Blockchain Papers

Dendi Ramdhani, Dzaky Farras Fauzan, Rama Hadi Nugraha, Dyandra Cissy · 5 authors

No abstract is available for this record.

Sylwia Nowak

Rules of origin are a core element of any free trade agreement, but their complexity can present significant challenges for efficient and compliant use. This paper discusses the challenges and opportunities in automating origin calculations for businesses involved in cross-border trade. It focuses on the role of Enterprise Resource Planning (ERP) systems, customs software and Long-Term Supplier Declarations (LTSDs) in simplifying compliance with preferential origin rules. Focusing on the United Kingdom’s trade, the paper outlines key factors businesses must consider to effectively automate origin management, such as rules interpretation, data quality, legal documentation and supplier cooperation. The potential roles of distributed ledger technology (DLT) and automation within customs declarations software are also explored.

I WAYAN SUMARJAYA, RENOVAR JOJOR DELIMA SIMANULLANG, RATNA SARI WIDIASTUTI

Forecasting is the process of estimating future events using past data. Financial time series forecasting often prioritizes stock price variables. Apart from the stock price variable, inter-transaction time or duration is also an important variable to predict, because the timing of changes in financial prices cannot be predicted. Duration modeling and forecasting can be done using the autoregressive conditional duration (ACD) model. In this research, modeling and forecasting using the ACD model was carried out on Ethereum. This research aims to predict the duration of Ethereum in order to help traders know the time needed to reach the next price change. Several ACD models with four distributions, i.e., exponential, Weibull, Burr, and generalized gamma were fit to the Ethereum duration. The research results suggest that the Burr-ACD model produces the smallest AIC value compared to other distributed ACD models. However, the forecast results using the Burr-ACD models show increasing duration and hence are less accurate. The generalized gamma-ACD (2,2) model was then chosen as an alternative for forecasting Ethereum duration, showing that Ethereum duration forecast results are less than one second, which indicates the high frequency of transactions that occur on Ethereum.

Surya Darmawan, Wafiq Azizah

This study aims to analyze Bitcoin price volatility after halving by considering interactions with Ethereum, Tether, Binance Coin, and USD Coin. This research was conducted because Bitcoin halving is a significant event affecting the dynamics of the crypto market, but its impact on price volatility is not fully understood. This research uses the EGARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity) method with purposive sampling technique. Daily price data from Bitcoin, Ethereum, Tether, Binance Coin, and USD Coin in the period May 11, 2020 to May 31, 2024. The analysis results show that Bitcoin price volatility increased significantly after the halving event. In addition, there is an effect of Bitcoin price volatility after halving, namely on the price of Ethereum, Tether and Binance Coin. While the price of USD Coin cannot be proven because the daily closing price data is homoskedasticity.

Herdian Rio Saputro, Noor Lathifah

Penelitian ini mengeksplorasi implementasi teknologi blockchain melalui Non-Fungible Token (NFT) dalam sistem e-ticketing pada industri hiburan, khususnya untuk acara stand-up komedi. Dengan pendekatan riset pasar dan uji konsep, penelitian ini bertujuan mengidentifikasi manfaat, tantangan, dan peluang dari penerapan NFT untuk meningkatkan daya saing bisnis. Hasil penelitian menunjukkan bahwa NFT dapat memberikan solusi inovatif dalam menjamin keamanan, keaslian, dan fleksibilitas tiket digital. Selain itu, NFT menawarkan nilai tambah berupa akses eksklusif, sistem royalti untuk kreator, serta peluang investasi dalam aset digital.Meskipun adopsi NFT dalam ticketing masih tergolong baru, fitur seperti mixed reality dan akses premium mampu menarik minat audiens modern yang mengutamakan pengalaman digital. Analisis terhadap kompetitor mengungkapkan potensi besar dalam mengintegrasikan NFT ke dalam sistem e-ticketing, walaupun tantangan berupa rendahnya pemahaman masyarakat terhadap teknologi blockchain masih menjadi hambatan utama. Proyek "NFT ComedyChain" yang diusulkan dalam penelitian ini dirancang untuk mengintegrasikan teknologi NFT dengan industri hiburan di Indonesia, membuka peluang bisnis baru bagi kolektor seni digital dan pelaku industri kreatif.Penelitian juga ini merekomendasikan adanya edukasi luas dan kolaborasi lintas sektor untuk memaksimalkan adopsi NFT, sekaligus menciptakan ekosistem hiburan yang aman, modern, dan inklusif. Dengan memastikan keaslian tiket melalui teknologi blockchain, NFT ticketing tidak hanya mengurangi risiko pemalsuan tetapi juga memperkenalkan model bisnis berkelanjutan yang menguntungkan semua pihak terkait. Implementasi NFT pada e-ticketing diharapkan menjadi gagasan baru dalam transformasi digital industri hiburan, terutama di Indonesia, sehingga mampu menciptakan nilai kompetitif yang lebih tinggi bagi para pelaku usaha.

