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Currently, the industrial field has entered the revolution era 4.0. This era is marked by rapid globalization and the combination of information and communication technology with conventional technology to significantly improve production efficiency and customer service. One area of industry that is currently developing is the textile field. Indonesia has one of its flagship textiles, namely, Batik. Batik has different motives in each region, one of which is monumental batik typical of the area of Semarang. But making batik is still made by conventional methods. Based on the development of industry 4.0, making batik motifs can be improved by using 3D printing as the latest technology in the batik industry.

3D batik motifs are produced by the triangle mesh method.

In this research, Web-based applications are produced to produce 3D batik motifs with triangular mesh and batik ordering based on the designed batik designs

We can make 3D batik motifs, especially monumental building in Semarang

The open and distance learning system implemented in Universitas Terbuka (UT) requires students to do self-learning, individually or in groups. Therefore, the students of UT must be able to motivate themselves to self-study and use their time effectively. The use of integrated learning media as one of the learning resources can support them in their learning activities. The use of internet, as a part of e-Learningbased Learning Preparation, is one way for students to perform learning activities. In the study group, students can use the internet services provided in mobile telecenters and local government offices. The implementation result of this model in Kepulauan Seribu, a group of islets located in the Jakarta Bay, in which the sample were taken from students living in Pramuka Islet, Harapan Islet, Tidung Islet, Panggang Islet, Untung Jawa Islet, and Pari Islet, showed that e-Learning-based Learning Preparation Model can motivate distance students to actively study in their groups. Due to geographical constraints of those islets, it is difficult to meet their peers in groups frequently. Using the regularly scheduled study groups and the computers connected to the internet, students can easily access the information and minimize the frequency of transportation for face-to-face meetings. About 70% of the students have accessed the learning resources through internet and get experiences and knowledge during eight months period of the study in 2006.

This study examines the volatility of inflation in Indonesia before and during COVID-19, focusing on people’s purchasing power. The high inflation variability makes future price expectations uncertain, creating risks in the long run and uncertainty in wealth redistribution. The ARIMA model was used from January 2005 to June 2020. The results show that the ARMA (0.1) model is suitable for testing inflation volatility in Indonesia. Forecasting results show that inflation for the next six months will still be under pressure due to COVID-19.

The purpose of this viewpoint paper is to show practical post COVID-19 observations as lessons for the future of tourism destination management and help inspire the tourism industry and academic community.

This paper is based on observations by, and discussions among, both international and Indonesian tourism experts and relate to the case of the famous UNESCO World heritage site, the Borobudur temple, in Indonesia.

As a result, the authors observed the following measures that have been taken by the local authorities; setting limits to the amount of visitors, increase the visitor area, provide guided tours only, work with price mechanism, mitigate the physical impacts of visits and involve the local community in the value chain. The paper shows that the COVID pandemic has unintentionally created urgency and an opportunity for the local authorities to deal with already ongoing and structural overtourism related issues. This demonstrated that a lockdown was needed to get out of a lock-in.

This paper fits in the ongoing debate on the effects of COVID-19 pandemic on the tourism sector. As it provides a practical case, the values of this paper lie in bridging the gap between conceptual contributions to the debate and practical observations. Also many links with the continuation of the overtourism debate are made.

The purpose of this paper is to know the relevance between the changes in non-taxable income with the receipt of Income Tax Article 21, Income Tax Article 25/29, the receipt of value added tax and the receipt of luxury sales tax r (PPnBM).

Changes in non-taxable income have potentially reduced the receipt of Income Tax Article 21, Income Tax Article 25/29 of individual taxpayers, otherwise it increased value added tax and luxury sales tax receipts. This study used the descriptive qualitative approach, by conducting a simple case study based on actual data. Data analysis technique used is descriptive statistics and comparison analysis. Research conducted at the Kantor Wilayah Direktorat Jenderal Pajak Jawa Timur II.

The results show that the changes of non-taxable income in 2013 and 2015 did not affect the receipt of Income Tax Article 21 but the growth is slowed, while the receipt of Income Tax Article 25/29 increased.

Value added tax and luxury sales tax receipts, increasing every year, slowed down in 2013, but increased higher in 2015.

