Miracle-dz/UniFAR-FTUs huggingface dataset:
PENDAMPINGAN PENERAPAN SISTEM PEMASARAN ONLINE DAN PELAPORAN KEUANGAN SEDERHANA PADA SEKTOR USAHA KECIL DI KELURAHAN MERUYA SELATAN

Sektor usaha kecil atau Usaha Mikro, Kecil, dan Menengah (UMKM) terbukti telah mendorong dan merangsang pertumbuhan ekonomi nasional secara berkesinambungan. Penerapan sistem pemasaran online dan pelaporankeuangan sederhana pada sektor usaha kecil diperlukan untuk mendukung pengembangan dan mewujudkan UMKM yang maju, mandiri, dan modern. Kegiatan pengabdian pada masyarakat ini memberikan pelatihan kepada pelakuUMKM untuk mulai memanfaatkan internet sebagai salah satu media pemasaran produk dan pelatihan pelaporan keuangan sederhana sesuai dengan standard akuntansi. Kegiatan ini dilakukan di RPTRA Manunggal KelurahanMeruya Selatan, Kembangan, Jakarta Barat. Peserta yang hadir dalam kegiatan ini berjumlah 20 orang peserta yang merupakan pelaku usaha kecil dan menengah. Kegiatan berlangsung dengan memperkenalkan sistem pemasaranonline melalui media sosial, kemudian peserta juga melakukan penyusunan laporan keuangan sederhana sesuai dengan standar akuntansi yang berlaku. Kegiatan di akhiri dengan memberikan modul pemanfaatan media pemasaran online dan modul penyusunan laporan keuangan sederhana sesuai dengan standar akuntansi.
Strategizing Information Systems: An Empirical Analysis of IT Alignment and Success in SMEs

IT investment is a crucial issue as it does not only influence the performance in Small-Medium Enterprises (SMEs) but it also helps executives to align business strategy with organizational performance. Admittedly, though, there is ineffective use of Information Systems (IS) due to a lack of strategic planning and of formal processes resulting in executives’ failure to develop IS plans and achieve long-term sustainability. Therefore, the purpose of this paper is to examine the phases of Strategic Information Systems Planning (SISP) process that contribute to a greater extent of success so that guidelines regarding the implementation of the process in SMEs can be provided. Data was collected by 160 IS executives in Greek SMEs during February and May 2017. Multivariate Regression Analysis was applied on the detailed items of the SISP process and success constructs. The results of this survey present that managers should be aware of the strategic use of IS planning so as to increase competitive advantage. Senior executives should choose the appropriate IT infrastructure (related to their business strategy and organizational structure), so as to align business strategy with organizational structure. The findings of this paper could help IS executives concentrate their efforts on business objectives and recognize the great value of the planning process on their business.
High-performance FPGA Architecture for Data Streams Processing on Example of IPsec Gateway

In modern digital world, there is a strong demand for efficient data streams processing methods. One of application areas is cybersecurity — IPsec is a suite of protocol that adds security to communications at the IP level. This paper presents principles of high-performance FPGA architecture for data streams processing on example of IPsec gateway implementation. Efficiency of the proposed solution allows to use it in networks with data rates of several Gbit/s.
O/S-enabled on-line software-based self-test and recovery for resilient shared-memory multicore systems

As technology scales deep into the sub-micron regime, transistors become less reliable. Future systems are widely predicted to suffer from considerable aging and wear-out effects. The issue of aging and gradual degradation necessitates the use of mechanisms that can enable protection against undesired system behavior by facilitating detection, mitigation, and/or recovery from faults throughout the lifetime of the system. Recently, several on-line testing techniques have been proposed in literature enabling dynamic detection of permanent faults. Software-based Self-Testing (SBST) is an emerging new paradigm in the testing domain, which relies on the exploitation of existing available resources resident in the system. Beyond the detection of faults, modern systems must be enhanced with mechanisms able to self-repair and recover the system to a fault-free state, in order to remain functional despite the presence of permanent faults. The objectives of this work are to develop techniques for: (i) on-line fault detection, (ii) scheduling methodologies to increase the system availability during testing and (iii) enhance the system with recovery capabilities. The first part of this thesis introduces a new paradigm of SBST that performs testing at the granularity of individual microprocessor core components in multi-/many-core systems based on the utilization. In particular, we develop the DaemonGuard, a framework that enables the real-time observation of individual sub-core modules and performs on-demand selective testing of modules that have been stressed. This technique aims to reduce the testing time by avoiding the over-testing of under-utilized units. The second part investigates the relation between system test latency and test time overhead under several scheduling policies. For this part we develop an exploration framework able to identify the best scheduling policy in order to increase system availability under a given test latency constraint. Additionally, a new methodology aiming to reduce the extra overhead related to testing that is incurred as the system scales up (i.e. the number of on-chip cores increases) is integrated and evaluated under the developed exploration framework. For the last part of this thesis, we propose to enhance our framework to support fault recovery capabilities. In particular, we proix Mi ch ae l A . S ki s s pose an efficient check pointing and rollback recovery mechanism which, upon fault detection, can restore the system to the most recently valid correct state and resume the normal operation assuming disabling of the faulty core, thereby leading to a healthy (but degraded) system. All the proposed techniques are evaluated through a series of experiments using a full-system, execution-driven simulation framework running a commodity operating system and real multithreaded workloads. x Mi ch ae l A . S kit sa s
EMPLOYING ORGANIZATIONAL CAPACITY COMPONENTS IN ENHANCING CORPORATE PERFORMANCE