Michał Pawlak, Mateusz Stolarczyk, Aneta Poniszewska-Marańda

Due to the expanding global population and the resulting surge in food demand, the challenges confronting the food supply chain network have to be examined and solved. These challenges encompass food safety, food fraud, traceability, and transparency in the supply chain. This paper analyzes the potential of blockchain technology to tackle these challenges by reviewing relevant literature. Addressing the limitations of current food supply chain management systems allows to suggest a new, transparent, and secure system that utilizes blockchain technology and is publicly available. The proposed system is built on the Hyperledger Fabric blockchain platform, features a permissioned distributed ledger, and efficiently stores and manages supply chain data.

Ericko Verdianto Karnadi, Dedy Dwi Prastyo

No abstract is available for this record.

Xiaopo Zhuo, Yajie Sun, Shaorui Zhou

Blockchain technology (BCT) has emerged as a promising solution for ensuring supply chain traceability. However, not all consumers have a comprehensive understanding of the benefits associated with BCT-enabled traceability. In this article, we investigate the impacts of consumer awareness on the adoption of BCT within a supply chain comprising a manufacturer and a retailer. We develop two distinct scenarios: Scenario B, where the supply chain traceability is managed via traditional digital systems, and Scenario E, where the supply chain traceability is managed via BCT-enabled systems. We introduce the concept of consumer traceability awareness level, representing the proportion of the consumer population that is knowledgeable about the advantages of these traceability technologies. The findings reveal that the adoption of BCT enhances the overall performance of the supply chain and makes it more sensitive to the consumer traceability awareness level. Nonetheless, the manufacturer consistently experiences advantages from BCT adoption, whereas the retailer's situation may deteriorate. In both scenarios, a low traceability awareness level prompts the retailer to target all consumers, whereas a high-traceability awareness level shifts its focus solely to the knowledgeable consumers. Intriguingly, the adoption of BCT shifts the retailer's inclination toward targeting the knowledgeable consumers rather than all consumers.

Muhammad Ramulia Siregar, Imran Lubis, Arief Budiman, Budi Budi

The development of blockchain technology, especially Non-Fungible Tokens (NFT), has created challenges for investors in determining the right investment value. This study aims to develop a decision support system using the Weighted Aggregated Sum Product Assessment (WASPAS) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess NFT as an investment alternative. The research process involves several stages, including problem identification, problem analysis, literature study, data collection, and data analysis. The criteria used in assessing NFT include price, owner/origin, format, rarity, and industry, each with a set weight. After collecting data on various NFTs, a decision matrix is ​​constructed and normalized to reflect the performance of each alternative. The WASPAS and TOPSIS methods are used to assign preference values ​​to each NFT alternative based on their proximity to the positive and negative ideal solutions. The analysis results show that NFT named "Video Clip" (A3) has the highest value with a preference of 0.671, followed by "Song" (A5) with a value of 0.445, and "Book" (A2) with a value of 0.465. Meanwhile, "Selvie Photo" (A4) and "Photo" (A1) have the lowest preferences of 0.196 and 0.189, respectively. This study contributes to NFT investment decision making, by providing a systematic and data-driven approach that can reduce risk and maximize potential profits for investors. The combination of WASPAS and TOPSIS methods offers a comprehensive framework for NFT valuation, so that it can be adopted by investors and NFT platform developers in evaluating the value of digital assets more effectively.