Thirteen computer codes developed by eleven groups are applied to the benchmark problem 20 (3‐D static force problem) for the TEAM Workshop. The solutions are compared with each other and with experimental results.

The purposes of this research are to investigate the relationship between strengths, weaknesses, opportunities and threats (SWOT) and development strategy and the relationship between development strategy and the success of Koperasi Unit Desa (KUD).

The sample population in this research is a village cooperative (KUD) that is located in the Indragiri Hulu Regency region. Withdrawal of the sample that is selected in this research is conducted by using the random sample method that is graded proportionately. This is done because this research has a homogeneous objective (Nazir, 1983, p. 346) and the sample retrieved is as much as 31 village cooperatives (KUD). The analysis method that is used to answer the research hypothesis is path analysis, which consists of two regression equations, namely, the influence of the variables of strength (X1), weakness (X2), opportunity (X3) and threat (X4) on the development strategy (Y1) variable and the influence of the development strategy (Y1) variable on the success of village cooperative (KUD) (Y2) variable by the hypothesis that is presented in a conceptual diagram.

The SWOT variable has a significance influence on the development strategy variable in the cooperative in Indragiri Hulu Regency, Riau Province, either partially or simultaneously. And among the variables, the development strategy variable has a significant influence on the success of village cooperative (KUD) in Indragiri Hulu Regency, Riau Province. Also, it was found that the SWOT variable has an indirect influence on the success of village cooperative (KUD) in Indragiri Hulu Regency, Riau Province.

To the authors’ knowledge, this is the first paper to test the relation between SWOT and the development strategy and the performance of village cooperatives in Indragiri Hulu Regency, Indonesia.

Cryptocurrency markets are gaining popularity, with over 23,000 cryptocurrencies in 2023 and a total market valuation of 870.81 billion USD in 2023. With its increasing popularity, cryptocurrencies are also susceptible to volatility. Predicting the price with the least fallacy or more accuracy has become the need of the hour as it significantly influences investment decisions.

This study aims to create a dynamic forecasting model using the ensemble method and test the forecasting accuracy of top 15 cryptocurrencies’ prices. Statistical and econometric model prediction accuracy is examined after hyper tuning the parameters. Drawing inferences from the statistical model, an ensemble model using machine learning (ML) algorithms is developed using gradient-boosted regressor (GBR), random forest regressor (RFR), support vector regression (SVR) and multi-layer perceptron (MLP). Validation curves are utilized to optimize model parameters and boost prediction accuracy.

It is found that when the price movement exhibits autocorrelation, the autoregressive integrated moving average (ARIMA) model and the ensemble model performed better. ARIMA, simple linear regression (SLR), random forest (RF), decision tree (DT), gradient boosting (GB) and multi-model regression (MLR) ensemble models performed well with coins, showing that trends, seasonality and historical price patterns are prominent. Furthermore, the MLR approach produces more accurate predictions for coins with higher volatility and irregular price patterns.

Although the dataset includes crisis period data, anomalies or outliers are yet to be explicitly excluded from the analysis. The models employed in this study still demonstrate high accuracy in predicting cryptocurrency prices despite these outliers, suggesting that the models are robust enough to handle unexpected fluctuations or extreme events in the market. However, the lack of specific analysis on the impact of outliers on model performance is a limitation of the study, as it needs to fully explore the resilience of the forecasting models under adverse market conditions.

The present study contributes to the body of literature on ensemble methods in forecasting crypto price in general, potentially influencing future studies on price forecasting. The study motivates the researchers on empirical testing of our framework on various asset classes. As a result, on the prediction ability of ensemble model, the study will significantly influence the decision-making process of traders and investors. The research benefits the traders and investors to effectively develop a model to forecast cryptocurrency price. The findings highlight the potential of ensemble model in predicting high volatile cryptocurrencies and other financial assets. Investors can design the investment strategies and asset allocation decisions by understanding the relationship between market trends and consumer behavior. Investors can enhance portfolio performance and mitigate risk by incorporating these insights into their decision-making processes. Policymakers can use this information to design more effective regulations and policies promoting economic stability and consumer welfare. The study emphasizes the need for using diversified model to understand the market dynamics and improving trading strategies.

