Sutte Indicator: an approach to predict the direction of stock market movements

The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). To see a comparison of the level of reliability prediction, the stock data were compared using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE). The result of this research is that Sutte Indicator can be used as a reference in predicting stock movements, and if it is compared to other indicator methods (SMA and MACD) via MAD, MSE, and MAPE, the Sutte Indicator has a better level of reliability

ROLE OF PUBLIC ACCOUNTANTS TO THE SUCCESS OF TAX AMNESTY IN FINANCIAL INSTITUTIONS AND BANKING IN INDONESIA

ABSTRACT PMK No. 118/2016 provides an opportunity for taxpayers whether or not to participate in tax amnesty, to improve compliance. How to report the property that has not been listed, both in the statement of wealth and annual tax notification. This phenomenon motivates empirical evidence on the role of the accounting firms for the success of tax amnesty in financial institutions and banking in Indonesia. The period of this research is done during the implementation of tax amnesty policy, 2016. The results show that public accountants have an important role in the implementation of tax amnesty policy in Indonesia. Future research can observe the same thing in other sectors and test the antecedent and the impact tax amnesty. Key Words: Public Accountant, Big Four, Tax Amnesty, Financial Institutio

SIMULATION OF NEUTRON INSPECTION TECHNIQUES BASED ON LASER-PLASMA NEUTRON BEAM AND FIRST EXPERIMENTS WITH CF SOURCE

openThis thesis is devoted to laser-plasma acceleration technology with an aim to produce the neutron source to foresee the use of neutron beams for addressing volumetric inspection of cargo container in order to provide the feasibility for custom border inspection on seaports and airports. We tried to significantly improve the system for simultaneous detection of hazardous and illicit materials. Neutron beams interact with the samples under study, inducing the emission of characteristic gamma radiation. The analysis of the emitted radiation allows retrieving the composition of a large variety of materials, avoiding visible damage or changes in the chemical composition. Many of these techniques have relied on massive and expensive radiation sources (e.g. particle accelerators) for several decades. In the last years, the advent of a new generation of ultra-short and super-intense lasers of higher intensities of 10 19 W/cm 2 paved the way for the exploration of new laser plasma interaction scenarios. Among the others, laser-driven particle acceleration, consisting in the production of high-energy electrons and ions. When a laser pulse is focused on a solid target, is attracting increasing attention in the scientific community. Indeed, the compact size and multi-particle nature of laser-based accelerators make them attractive for applications in several fields, from astrophysics to medical science. However, the applicability of laser-driven radiation sources to the elemental analysis of materials remains substantially unexplored. Therefore, the goal of this thesis work is to address the possibility of neutron productions by exploiting laser-driven particle acceleration mechanism for materials characterization, using neutron-in and gamma-out reactions. To this aim, we provide the brief detail for neutrons production in laser plasma acceleration using fusion and portable laser driven acceleration in target normal sheath acceleration (TNSA) mechanism using d(d,n)He, 7Li(p,n)4Be, 3Li(d,n)4Be reactions. Neutrons produced from these nuclear reactions are used in order to characterize the target object for materials identification. Geant4 simulation was made in an experimental approach. First, to make laser-driven neutron sources suitable for the mentioned applications. Then neutrons produced were used to characterize the numerous illicit and explosives materials that can be mixed and diluted to create countless varieties, the majority of which are made up entirely of the components H, C, N, and O. Lastly, the simulation was performed with an radioactive neutron source and results were obtained to test on basis of a proof-of-principle experiment in laboratory. The outcomes of this study confirms that materials characterization can be performed with the neutron produced from laser facilities. The predictions made from 252 Cf neutron source shows that 252 Cf source emits high-energy correlated neutrons and gammas, making it a valuable interrogation source. Major problem of this source is, it cannot be turned off, and emits radiation continually. This limits their use to small experiments that depends on constant neutron flux without pulsed emission. Therefore, it may be advantageous to switch on and off the interrogating source, laser driven fusion neutron sources are practically suitable since they lack intrinsic gamma-neutron correlations.This thesis is devoted to laser-plasma acceleration technology with an aim to produce the neutron source to foresee the use of neutron beams for addressing volumetric inspection of cargo container in order to provide the feasibility for custom border inspection on seaports and airports. We tried to significantly improve the system for simultaneous detection of hazardous and illicit materials. Neutron beams interact with the samples under study, inducing the emission of characteristic gamma radiation. The analysis of the emitted radiation allows retrieving the composition of a large variety of materials, avoiding visible damage or changes in the chemical composition. Many of these techniques have relied on massive and expensive radiation sources (e.g. particle accelerators) for several decades. In the last years, the advent of a new generation of ultra-short and super-intense lasers of higher intensities of 10 19 W/cm 2 paved the way for the exploration of new laser plasma interaction scenarios. Among the others, laser-driven particle acceleration, consisting in the production of high-energy electrons and ions. When a laser pulse is focused on a solid target, is attracting increasing attention in the scientific community. Indeed, the compact size and multi-particle nature of laser-based accelerators make them attractive for applications in several fields, from astrophysics to medical science. However, the applicability of laser-driven radiation sources to the elemental analysis of materials remains substantially unexplored. Therefore, the goal of this thesis work is to address the possibility of neutron productions by exploiting laser-driven particle acceleration mechanism for materials characterization, using neutron-in and gamma-out reactions. To this aim, we provide the brief detail for neutrons production in laser plasma acceleration using fusion and portable laser driven acceleration in target normal sheath acceleration (TNSA) mechanism using d(d,n)He, 7Li(p,n)4Be, 3Li(d,n)4Be reactions. Neutrons produced from these nuclear reactions are used in order to characterize the target object for materials identification. Geant4 simulation was made in an experimental approach. First, to make laser-driven neutron sources suitable for the mentioned applications. Then neutrons produced were used to characterize the numerous illicit and explosives materials that can be mixed and diluted to create countless varieties, the majority of which are made up entirely of the components H, C, N, and O. Lastly, the simulation was performed with an radioactive neutron source and results were obtained to test on basis of a proof-of-principle experiment in laboratory. The outcomes of this study confirms that materials characterization can be performed with the neutron produced from laser facilities. The predictions made from 252 Cf neutron source shows that 252 Cf source emits high-energy correlated neutrons and gammas, making it a valuable interrogation source. Major problem of this source is, it cannot be turned off, and emits radiation continually. This limits their use to small experiments that depends on constant neutron flux without pulsed emission. Therefore, it may be advantageous to switch on and off the interrogating source, laser driven fusion neutron sources are practically suitable since they lack intrinsic gamma-neutron correlations