Sudriyanto Sudriyanto, Mochammad Faid, Kamil Malík, Ahmad Supriadi

Amid the highly volatile fluctuations in the cryptocurrency market, the ability to accurately predict Bitcoin prices becomes crucial for investors and financial analysts. This study aims to develop a predictive model using Long Short-Term Memory (LSTM) Neural Networks, a specific form of recurrent neural network, to predict Bitcoin prices. Historical data on daily closing prices of Bitcoin from 2015 to 2023 was used to train and test the model. Following data preprocessing, which included normalization and the creation of a time series dataset, the LSTM model was constructed with two LSTM layers and two dense layers to enhance the predictive analysis. The model was trained with the data split into 80% for training and 20% for testing. Results show that the LSTM model was able to produce fairly accurate predictions with a low loss value on the test data. Further evaluation through comparison with baseline models showed significant improvements in predictive accuracy. This research demonstrates the potential application of advanced machine learning techniques in financial analysis, particularly in predicting the prices of highly volatile assets like Bitcoin. With continuous improvements to the model architecture and parameter optimization, Bitcoin price predictions could become more reliable, helping stakeholders make more informed investment decisions.

Chrisna Satya Wardhana

This research aims to comprehensively explore the fundamental factors that influence cryptocurrency price volatility, and apply them to adoption, regulation and investment strategies. The fundamental factors explained include supply, demand, mining activity, transaction fees, block size, blockchain technology, and context mechanisms. This research uses a qualitative and quantitative approach with literature study and secondary data analysis. The research results show that cryptocurrency price volatility is significantly influenced by the interaction of supply and demand, mining activity as reflected in the hash rate, as well as transaction costs and block size in the blockchain network. Additionally, blockchain technology and the context mechanisms used also contribute to price volatility. High price volatility hinders the use of cryptocurrencies as a stable medium of exchange and investment instrument.

Ferry Mulyanto, Ayi Purbasari

Penelitian ini merupakan sebuah langkah maju dalam upaya meningkatkan efisiensi dan transparansi dalam manajemen rantai pasokan dengan memperkenalkan sebuah inovasi berbasis teknologi blockchain. Dalam latar belakangnya, paradigma tradisional dalam manajemen rantai pasokan sering kali dihadapkan pada tantangan koordinasi yang kompleks dan informasi yang rentan terdistorsi, yang dapat mengakibatkan kesalahan transaksi dan ketidakjelasan dalam proses. Untuk mengatasi permasalahan ini, kami mengusulkan pendekatan baru dengan menerapkan arsitektur berbasis blockchain, yang menjanjikan keunggulan dalam desentralisasi dan distribusi informasi. Tujuan dari penelitian ini adalah untuk menguji efektivitas solusi ini dalam meningkatkan transparansi dan kinerja rantai pasokan secara keseluruhan. Metode penelitian kami melibatkan pengembangan dan implementasi sistem blockchain yang terintegrasi dalam rantai pasokan yang ada, diikuti dengan pengujian dan evaluasi kinerja solusi ini. Hasil dari pengujian menunjukkan penurunan yang signifikan dalam kesalahan transaksi dan peningkatan tingkat transparansi real-time, memberikan bukti konkret tentang keberhasilan inovatif solusi ini. Dengan menerapkan teknologi blockchain, kami berhasil mengubah paradigma manajemen rantai pasokan dan membuktikan nilai tambahnya dalam mengatasi tantangan yang ada. Meskipun demikian, kami mengakui bahwa penelitian ini memiliki keterbatasan, terutama dalam hal generalisasi hasil ke sektor rantai pasokan yang lebih luas. Oleh karena itu, penelitian ini menjadi titik awal untuk penelitian lanjutan dan pengembangan solusi yang lebih holistik dalam meningkatkan efisiensi dan transparansi rantai pasokan global.

