockchain technology is gaining prominence after its first famous implementation as part of the digital currency Bitcoin. It is made up of a series of blocks (the ledger) that give a secure, unchangeable, and auditable list of records. Once a block is recorded using encryption and a distributed database, it cannot be modified. The ledger in the case of Bitcoin stores the history of all monetary transactions. In three sections, this paper provides a review of blockchain technology for an interface design audience: (1) The fundamentals that enable block-chain technology are briefly discussed. (2) Specific examples include the use of HCI in blockchain research and development. (3) In the form of a fledgling research agenda, opportunities and difficulties for HCI and interface design are presented.
Cherlina Helena Purnamasari Panjaitan, Lisda Juliana Pangaribuan
Protocol Zero Knowledge Proof is one of the protocols in Cryptography that has a fairly good level of security, because it applies the concept of "Truly Zero Knowledge Proof" which is not leaking any information. This protocol is used in the Fiat Shamir, Guillou Quisquater and Schnorr Feige Algorithms, all of which are Cryptographic Algorithms using private keys and public keys. In the Public key, all three of these Algorithms use a random number generator at the values p and q to get the public key. In this study, the author will generate a public key generation test using CPRNG (Cryptographically-secure Pseudo-Random Number Generator) with the Blum Blum Shub algorithm. The test will be conducted on the Fiat Feige Algorithm, the formation of the key will use the Blum Blum Shub Algorithm, but the Identification Protocol still uses the Fiat Shamir Feige Algorithm. The results of this study show the Feige Fiat Algorithm with the Blum Blum Shub Algorithm as the key builder successfully identifies the pattern sent by the signer.
Hyperledger Fabric refers to a blockchain technology regulated by the Linux Foundation, which implements a blockchain network, namely the permission blockchain. The network provides a membership service concept, which means that only certain parties can transact and access data. This research will show the blockchain architecture design of the hyperledger fabric, which is designed for the purchasing strategy of recycled waste products. The design will be used to make purchases for managing distributors in buying recycled waste products from waste banks as raw materials to be processed. The traditional purchasing process using the bank as a third party will take longer and will be more expensive. Therefore, this research aims to improve data security and transparency between the authorities and direct the payment process in an instant and dramatically reduce transaction costs. Besides, this design can also be applied to any e-commerce. The method used is blockchain, which focuses on hyperledger fabric design. The position on the hyperledger fabric is only applied to the transaction processing of the hyperledger fabric. This study's results apply a design to a blockchain system using a hyperledger fabric to overcome several technical problems related to blockchains such as throughput, scalability, and interoperability and contribute to purchasing strategies.
Ratul Amin Md., Muhammad Yasar Khan, Megat F. Zuhairi
Distributed ledger technology is an immutable data storage and transparent system, which is a constituent component that empowers the FSCM (Food supply Chain Management). Due to the autonomous and immutable data feature, the scalability of blockchain technology is quite a challenge. A supply chain is a network that flows product from suppliers to the final consumer, which produces a high volume of data. In the blockchain, processing high volume of data is quite a significant issue and may affect business profit. To overcome the issue, Big Data and User Controllable Code for Smart Contracts (UCCSC) will be integrated with the blockchain-based FSCM system. Big data technology is typically used to analyze high volume of both structured and unstructured data, which is very difficult to process using habitual database and software techniques. The UCCSC integrates the blockchain and big data and manage the user in the FSCM system. This paper mainly discusses the integration of blockchain-based FSCM and Big Data, and the mechanism that supports such system.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Distributed ledger-based technology crowdfunding is an appealing method for e-economy and its revolutionary concept enable improved credibility and confidentiality in transaction. It has a unique data security concept, which provides immutability, traceability, increased trust and faster settlement. An interesting use case of distributed ledger is the conventional crowdfunding. In the recent years, the acceptance of blockchain for commercial and businesses has significantly increased. Some of the industries, where the blockchain method can be applied are food supply chain, healthcare, crowdfunding, and government services. In this paper, the crowdfunding use case is chosen to be reviewed. Nonetheless, the conventional approach of crowdfunding has a few downsides, which drive away genuine investors into a legitimate business. To date, crowdfunding i.e., monetary funding is typically unregulated, and a lack of end-to-end monitoring system has led to many fraudulent projects. In addition, the traditional crowdfunding lacks transparency and proper agreement (contract) for investors. This paper aims to survey the security issues and challenges of crowdfunding and highlighted the benefits of using blockchain for such use case.