Purpose: Ongoing investigations on modern markets demonstrated that organizational limit structure some portion of the organization’s environment that affect its performance. Knowing its standing to the industry, a recent study inspected the effect of organizational capacity on business performance in Malaysia. The research focuses on attaining two objectives. Firstly, to analyze the perceptions of Malaysian listed companies’ directors on business capacity components. Secondly, to analyze whether different components of organizational capacity effect the performance of organizations listed in Malaysia. Methodology: A questionnaire survey and the regression analysis have been used in obtaining the data and answering the research questions respectively. Main Findings: The consequences of this study show that company structure plays an important role in manipulating the organization’s performance. Nonetheless, organizational learning was established not to explain Malaysian companies’ performance. Hence, the results assist the firm in their hunt for better performance through using suitable business resources. Implications/Applications: Recognizing organizational structure as an important organizational capacity element might improve the performance of local business in the market to withstand competitive advantage.
PRAKTIK HIGIENE DAGING DALAM PENYEMBELIHAN HEWAN QURBAN DI KOTA KUPANG

The procedure for handling sacrificed animals has been regulated in Regulation of the Minister of Agriculture - Republic of Indonesia No. 114/Permentan/PD.410/9/2014. This research aims to describe the procedure of slaughter of qurban animals in Kupang City in relation to the provision of safe, health, intact, and halal meat (ASUH). This study is a descriptive study conducted through observation and interviews with qurban committee 1438H (2017M) at two mosques in Kupang City. Assessment is done on how to produce ASUH meat. There are fifteen aspects that are qualitatively assessed, 1 point if fulfilled and 0 if not fulfilled. Total of fulfillment points was then made in a percentage. The hygiene and sanitation practice of qurban slaughter at Al Mujahidin Mosque-Penfui and Darul Hijrah Mosque-Kolhua of Kupang City is quite good with a value of 10/15 (66.67%). Some things that need to be improved are the limitation of personnel with trained people. Meat processing facilities that need to be added is table and basket for meat storage.
Genetic programming-based pseudorandom number generator for wireless identification and sensing platform

The need for security in lightweight devices such as radio frequency identification tags is increasing and a pseudorandom number generator (PRNG) constitutes an essential part of the authentication protocols that provide security. The main aim of this research is to produce a lightweight PRNG for cryptographic applications in wireless identification and sensing platform family devices, and other related lightweight devices. This PRNG is produced with genetic programming methods using entropy calculation as the fitness function, and it is tested with the NIST statistical test suite. Moreover, it satisfies the requirements of the EPCGen2 standards.
The Hidden Risks of ESG Conformity - Benefiting from the ESG Life Cycle

This paper investigates the relationship between ESG scores and stock prices. Further to previous research we add ESG revisions to the overall level of ESG scores. We propose an ESG life cycle framework, which we decompose into four clusters. Each of these clusters exhibits different characteristics with respect to ESG scores and their influence on stock returns. We find that holding portfolios solely tilted towards absolute ESG scores bears significant ESG related performance risks. In an event-study setting, we find that markets react to ESG improvements of top ranked firms with negative abnormal returns. Similarily, second-tier firms experience significant negative abnormal returns when ESG ratings are declining. Adding revisions offers a deeper insight into the return – and risk dynamics of ESG related portfolios. Not only the level of ESG scores, but also the position within the ESG cycle is of special relevance to the portfolio’s return. ESG minded investors should consider the combination of both aspects when making portfolio decisions.
Evolution of monitoring, accounting and alerting services at INFN-CNAF Tier-1