Eleazer Gottlieb Julio Sumampouw, Irwan Sembiring

ABSTRAK Penelitian mengenai Analisis Verifikasi Proof of Stake (PoS) NFT dengan Teknologi Smart Contract, yang dilakukan melalui metode eksperimental, menghasilkan pencapaian yang sesuai dengan tujuan penelitian. Peneliti berhasil mengembangkan dan menjalankan sistem sesuai dengan tujuan yang diinginkan. Beberapa pencapaian utama mencakup implementasi berhasil dari proses verifikasi PoS, serta proses Stake, Unstake, dan Claim yang menggunakan integrasi Web3 dan dompet Metamask. Rekam transaksi dengan akurat mencatat waktu pengirim dan penerima bersama dengan prosedur verifikasi pemilik. Lebih lanjut, penelitian ini menyajikan analisis perbandingan antara Proof of Work (PoW) dan Proof of Stake (PoS). Temuan penelitian menunjukkan keunggulan Proof of Stake (PoS) dalam efisiensi waktu transaksi, biaya transaksi yang lebih rendah, peningkatan keamanan melalui pemilihan validator yang cermat, dan ketahanan terhadap berbagai jenis serangan. Secara keseluruhan, penelitian ini mengukuhkan keefektifan dan keunggulan implementasi Proof of Stake (PoS) dalam konteks Non-Fungible Tokens (NFTs) menggunakan Smart Contract. ABSTRACT The research on the Analysis Verification of Proof of Stake (PoS) NFT Smart Contract Technology, conducted through experimental methods, has yielded successful outcomes aligning with the research objectives. The researcher has successfully developed and executed the system, achieving the intended goals. Key accomplishments include the successful implementation of the PoS verification process, as well as the Stake, Unstake, and Claim processes, utilizing Web3 and Metamask wallet integration. Transaction records accurately capture the timing of sender and receiver actions, alongside owner verification procedures. Furthermore, the research presents a comparative analysis between Proof of Work (PoW) and Proof of Stake (PoS). The findings underscore the superiority of Proof of Stake (PoS) in terms of transaction time efficiency, lower transaction costs, enhanced security through meticulous validator selection, and resilience against various types of attacks. Overall, the research substantiates the efficacy and advantages of implementing Proof of Stake (PoS) in the context of Non-Fungible Tokens (NFTs) using Smart Contracts.

Teuku Isnaini, Boihaki Boihaki

This research presents an in-depth review of the Non- Fungible Tokens (NFTs) phenomenon in the context of Era 5.0. With a focus on understanding, trends, and implications, this research introduces the basic concepts of NFTs as well as the history of their development in decentralized digital ecosystems. Through a comprehensive qualitative approach, this research analyzes related literature, reveals current trends in the use of NFTs, and highlights their economic, cultural, and social implications. This research methodology includes literature studies, market data analysis, and interviews with industry experts. The research results show that NFTs are making a significant impact in the digital economy, opening up new opportunities for digital content monetization, and uniquely recognizing ownership rights. Although adoption of NFTs is increasing, we also identified challenges such as inequality of access and environmental impacts that need to be addressed. It is hoped that the results of this research will provide valuable insight for academics, practitioners and policy makers in understanding the role and potential of NFTs in the context of continuing technological and economic developments.

Nycholas Liunardo, Didik Gunawan, Neni Murniati

The purpose of this study is to test the ability of the Autoregressive Integrated Moving Average (ARIMA) model to predict the Ethereum value which fluctuates greatly due to the Rusian and Ukraine War. The population in this study is daily closing price data for the period May 2021 to May 2022, so the sample in this study is 396 data time series data. The results showed that the best ARIMA model for predicting the Ethereum value was ARIMA (1,1,0). ARIMA (1,1,0) can predict the Ethereum value pretty good because the value of the forecasting results is not much different from the actual value. This is also evidenced by the results of the accuracy test using MAPE which has a result of 0,448 which means the accuracy of forecasting is 55,2%.

Salah Eddine Bellal, Seyf El Islam Bousiouda, Abelhamid Dekhinet

This article specializes in the implementation of Blockchain generation in deliver chain control in Algeria, with the aim of improving transparency and security of operations. The article highlights the importance of supply chains for local businesses and the global economy, introducing the decentralized architecture and secure capabilities of blockchain's distributed ledger. The work implements blockchain technology in supply chain management in Algeria, with a view to improving transparency and security of operations. We begin by highlighting the importance of blockchain as a key business priority and its potential to reshape the future of business through the process of reform and reconstruction. Next, we present an extensive overview of the advantages and limitations of blockchain technology. By analyzing its advantages and disadvantages, we also look at existing solutions to address these drawbacks. Finally, a use case is presented to validate this technology in the pharmaceutical sector in Algeria.

Rizwan Nurfalah, Habi Baturohmah, Rieska Rahayu Ayuningsih

Di era sekarang teknologi sudah semakin pesat berkembang dalam berbagai sektor, salah satu peningkatan yang cukup signifikan yaitu hadirnya mata uang digital dengan teknologi blokchain yang membawa perubahan dalam pergerakan ekonomi dengan membawa nama cryptocurrency. Pada penelitian ini betujuan untuk mengukur data tingkat akurasi indikator Exponential Moving Average dalam analisis teknikal mata uang digital cryptocurrency. Penelitian ini mengambil data mata uang digital cyrptocurrency Bitcoin periode 2017 – 2023 sebagai objek penelitian yang dilakukan. Hasil penelitian tingkat akurasi indikator Exponential Moving Average pada Bitcoin selama periode 2017 – 2023 adalah mendapatkan tingkat akurasi sebesar 53.33 % dengan mengetahui tingkat akurasi dalam mengambil keputusan untuk melakukan penjualan dan pembelian maka sebagai investor dapat meminimalisir resiko dalam berinvestasi.