Ferrocenylmethylchalcogenolate reagents for THE PREPARATION OF NOVEL GROUP 11/16 POLYNUCLEAR CLUSTERS

The preparation of Silylated ferrocenylmethyl chalcogen reagents CpFe(η5- • C5H4CH2ESiMe3 [E = S (D, Se (2)] in good yield is presented. These ligands were designed to have an alkyl spacer between the cyclopentadienyl group of ferrocene and the chalcogen atom that would act as an insulating bridge. Reactions of (1) or (2) with group 11 metal salts afforded single crystals of [Cu3(SCH2Fc)3(PPh3)3] (3), [Ag48S6(SCH2Fc)36] (4), [Ag10(SCH2Fc)ι0(PPh3)4] (5) and [Ag8(SeCH2Fc)8(PPh3)4] (6) that were suitable for X-ray analysis. Cyclic voltammetry experiments were conducted on {3) and (4) where single pseudo-reversible oxidation waves were observed at all scan rates and after repetitive cycles. No evidence of bond cleavage or communication between iron centres and chalcogen atoms was observed suggesting that the alkyl spacer acts as an insulating bridge

Application of machine learning to support self-management of asthma with mHealth

While there have been several efforts to use mHealth technologies to support asthma management, none so far offer personalised algorithms that can provide real-time feedback and tailored advice to patients based on their monitoring. This work employed a publicly available mHealth dataset, the Asthma Mobile Health Study (AMHS), and applied machine learning techniques to develop early warning algorithms to enhance asthma self-management. The AMHS consisted of longitudinal data from 5,875 patients, including 13,614 weekly surveys and 75,795 daily surveys. We applied several well-known supervised learning algorithms (classification) to differentiate stable and unstable periods and found that both logistic regression and naïve Bayes-based classifiers provided high accuracy (AUC > 0.87). We found features related to the use of quick-relief puffs, night symptoms, frequency of data entry, and day symptoms (in descending order of importance) as the most useful features to detect early evidence of loss of control. We found no additional value of using peak flow readings to improve population level early warning algorithms

