66 research outputs found
PENGARUH PERSEPSI KEADILAN PADA KOMITMEN AFEKTIF DAN KEPUASAN KERJA : PERAN MEDIASI KEPEMILIKAN PSIKOLOGIS DI KALANGAN KARYAWAN NON-KELUARGA PT.JOGLO SEMAR
No full textABSTRAK PENGARUH PERSEPSI KEADILAN PADA KOMITMEN AFEKTIF DAN KEPUASAN KERJA : PERAN MEDIASI KEPEMILIKAN PSIKOLOGIS DI KALANGAN KARYAWAN NON-KELUARGA PT. JOGLO SEMAR. RYAN DWI INDRAWAN F0208031 Perusahaan keluarga seringkali dikaitkan dengan budaya pendirinya, sehingga peran persepsi keadilan dan kepemilikan psikologis dirasa penting karena perusahaan keluarga memiliki beberapa aspek yang mempengaruhi ketidak adilan karyawan non-keluarga. Kurangnya persepsi keadilan karyawan non-keluarga mempengaruhi komitmen afektif dan kepuasan kerja di kalangan karyawan non-keluarga. Tujuan dari penelitian ini menyelidiki dan menguji secara empiris persepsi keadilan karyawan non-keluarga. Secara eksplisit peneliti berfokus pada mekanisme bagaimana peneliti mengarah pada komitmen afektif dan kepuasan kerja. Peneliti memperkenalkan konsep psikologis pemilik perusahaan sebagai faktor yang mempengaruhi persepsi keadilan karyawan non-keluarga dan sikap kerja mereka. Metode yang digunakan pada penelitian ini adalah deskriptif kuantitatif, dan data dalam penelitian ini diperoleh melalui penyebaran kuisioner kepada responden. Teknik pengambilan sampel dalam penelitian ini menggunakan teknik purposive sampling, yaitu dilakukan dengan mengambil sampel dari populasi berdasarkan pertimbangan (judgement) tertentu atau jatah (quota) tertentu. Kriteria sampel yang diambil yaitu karyawan PT. Joglo Semar yang bukan anggota keluarga yang minimal telah bekerja selama 1 tahun. Jumlah sampel dalam penelitian ini sebanyak 100 sampel. Uji validitas yang digunakan dalam penelitian ini adalah dengan Confirmatory Factor Analysis. Dalam mengukur reliabilitas, peneliti menggunakan teknik analisis Cronbach Alpha. Untuk pengujian hipotesis digunakan analisis regresi berdasarkan langkah-langkah yang dianjurkan oleh Baron & Kenny (1986). Dari hasil penelitian ini dapat diketahui bahwa keadilan prosedural dan keadilan distributif berpengaruh terhadap kepemilikan psikologis, sehingga kepemilikan psikologis dapat memediasi komitmen afektif dan kepuasan kerja karyawan non-keluarga PT. Joglo Semar. Penelitian ini sejalan dengan penelitian yang pernah dilakukan Phillip Sieger mengenai komitmen afektif dan kepuasan kerja karyawan non-keluarga yang meneliti peran dari persepsi keadilan dan kepemilikan psikologis. Kata kunci : Persepsi Keadilan, Komitmen Afektif, Kepuasan Kerja, Kepemilikan Psikologis ABSTRACT THE EFFECT OF PERCEIVED JUSTICE ON AFFECTIVE COMMITMENT AND JOB SATISFACTION: MEDIATING ROLE OF PSYCHOLOGICAL OWNERSHIP AMONG NON-FAMILY EMPLOYEES OF PT. JOGLO SEMAR. RYAN DWI INDRAWAN F0208031 Family-owned company is often associated with its founder, so that the role of perceived justice and psychological ownership was considered as important because family company has some aspects contributing to injustice for non-family employees. The lack of perceived justice among non-family employees affected their affective commitment and job satisfaction. The objective of research was to investigate and test empirically the perceived justice of non-family employees. Explicitly, the author focused on the mechanism of how the author concentrated on affective commitment and job satisfaction. The author introduced psychological concept of company owner as the factors affecting the non-family employees’ perceived justice and their job attitude. The method employed in this research was descriptive quantitative one and the data of research were obtained through distributing questionnaire to the respondents. The sampling technique used in this study was purposive sampling technique, the one conducting by taking the sample from the population based on certain judgment or quota. The criterion of sample taken was employee of PT. JogloSemar not member of family who had worked for at least 1 year. The sample of research consisted of 100 respondents. Validity test used in this study was Confirmatory Factor analysis. In measuring the reliability, the author employed Cronbach Alpha analysis technique. The regression analysis was used for hypothesis testing based on the procedure recommended by Baron & Kenny (1986). From the result of research, it could be found that distributive justice affected the psychological ownership, so that psychological ownership could mediate the affective commitment and job satisfaction of non-family employees in PT. JogloSemar. This study was in line with Phillip Sieger’s study on affective commitment and non-family employees investigating the role of perceived justice and psychological ownership. Keywords: Perceived Justice, Affective Commitment, Job Satisfaction, Psychological Ownershi
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Lithographic patterning of polymeric media for biotechnology applications