Muhammad Akhif

LPMP West Sumatra is a company in the technical implementation department of the Ministry of Education and is led by leadership and is responsible to the Director General for Improving the Quality of Educators and Education Personnel (PMPTK). The selection process for hiring contract employees has difficulties because the system is still manual where all the processes from the initial stage of registration selection to the final stage of registration selection are all done manually so it takes quite a long time and is troublesome and drains a lot of energy and energy for the company management. . So there is a need for an online selection information system for contract employee recruitment at LPMP West Sumatra such as a decision support system. This Decision Support System (DSS) uses the Simple Multi Attribute Rating Technique (SMART) method. The SMART method is a decision-making method for handling multi-criteria problems based on calculating the criteria weights for each alternative. The aim of this decision support system was to be able to assist the selection process for hiring contract employees at LPMP West Sumatra quickly, precisely and accurately. The results obtained by the alternative with the name of the prospective contract employee were Ririn Novrianti with a score of 0.755. This helps West Sumatra LPMP leaders in determining prospective contract employees who meet the requirements for employment

Alfin Abdilah, Putri Anggun Sari, Ananto Tri Sasongko

This research is motivated by the difficulty of the Lazy Minting NFT process in the Rarible Marketplace. The NFT Lazy Mining process on the Rarible Marketplace can be said to be inefficient because the process still has to be done one by one. Not to mention other problems that arise such as wrong numbering and typing errors or typos. This resulted in the Lazy Minting NFT process on the Rarible Marketplace becoming less effective. This problem will make it difficult for NFT creators if they have a large number of digital works. Therefore, this research aims to build an automated NFT Lazy minting system on the Rarible Marketplace on the Ethereum Blockchain using AutoIt, so that the NFT Lazy minting process on the Rarible Marketplace becomes more effective and efficient. The method used in the development of the Lazy Minting NFT automation system in the Rarible Marketplace is Agile Development. This research resulted in a Lazy minting NFT automation system on the Rarible Marketplace on the Ethereum Blockchain. The conclusion of this study is that the application of this system is able to make the NFT Lazy mining process on the Rarible Marketplace more effective and efficient. This can make it easier for NFT creators in their NFT sales process.

Agustina Agustina, Andreani Caroline Barus

This research was conducted to determine the impact of the crisis caused by Russia and Ukraine on the condition of various war instrument investments, such as the stock market represented by the JCI and the Nasdaq Index, world gold prices, crypto assets such as bitcoin, Ethereum, ripple as well as against the US dollar. From these results, it is hoped that later the most stable investment instrument can be found when there is a crisis shock, so that it can provide input to investors to be able to make the safest investment. The study was conducted testing the difference between pre- and post-war conditions of Russia-Ukraine. The test uses a Wilcoxon test that is adjusted to the normality test results. Based on the tests carried out, it shows that there is a difference between the Stock Market (JCI); Stock Market (NASDAQ); Dollars; Crypto (Bitcoin); Crypto (Ethereum); Crypto (Ripple); World Gold before (Pre) with after (Post) Russia-Ukraine War.

Julianto Julianto

The purpose of this research is to describe and explain the latest developments in NFT which are digital assets that can be owned digitally using blockchain technology where the blockchain system maintains ownership and certificates of NFT Tokens including spying on every transaction and ownership of NFTs. NFT allows a digital work/asset to be owned by all users as long as the asset does not change hands to other users, because NFT can be transferred by the original voters. NFTs can be in the form of works of art, such as game assets, photos, videos, music, and so on. NFT can be traded or auctioned in many existing NFT marketplaces, such as opensea, rarible, axie infinity. The selling price of the NFT depends on subjective factors such as the quality, creativity and reputation of the artist. The more unique, interesting, an NFT work and well-known creator, the higher the value of the NFT token price will be. The way NFT works is that its digital data storage system will allow users to transfer data confidentially to each other, through encryption schemes in cryptography, so that data cannot be confidential and owned by other users, because they do not own the data