This research, to the best of our knowledge, is the first to use the above models to develop an ensemble model on the data for which the outliers have not been adjusted, and the model still outperformed the other statistical, econometric, ML and deep learning (DL) models.

加密貨幣市場越來越受歡迎; 於2023年,不同種類的加密貨幣為數已超過23,000種; 同年,它們的總市場估值為八千七百零八點壹億美元。雖然加密貨幣越來越受歡迎,但它們仍然容易受到波動性的影響。預測謬誤減至最少的價格或作出更準確的價格預測就成為某些特定時刻的首要事項,這是因為投資決策會顯著地受到這些預測的影響。

研究人員擬以集成學習方法來創造一個動態預測模型,並以此模型測試預測15個頂尖加密貨幣價格的準確性。 研究人員調校超參數後,便審查統計及計量經濟學模式的預測準確性。研究人員基於從統計模式作出的推斷,研製一個使用機器學習算法的集成模型。研究人員在研製這個集成模型時,使用了梯度提升迴歸變量、隨機森林迴歸、支持向量迴歸和多層感知器。 驗證曲線被用來優化模型參數,以及提高預測的準確性。

研究人員發現,當價格變動展示自相關時,差分整合移動平均自我迴歸模型和集成模型會表現得更好; 另外,若使用加密貨幣,差分整合移動平均自我迴歸模型、簡單線性迴歸、隨機森林、決策樹、梯度提升和多模型迴歸集成模型會有良好的表現。再者,就波動性較高和價格模式不規則的加密貨幣而言,採用多重線性迴歸的方法會使預測更為準確。

據我們所知,這是首個研究,以上述的各個模型來研發一個集成模型,而這個集成模型,雖建基於異常值並未調整的數據,但它的表現卻比其它的統計、計量經濟學、多重線性和深度學習等的模型更為優良。

The primary objective of the study is to explore and elucidate the relationship between spirituality and workplace performance. This study aims to fill a gap in the existing literature by presenting a theoretical–methodological framework that incorporates various aspects and research propositions, differentiating them based on specific mediating variables.

This research uses a systematic literature review methodology, analyzing 95 articles published over 20 years (2002–2022). This approach is designed to collate and synthesize evidence supporting the proposed relationship between spirituality and workplace performance and to understand the nuances of spirituality’s influence on performance.

The systematic review reveals recurring mediating constructs and various established theoretical–empirical relationships between spirituality and workplace performance throughout the study period. It highlights the significant role of spirituality in enhancing worker well-being, engagement and productivity.

This study addresses the impacts on societal views of work, employee well-being and organizational culture, especially considering the growing discussions around holistic and spiritually inclusive workplaces.

This paper introduces originality by presenting a theoretical–methodological framework that emphasizes five distinct research propositions. These propositions, rooted in a comprehensive literature review, provide insights into how spirituality might influence workplace performance through various mediating variables.

The purpose of this paper is to analyze the influence of factors that affect human resource competency (HRC) 4.0, employee readiness for transformational change as well as analyzing the mediating and moderating factors that influence the relationship of factors such as soft skills training and individual characteristics on employee readiness for transformational change and HRC 4.0.

This research is a quantitative research with descriptive statistics. The analytical tool used is a structural equation model of partial least squares (PLS). This research was conducted at five Bank Indonesia Offices in Aceh and North Sumatra Provinces. Using a proportional random sampling technique, 200 respondents of employees were selected.

The results of this study are as follows: (1) both soft skill training and individual characteristics have a significant effect on HRC 4.0; (2) HRC 4.0, soft skill training and individual characteristic have a significant on employee readiness for transformational change; (3) soft skill training has significant effect on employee readiness for transformational change through HRC 4.0; (4) individual characteristic has a significant effect on employee readiness for transformational change through HRC 4.0; (5) the effect of HRC 4.0 on employee readiness for transformational change moderates by transformational leadership; (6) the effect of HRC 4.0 on employee readiness for transformational change moderates by employee commitment to change.

This research contains valuable novelty, which is a new concept of HRC 4.0 that is linked to soft skill training and individual characteristics variables, and employee readiness for transformational change. Furthermore, transformational leadership and employee commitment variables have significant effect in moderating the influence off HRC 4.0 on employee readiness for transformational change.