No full textLithographic patterning has heavily utilized in the semiconductor industry for its ability to pattern vast numbers of complex shapes down to the nanometer scale. However, only recently has this technology been employed in the biotechnology field despite the fact that most of that the most important biological components such as cells, antibodies, DNA and proteins operate at this level. This work is an exploration of the use of lithographic printing methods in two areas deeply-entrenched in biotechnology: self assembly and microarray-based manipulation of biological media. It was inspired by the natural self assembly which occurs in nature and in our bodies at all scales. The majority of this work dealt with the patterning of bioreactive copolymers into different three-dimensional microshapes which could be functionalized with single strands of DNA for subsequent sequence-specific particle assembly. This type of technology, where very small-scale matter can be directed to self assembly into programmed macrostructures in a highly-specific manner has the capability to be adapted for many next-generation applications in drug delivery, nanofabrication, biosensing, and microelectronics. A secondary technology was explored in this work involving the paired sequencing of antibody gene sequences with the aid of lithographically-patterned microarrays. This methodology represents a bridging of bottom-up fabrication methods of DNA and proteins with top-down optical fabrication techniques which is already finding increasing utility in applications such as vaccine discovery, diagnostics, and autoimmune research. Because of the versatile nature of the components of this research, it is the hope of the author that the techniques discovered and explored here provide support and inspiration for future research in the biotechnology field as well as in other fields which may benefit as well.Chemical Engineerin
INDONESIA'S DEFENSE OF SEBATIK ISLAND IN A BORDER DISPUTE BASED ON THE PRINCIPLE OF UTI POSSIDETIS
No full textIndonesia is the largest archipelagic country on the Asian continent, with more than 17,000 islands. The government has yet to identify many small and outermost islands in detail. Identifying these outer islands further emphasizes the sovereignty of the Republic of Indonesia regarding the location of the country's borders. Border areas are an essential aspect because they are a marker of a country's jurisdiction. Border areas are an arena for interactions between global and local communities that occur every day. Indonesia has several disputes with neighboring countries about the outer islands directly adjacent to it. Sebatik Island is one of the disputed islands. Meanwhile, Indonesia obtained its territory according to colonial jurisdiction. Sebatik Island which was obtained based on the Uti Possidetis principle. The research method used is normative juridical, examining library materials through norms, rules, legal principles, and doctrine. Among them are the Technical Aspects of the United Nations Convention on the Law of the Sea (TALOS) and the United Nations Convention on the Law of the Sea (UNCLOS). This paper examines Indonesia's potential to defend Sebatik Island using the Uti Possidetis principle. This principle holds that the territories of former colonies should be recognized as independent states with the same borders they had before colonization. By invoking this principle, Indonesia sought to assert its rightful claim to Sebatik Island and protect its sovereignty. Many countries have recognized this legal precedent, and have been used to resolve other border disputes worldwide
Bridging the Gap Between Secondary Education and College Level S.T.E.M. Education
No full textabstract: This research ventures to adjust the Algebra 2 Core Standards set by the Arizona Department of Education so that computer science concepts may be taught in parallel with the mathematical concepts in Algebra 2 in order to facilitate a better understanding of both subjects. The close relation to computer science and mathematics make this course possible. Students will be more prepared for university level education when they understand how technology works rather than simply how to use it. The solution is to create an online set of modules that can be taught alongside the high school mathematics course, Algebra 2. The solution contains a set of five modules that parallel with the Arizona core standards of the class. There are several obstacles that needed to be overcome in order to create online modules that would fit the needs of schools, students and teachers. This solution will reach students quickly as the hope is that it will become a requirement according to the Arizona Department of Education core standards. The course will be easily accessible to students as it is online and the course will fit into the existing education system, which would not require state laws to be passed in order to require the teaching of computer science. The goal is to bridge the gap between secondary education and college level S.T.E.M. education specifically in reference to computer science so that students start college with a strong understanding of how technology works in order to help them become more successful in the future
Distinct Feature Learning and Nonlinear Variation Pattern Discovery Using Regularized Autoencoders
No full textabstract: Feature learning and the discovery of nonlinear variation patterns in high-dimensional data is an important task in many problem domains, such as imaging, streaming data from sensors, and manufacturing. This dissertation presents several methods for learning and visualizing nonlinear variation in high-dimensional data. First, an automated method for discovering nonlinear variation patterns using deep learning autoencoders is proposed. The approach provides a functional mapping from a low-dimensional representation to the original spatially-dense data that is both interpretable and efficient with respect to preserving information. Experimental results indicate that deep learning autoencoders outperform manifold learning and principal component analysis in reproducing the original data from the learned variation sources.