Creating Space in a Busy and Complex System- Exploring the Factors that Impact how EPs Support Teachers with Work Related Stress

Excessive levels of stress as a consequence of high workload continues to be the primary reason why teachers leave their profession. Despite the ability that Educational Psychologists (EPs) have to work with schools to support mental health and well-being, EPs are not routinely commissioned by schools to undertake activities that supports teachers to manage work related stress. This study sought to explore the factors that impacted how EPs worked with teachers to reduce stress. The study did this by exploring the views of Special Educational Needs Co-ordinators (SENCos) and EPs. The research employed a mixed method approach, which combined qualitative and quantitative data in two distinct phases of data collection. A total of 49 SENCos and 56 EPs were recruited for the study. Phase one of the study involved EPs and SENCos completing an online questionnaire. Data from the first phase of the study was then analysed to inform the follow up semi-structured interviews which would form the second phase of the study. A total of five EPs and five SENCos were recruited for the second phase of the study. Findings from both phases of the study confirmed that EPs and SENCos believed that teachers continued to be overly stressed due to high workload, and that the Covid-19 pandemic had exacerbated teacher stress. SENCo uncertainty of the EP role, and the limited access that schools have to EPs, were cited as significant barriers impeding SENCos from commissioning EPs to do work that would reduce teacher stress. The key findings are extensively discussed in the final chapter, and implications for both policy and practice are outlined as a result. The study concludes that EPs should be afforded a greater role in supporting teachers to reduce and manage stress. However, the study argues that equal consideration needs to be given to the systems and processes that cause teachers’ stress in the first place

A STUDY ON LITERACY AND USAGE BEHAVIOUR OF CREDIT CARDS USERS IN INDIA

Purpose of the study: This study aims to find credit card literacy (henceforward CCL) and credit card usage behavior (henceforward CCUB) in India. Methodology: A survey was conducted on 400 respondents who were using a credit card in India. The questionnaire used for collecting data consisted of three sections; demographic information, CCL, and CCUB. To check the CCL, the customers were asked to rate their awareness of the terms and conditions of the credit card providers, while CCUB was measured using five questions. Main findings: CCL is found to be 34% and the results of logistic regression show that CCL and demographic factors influence the CCUB. Implications of this study: An understanding of the CCUB will be helpful in controlling excessive debt and high-interest payments. Novelty/Originality of this study: This paper gives a unique insight into CCL and CCUB in India

The Relationship Between Prior Knowledge and Creative Thinking Ability in Chemistry

This study aims to determine the relationship between prior knowledge with creative thinking ability of students in grade XI science at public school of Takalar. This research is ex post facto. The population in this research is was all students in grade XI science at public school of Takalar consisting of 39 classes with a total enrollment in 1537 people. Technique collecting sample using stratified purposive random sampling and selected grade XI Science SMAN 1 Takalar, SMAN 3 Takalar, SMAN 1 Polongbangkeng Selatan, and SMAN 3 Polongbangkeng Utara consist of 134 learners. The data was collected by using prior knowledge test consist of 16 items (α = 0.883) and verbal creativity test consist of 18 items (α = 0.808). Data were analyzed using correlation and regression analysis, The coefficient correlation between the two variables is 0.619 with p = 0.000 (p <0.05). This value indicates that there is a relationship between prior knowledge with creative thinking ability in chemistry and relationship between the two variables is a positive relationship

sutteForecastR: Forecasting Data using Alpha-Sutte Indicator

The alpha-Sutte indicator (alpha-Sutte) was originally from developed of Sutte indicator. Sutte indicator can using to predict the movement of stocks. As the development of science, then Sutte indicator developed to predict not only the movement of stocks but also can forecast data on financial, insurance, and others time series data. https://cran.r-project.org/web/packages/sutteForecastR/index.htm