Bryan Yafet Widiawira, Fajar Syaiful Akbar

Penelitian ini bertujuan untuk menganalisa perbandingan kinerja Bitcoin, indeks saham LQ45, dan emas spot sebagai instrumen investasi menggunakan variabel pengukuran kinerja return, risk, Sharpe, Treynor, dan Jensen. Jenis penelitian ini merupakan kuantitatif. Populasi yang digunakan merupakan harga penutupan bulanan dari Bitcoin, indeks saham LQ45, dan emas spot. Teknik pemilihan sampel adalah purposive sampling yang berjumlah 72 data untuk masing-masing instrumen investasi Bitcoin, indeks saham LQ45, dan emas spot selama periode 1 Januari 2017-31 Desember 2022. Teknik analisa data yang digunakan adalah uji Kruskal-Wallis. Hasil penelitian ini menunjukkan bahwa Bitcoin, indeks saham LQ45, dan emas tidak memiliki perbedaan yang signifikan terkait return, sedangkan pada aspek risk, Sharpe, Treynor, dan Jensen terdapat perbedaan yang signifikan. Selain itu, instrumen investasi dengan kinerja return, risk, Sharpe, dan Treynor tertinggi dimiliki oleh Bitcoin, sedangkan pada pengukuran kinerja Jensen dengan nilai tertinggi dimiliki oleh indeks saham LQ45. Simpulan pada penelitian ini adalah kinerja instrumen investasi terbaik dimiliki oleh Bitcoin. Penelitian ini diharapkan dapat dijadikan sebagai sumber referensi dan bahan pertimbangan bagi para investor atau masyarakat secara umum dalam memilih instrumen investasi.

Didik Gunawan, Indriana Febrianti

The purpose of this study is to test the ability of the ARIMA model to predict the value of Ethereum, especially during economic shocks such as the current COVID-19 pandemic. The population in this study is Ethereum value weekly data for the period January 2017 to December 2020, so there are 208 samples in this study. The results showed that the use of the ARIMA method in predicting the value of Ethereum got poor results, where the forecast value was very much different from the actual value. This is evidenced from the results of the accuracy test using MAPE which got a result of 51.94%. On the other hand, the economic conditions that are experiencing uncertainty due to the COVID-19 pandemic and the emergence of deficit (decentralized finance) in early 2021 have pushed up a very significant increase in the value of Ethereum so that the error standard is higher and reduces the ability of the ARIMA model to predict the value of Ethereum. Further research is recommended to use a more advanced model such as the Autoregressive Fractionally Integrated Moving Average (AFRIMA) in order to obtain a better forecast value.

Abdillah Arif Nasution, Iskandar Muda, Yasara Ulfah, Erlina Erlina · 5 authors

Purpose : This study examines the impact of labor input, construction costs, and building permits on production construction. Theoritical Framework : Nowadays, construction projects are growing. Construction projects require serious management because the larger the project, the more complex the dependence on one job to another in order to achieve the desired results. Design/Methodology/Approach : The secondary data explore from European data obtained from Eurostat from 2016 to 2019. Analyzing and proving hypotheses using Smart PLS software. Findings : The labor input has impact on production construction. The Construction Cost and Building Permits are not impcat to the Production Construction. Efforts to increase business creation should be a development priority in Europe. This is not only related to efforts to achieve the demographic bonus, but also efforts to achieve increased welfare for the Europe community. Research implication : Regional revenue is money that goes into the regional treasury. In implementation of decentralization, regional revenues consist of revenue and financing. Regional income is a recognized right of local government as in the period concerned, while regional financing is all revenues that need to be paid back and/or expenses that will be received back, either in the relevant fiscal year as well as in other fiscal years next. Practical implication : There is potential for the development and energy sources, increasing mastery of technology and quality of human resources, development of strategic industries, increasing sector between European and non-European countries. Social implication : The construction sector is one sector that can create jobs and encourage the transfer of technology that is useful for social aspects. Originality/Value : Enhancement productivity and quality of human resources to be important factor in the effort to reach the potential bonus demographics in Europe. In an effort to achieve demographic bonus opportunities, then in European countries it is expected focus on improving job creation and business for the population young age due to the number of young people which is relatively less. If this population group has the ability increase revenue and productivity, then the country's economy can be improved which in turn can promote growth economy in achieving the demographic bonus in future.