A key issue in using autoencoders for nonlinear variation pattern discovery is to encourage the learning of solutions where each feature represents a unique variation source, which we define as distinct features. This problem of learning distinct features is also referred to as disentangling factors of variation in the representation learning literature. The remainder of this dissertation highlights and provides solutions for this important problem.
An alternating autoencoder training method is presented and a new measure motivated by orthogonal loadings in linear models is proposed to quantify feature distinctness in the nonlinear models. Simulated point cloud data and handwritten digit images illustrate that standard training methods for autoencoders consistently mix the true variation sources in the learned low-dimensional representation, whereas the alternating method produces solutions with more distinct patterns.
Finally, a new regularization method for learning distinct nonlinear features using autoencoders is proposed. Motivated in-part by the properties of linear solutions, a series of learning constraints are implemented via regularization penalties during stochastic gradient descent training. These include the orthogonality of tangent vectors to the manifold, the correlation between learned features, and the distributions of the learned features. This regularized learning approach yields low-dimensional representations which can be better interpreted and used to identify the true sources of variation impacting a high-dimensional feature space. Experimental results demonstrate the effectiveness of this method for nonlinear variation pattern discovery on both simulated and real data sets.Dissertation/ThesisDoctoral Dissertation Industrial Engineering 201
Data Management Behind Machine Learning
No full textabstract: This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level
An Analysis of Student Major Choice at ASU In Computer Science, Computer Systems Engineering and Software Engineering
No full textabstract: Even in the largest public university in the country, computer related degrees such as Computer Science, Computer Systems Engineering and Software Engineering have low enrollment rates and high dropout rates. This is interesting because the careers that require these degrees are marketed as the highest paying and most powerful. The goal of this project was to find out what the students of Arizona State University (ASU) thought about these majors and why they did or did not pick them. A total of 206 students were surveyed from a variety of sources including upper level classes, lower level classes and Barrett, the Honors College. Survey questions asked why the students picked their current major, if they had a previous major and why did they switch, and if the students had considered one of the three computer related degrees. Almost all questions were open ended, meaning the students did not have multiple choice answers and instead could write as short or as long of a response as needed. Responses were grouped based on a set of initial hypotheses and any emerging trends. These groups were displayed in several different bar graphs broken down by gender, grade level and category of student (stayed in a computer related degree, left one, joined one or picked a non-computer related degree). Trends included students of all grade levels picking their major because they were passionate or interested in the subject. This may suggest that college students are set in their path and will not switch majors easily. Students also reported seeing computer related degrees as too difficult and intimidating. However, given the low (when compared to all of ASU) number of students surveyed, the conclusions and trends given cannot be representative of ASU as a whole. Rather, they are just representative of this sample population. Further work on this study, if time permitted, would be to try to survey more students and question some of the trends established to find more specific answers
Random Python Program Generator for JavaScript
No full textabstract: The most important task for a beginning computer science student, in order for them to succeed in their future studies, is to learn to be able to understand code. One of the greatest indicators of student success in beginning programming courses is the ability to read code and predict its output, as this shows that the student truly understands what each line of code is doing. Yet few tools available to students today focus on helping students to improve their ability to read code. The goal of the random Python program generator is to give students a tool to practice this important skill.