Increased adoption of the Internet of Things (IoT) in multiple domain areas continuously increases the volume of data and transactions from the IoT devices. The IoT systems are vulnerable to more attacks because of increased adoptions and technology adoptions. Protecting the data and providing security to the data and transactions is one of the critical issues for the effective quality of service (QoS) in the IoT environments. An adaptable IoT framework is proposed based on the research approach of 'ADOPT' that leverages the blockchain technology and features considering security as one of the QoS parameters. In the proposed model of a three-layer IoT architecture with an application layer, network layer, and perception layer, the blockchain features are adopted for the resource-constrained IoT environment. In the perception layer, the model uses a local and temporary memory to maintain the local chain, which is managed based on the memory size and time constraints. The application layer nodes manage the synchronization of the data from the corresponding local chain at the edge node. The implementation of the proposed model uses Ethereum, an open-source public blockchain, and using mobile devices as an edge node. The results are verified for security factors like access, authorizations, confidentiality, and computing resources.
Bitcoin is the most popular cryptocurrency with the highest market value. It was said to have potential in changing the way of trading in future. However, Bitcoin price prediction is a hard task and difficult for investors to make a decision. This is caused by nonlinearity property of the Bitcoin price. Hence, a better forecasting method is essential to minimize the risk from inaccuracy decision. The aim of this paper is to first compare three different neural networks which are Feedforward Neural Network (FNN), Nonlinear Autoregressive with Exogenous Input (NARX) Neural Network and Nonlinear Autoregressive (NAR) Neural Network by obtaining the predicted result for each model. The best model is identified by evaluating the performance measurement of each model. After obtaining the best model, it is used to undergo 30 days ahead forecast. The result showed that the performance of NARX out-performed FNN and NAR. It is proven NARX is the suitable neural network to forecast Bitcoin price. The resulting model provides new insights into Bitcoin forecasting using NARX which directly benefits the investors and economists in lowering the risk of making the inaccurate decision when it comes to investing in Bitcoin.
Keamanan data sangat penting dilakukan dalam menjaga kerahasiaan informasi itu sendiri, terutama bila informasi tersebut hanya boleh diketahui pihak yang tertentu saja. Pengiriman data atau informasi tanpa dilakukan pengamanan akan beresiko terhadap penyadapan. Sehingga informasi yang ada di dalamnya dapat mudah diketahui oleh pihak-pihak yang tidak berhak, dan hal seperti itu sangat merugikan.Hingga saat ini, kriptografi merupakan salah satu solusi untuk menjamin keamanan dari suatu informasi. Zero Knowledge Proof (ZKP) merupakan protokol kriptografi yang dapat digunakan seseorang untuk membuktikan kepemilikan seseorang (prover) akan suatu informasi rahasia kepada orang lain (verifier), tanpa perlu mengungkapkan informasi tersebut atau memberikan cara bagi orang lain untuk mengetahui rahasia tersebut. Hasil pengujian adalah Zero Knowledge Proof membagi satu aliran data menjadi blok-blok kecil Masing-masing blok ini dienkripsi secara terpisah. Dalam implementasi tanpa bukti pengetahuan, kunci untuk mengenkripsi hanya akan berada pada pengguna, dan dengan itu, ia akan dapat mengenkripsi dan mendekripsi informas, Algoritma zero knowledge proof adalah metode yang unik dimana pengguna dapat membuktikan kepada pengguna lain bahwa dia tahu informasi tambahan.