CNAF is the national center of INFN (Italian National Institute for Nuclear Physics) for IT technology services. The Tier-1 data center operated at CNAF offers computing and storage resources to scientific communities as those working on the four experiments of LHC (Large Hadron Collider) at CERN and other 30 experiments in which INFN is involved. In past years, monitoring and alerting services for Tier-1 resources were performed with several software, such as LEMON (developed at CERN and customized on the char-acteristics of datacenters managing scientific data), Nagios (especially used for alerting purposes) and a system based on Graphite database and other ad-hoc developed services and web pages. By 2015, a task force has been organized with the purpose of defining and deploying a common infrastructure (based on Sensu, InfluxDB and Grafana) to be exploited by the different CNAF depart-ments. Once the new infrastructure was deployed, a major task was then to adapt the whole monitoring and alerting services. We are going to present the steps that the Tier-1 group followed in order to accomplish a full migration, that is now completed with all the new services in production. In particular we will show the monitoring sensors and alerting checks redesign to adapt them to the infrastructure base on the Sensu software, the web dashboards creation for data presentation, the porting of historical data from LEMON/Graphite to InfluxDB.
Machine Learning Approach for Stress Detection using Wireless Physical Activity Tracker

Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. This paper provides an effective method for the detection of cognitive stress levels using data provided from a physical activity tracker device developed by FITBIT. The main motive of this system was to use a machine learning approach in stress detection using sensor technology. Individually, the effect of each stressor was evaluated using logistic regression and then a combined model was built and assessed using variants of ordinal logistic regression models including logit, probit, and complementary log-log. This system was used and evaluated in a real-time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that a stress detection system should be as non-invasive as possible for the user.
Designing Marketing Strategy Based on Value from Clothing-producing Companies Using the AHP and Delphi methods

Organizations design some strategies to win the competition. This paper discusses the design of market strategies to achieve harmony between value-based segmentation and marketing mix. The strategy's implementation starts with segmentation, targeting, and positioning. The clothing company ("M") was selected as a research object. Identification of market segments using cluster analysis while determine the target market using the AHP and Delphi method. Besides, Bull's eye research was used for product positioning. The results show that "M" customers are classified into two groups, referred Big Spenders and Discount Finders. Big Spender selected as the primary target market with a focus on size and durability. The marketing strategy focuses on Instagram and Facebook. As a result, the ads developed prototypes have proven to be better.
Role of Dividend Policy in Relation to Profitability, Liquidity and Firm Value in Non-Financial Companies in Indonesia

Good corporate value is a company achievement to increase shareholders' wealth. Investors use financial statements as one of the information to assess whether investment is feasible or not. The purpose of this study is to look at the role of dividend policy as a mediating variable between the relationship of profitability, liquidity and firm value. The population in this study was 463 non-financial companies listed on the Stock Exchange in 2014-2017 with a sample of 56 companies. The researcher used panel data regression as a data analysis technique. The results of the study show the effect of profitability, liquidity, dividend policy on firm value have a positive significant effect. In addition, profitability and liquidity influence the value of the company better if through dividend policy. This research contributes to the importance of dividend policy in relation to profitability, liquidity, and firm value for investors to make their investment decisions.
The impact of B2B value co-creation on consumer’s purchasing intentions in SE-Asia

In an increasingly competitive marketplace, consumers are presented with greater choices of services than ever before, and therefore, understanding the B2B value co-creation activities between both suppliers and consumers is of great importance. This study intends to investigate the impact of B2B value co-creation impact on consumers in South East Asia’s services industry. The research questions formulated for this paper ask what is the impact of B2B value co-creation on consumer satisfaction? Existing studies have mostly focused on examining the concept of value co-creation behavior and its impact within organizational settings, with little consideration of B2B value co- creation from consumer standpoint. Therefore, consumer approach to assessing B2B value co-creation impact on consumer provides new insights and a greater understanding on the mechanism of B2B value co-creation. Findings reveal that B2B value co-creation activities have a positive impact on consumer satisfaction in Asian services sector involved in B2B activities. Findings further show that B2B value co-creation activities have a positive effect on consumer repurchase intentions, which suggests that B2B value co-creation activities have a positive effect on consumer repurchase intention.
Simultaneous Estimation of Flexible Models and Associated Hyperparameters: An Application to Travel Activity-Duration Modeling