The program writes randomly generated, syntactically correct Python 3 code in order to provide students infinite examples from which to study. The end goal of the project is to create an interactive tool where beginning programming students can click a button to generate a random code snippet, check if what they predict the output to be is correct, and get an explanation of the code line by line. The tool currently lacks a front end, but it currently is able to write Python code that includes assignment statements, delete statements, if statements, and print statements. It supports boolean, float, integer, and string variable types
Cheese Machines and Cellos: Technical Craftsmen and Craft Technicians
No full textThe study is based on a period of ethnographic research among approximately thirty tradesmen, apprentices, supervisors and related personnel at a medium-sized precision engineering company in Hamilton, New Zealand. The company specialises in high quality niche products and machinery for the dairy, aviation and medical technology industries. Its work involves a wide variety of engineering crafts and practices.
My aim was to better understand the work that was done there, the elements of skilled and expert practice involved in it; how these skills were learned and from whom, and what they meant to those who held them. I wanted to find out which people and what conditions and environments best enabled the acquisition of skills and a good learning experience. By way of comparison to this main group, I interviewed a smaller number of craftspeople in the wider community: a fine furniture maker, a printmaker, a ceramicist and two luthiers, all of whom worked independently.
This ethnography is located within a wider literature on apprenticeship, skill and education, and about what it means to be a “maker of things” (e.g. Beeby 1992; Biesta 2006; De Munck, Kaplan and Soly 2007; Dormer 1994, 1997; Keep 2007, 2009; Sennett 2008). I also draw on ethnographic discussions by other scholars who have described skilled practices and ways of learning in diverse social and cultural contexts (e.g. Coy 1989; Crawford 2009; Eraut 2001, 2002; Keller and Keller 1996; Lave 1988, 2011; Marchand 2003, 2010).
My ethnographic data provides a rich description of a contemporary industrial workplace where learning involves both practical and theoretical knowledge and creative ability. The findings demonstrate that successful learning on the shop floor (and in the other examples given) is the result of a complex amalgam of disparate elements. The learning and teaching in these workplaces are sometimes structured and sometimes serendipitous. They are embedded in and arise from the processes of creativity, analysis, manufacture and reflection. They involve not only what takes place at the worksites but also the qualities and dispositions and histories of learning, both formal and informal, that the participants bring to their work.
The development of skill and the acquisition of knowledge are shown to be complex and deeply personal and individual phenomena that are best nurtured in environments rich in materials, opportunity and experience, and in cooperation with interested, capable and expert “others”. This complexity is not easily represented in or catered for by current forms of educational assessment in New Zealand.
A further and largely unexpected dimension of the study was my growing awareness of my own apprenticeship as a practitioner of ethnography, including my location as a participant observer in the actual field of study. This experience invariably led me to reflect further on the processes of apprenticeship, education and learning
On the limits of engine analysis for cheating detection in chess
No full textThe integrity of online games has important economic consequences for both the gaming industry and players of all levels, from professionals to amateurs. Where there is a high likelihood of cheating, there is a loss of trust and players will be reluctant to participate — particularly if this is likely to cost them money.
Chess is a game that has been established online for around 25 years and is played over the Internet commercially. In that environment, where players are not physically present “over the board” (OTB), chess is one of the most easily exploitable games by those who wish to cheat, because of the widespread availability of very strong chess-playing programs. Allegations of cheating even in OTB games have increased significantly in recent years, and even led to recent changes in the laws of the game that potentially impinge upon players’ privacy.
In this work, we examine some of the difficulties inherent in identifying the covert use of chess-playing programs purely from an analysis of the moves of a game. Our approach is to deeply examine a large collection of games where there is confidence that cheating has not taken place, and analyse those that could be easily misclassified.
We conclude that there is a serious risk of finding numerous “false positives” and that, in general, it is unsafe to use just the moves of a single game as prima facie evidence of cheating. We also demonstrate that it is impossible to compute definitive values of the figures currently employed to measure similarity to a chess-engine for a particular game, as values inevitably vary at different depths and, even under identical conditions, when multi-threading evaluation is used
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