 Kata Kunci: Keamanan ,data,penyadapan ,Zero-Knowledge proof
In the past eight years of Bitcoin's history, the economy has seen the price of Bitcoin rapidly grow due to its promising outlook on the future for crypto currencies. Investors have taken note of several advantages Bitcoin provides over the traditional banking system. One such trait is that Bitcoin allows for decentralized banking, meaning that Bitcoin cannot be regulated by powerful banks. There is also a market cap of 21 million Bitcoins that can be in circulation, therefore a surplus of Bitcoins cannot be "printed" which would result in inflation. Bitcoin resolves the issue with transaction security by using a block chain, or a ledger, which records the history of every transaction ever made into one long hexadecimal "chain" of anonymous transactions, which keeps transaction history transparent, but also confidential. Bitcoin as a result has become a very bullish investing opportunity, and due to the huge volatility of the Bitcoin market price, this paper attempts to aid in investment decision making by providing Bitcoin market price prediction. Our team explored several Machine Learning algorithms by using Supervised Learning to train a prediction model and provide informative analysis of future market prices. We start with Linear Regression models, and train on several important features, then We proceed with the implementation of Recurrent Neural Networks (RNN) with Long Short Term Memory (LSTM) cells. All code is written in Python using Google's Tensor Flow software library. We show that the price of Bitcoin can be predicted with Machine Learning with high degree of accuracy.
During the Industrial Revolution 4.0 era, the block chain was used as a digital record of transactions that is simultaneously used and shared within a large decentralized, publicly accessible network. In order to maintain the healthcare sector in Industrial Revolution 4.0, smart contracts are used to provide those addresses which provide transparent ways to do transactions among entities. In the other hand, the adoption has challenges, such as the adoption curve, the complexity of the business ecosystems and standardization, data privacy, and people expectations in the healthcare industry.
This paper recommends a blockchain framework that secures the e-learning platform. The proposed framework was used to build a widely manageable and safe data delivery facility that will connect to existing educational data. Institutions can simply have amassed their data history without demanding a copy from central servers. The proposed blockchain framework enhances data security and removes trust concerns amongst users or between third-party institutions accessing applications and services. Data distribution can be used with smart contracts to warranty that institutions will continue to be in control of their data entrance, are alert of the source of collected data sources, and are up-to-date when their data is log on by others. Immutable audit logs are generated through data source and contact history to keep institutions informed of the time their data are retrieved. Blockchain has the potential that could provide a system with massive openness, online secure database that e-learning platforms needed. The blockchain can be implemented on different learning platforms based on the information security policies of the institutions.
Blockchain is a secure and distributed ledger structure and each block is a cryptographic hash of some other factors like a timestamp. The chain is formed by linking the blocks and distributed data is present on multiple computers. The blockchain made system are more fault-tolerant and has high availability even in times of database failures. Though Linux is considered a benchmark for security, it is susceptible to various attacks. With the use of blockchain, Linux logs can be made more transparent among multiple root users and secured by hosting the logs on a decentralized Ethereum blockchain which is customized as per the requirement. It has been observed that in a scenario with multiple root users working simultaneously on same system, transparency between multiple root users can be compromised if some appropriate changes are made in few lines containing the history, Hence, with the help of Ethereum blockchain and log monitoring using log monitors, it is much easier to track the intrusions to identify the source of unauthorized access to logs or changes in them.
Digital streaming also experiencing rapid expansion, the digital streaming application enables us to access and download videos using the existing electronic platform. All this time, services require the content provider to register the copyright to the marketplace or third party. With the existence of blockchain technology makes it possible for the customer to control their data, the available blockchain technology is Smart Contract. Smart Contracts enables instant payment without delay, without obstacles, and without a third party (mediator) which are performed in a decentralized network. Based on the reasons above, this paper will be focusing on a discussion about the smart contract blockchain on digital video streaming application by creating design a streaming video platform with a decentralized peer-to-peer concept.
PT PLN (Persero) as one of the state-owned companies in Indonesia, has the business of selling electricity as one of the core businesses of the company. Business. With customers in 2018 reaching 71.92 million customers, PT PLN (Persero) has entered into a power purchase and purchase contract with customers with the same number of 71.92 million customers. Smart Contracts are expected to be a substitute for written contracts because smart contracts do not require storage space for written documents and are safe from contract changes made by unauthorized parties because they are protected by cryptographic techniques.