Estimation of flexible-statistical models of travel demand involves tuning varying parameters, hyperparameters, manually and iteratively. Proper tuning of hyperparameters results in superior models. However, considerable expertise, including technical knowledge of statistics, data mining or machine learning, and experience are required to tune hyperparameters and consequently generate appropriate models. Moreover, tuning hyperparameters is prone to subjective error and consequently produces travel demand models that are difficult to reproduce and extend, and makes the development more an art than a science. There is a need for methods to reduce or eliminate subjectivity during the tuning process. This study proposed a framework to reduce subjectivity during the tuning of hyperparameters required for the estimation of nonparametric models of activity-duration. That is, a flexible-statistical framework, which leverages state-of-the-art innovations in Bayesian optimization (BO), was proposed to estimate Gaussian process models of activity duration and associated hyperparameters. The framework was applied to estimate duration models for five types of out-of-home non-mandatory activity episodes for household individuals in the greater Los Angeles area. Experiments demonstrate that the accuracy of results from the proposed framework are superior to those from the current tuning process, and are obtained in a fraction of the time. The proposed framework could potentially increase the productivity of modelers by reducing time required to tune hyperparameters.
Fair Machine Learning

In this research an approach for bias reduction, while still maintaining usability of the classifier, is proposed. The approach for bias reduction requires all preprocessing to be done, include one-hot encoding and making the training and test set split. The approach then requires a banned feature, a feature that has for example been deemed morally irrelevant for the classification purpose. For the bias reduction, the proposal is to use the KS-score obtained from the two sample KS-test to determine how well a feature contributes to classification and how well it contributes to the bias of the banned feature. So that means that all features present in the dataset that are not the label(L) or the banned feature(B), that the following holds for feature X to be safe to use in the training dataset: KS-score(X|L=1,X|L=0) > KS-score(X|B=1,X|B=0) After all features are checked, the unsafe (or flagged) features need to be removed from both the training and the test set in order to make the classifier as fair as possible. The datasets that have been used are the Titanic dataset, with as banned feature the passenger class and a Financial survey, with as banned feature the race. The results have shown that the overall bias has been reduced for both the Titanic dataset and the Financial survey. However in terms of relative fairness, the Financial survey is the only one that became less fair for a certain banned feature value (Race = White). All other values became fairer for both the Financial survey and the Titanic dataset.
Pengaruh Bauran Pemasaran Terhadap Loyalitas Pelanggan Zoya Cabang Medan Dengan Brand Image Sebagai Variabel Moderating

Customer loyalty is customer loyalty to companies, brands and products, where this loyalty is influenced by various factors such as marketing mix, product, price, location and promotion and influenced by brand image as a moderating variable. This study aims to explain the effect of product, price, location and promotion on Zoya customer loyalty with brand image as a moderating variable. This research is quantitative research and the method to determine the sample is the Lemeshow formula with a sample size of 100 respondents. Data is obtained by distributing questionnaires that have been structured to the respondents. The data analysis technique used is the MRA (Moderating Regression Analysis). The results showed that as partially the product had a positive and significant effect on customer loyalty by 22.3%, the price had a positive and significant effect on customer loyalty by 35.7%, the location did not affect customer loyalty and promotion had a positive effect and significant to customer loyalty of 21.1%. The prices, locations and promotions simultaneously have a positive and significant effect on customer loyalty. And products, prices, locations and promotions have a positive effect on customer loyalty by moderating the brand image in Zoya Medan Branch.
E-marketing strategy: to improve customer preference for local brand over foreign brand in the era of a developing country

This research will determine the factors that influence customer preference for local brands over foreign brands in the era of a developing country. This is a quantitative research design. Questionnaires have been used to collect the data on product standards, social media engagement, local positive testimonials, brand application and brand trust. The sample size was 80 – randomly selected. Organizations should improve quality, design, compatibility, consistency, attitude and online appearance on YouTube, Facebook, Instagram, and LinkedIn. Celebrity testimonials have more influence on consumers than a non-celebrity testimonial. The research is original in that it was conducted from scratch. Moreover, the researchers sought help from previous research in the field to define technical terms, of which have been cited accordingly.
Preliminary Draft: Please do not cite or circulate without permission of the authors Pricing Strategies of Big4 and Non-Big4 Auditors in the Light of Audit Tendering

Acknowledgements: We thank Karin Brunsson, Benedikt Downar (discussant), Marc Eulerich, Jörg-Markus Hitz, Annette Köhler, Gilad Livne (discussant), Kai-Uwe Marten, Beatriz García Osma, Brandon Gipper, Angela Pettinicchio, Martin Schmidt, Arthur Stenzel, Jochen Theis, conference participants at the 10th European Auditing Research Network (EARNet) Symposium in Parma (2019) and the 2nd Swiss Accounting Research Alpine Camp (SARAC) in Andermatt (2020), as well as workshop participants at the University of Duisburg-Essen for their helpful comments and suggestions.