GLOBALIZATION VS INTERNATIONALIZATION FOR ENTREPRENEURS

Di sebuah artikel pada Harvard Business Review, Theodore Levitt mempublikasikan tulisan berjudul Globalization of Markets; sebuah review aktivitas bisnis setelah menjadi sebuah topik menarik untuk akademisi dan praktisi. Topik ini juga menjadi fenomena karena argumen beliau tentang globalisasi yang merupakan sebuah konvergensi ekonomi dengan aktivitas bisnis tanpa adanya hambatan nasional. Hal tersebut kontras dengan internasionalisasi yang cenderung lebih menyempit dan berhubungan bisnis dengan bagian luar perbatasan nasional. Ide sentral yang harus dijawab oleh manajer dan para entrepreneur adalah apakah pasar mereka global atau internasional. Sebelum menjawabnya, mereka butuh pengertian dan paradigma baru tentang hal ini. Lebih lanjut, Thomas Friedman dalam bukunya ‘The World is Flat’ juga memperkuat ide Levitt dan menuliskan sebuah dunia dengan evolusi informasi dan teknologi. Era baru ekonomi ini membuka kesempatan baru dalam sudut pandang entrepreneur. Ada sebuah pintu yang terbuka lebar untuk memasuki pasar global dan lebih mudah untuk menyesuaikan perkembangan perusahaan atau bisnis baru

ANALYSIS OF MORAL VALUE IN THE MOVIE ZOOTOPIA BY RICH MOORE AND BYRON HOWARD

A movie is a form of literary work which has the main function as a means of entertainment. Apart from just being entertaining, films also have the potential as a learning tool because they provide audio and visual stimuli that can attract the attention of the audience and convey various moral values that describe the principles underlying good and bad actions. It is important for students to be introduced to and taught about these moral values so that they can understand and learn them well. This study of the moral The theme in the film Zootopia aims to explore educational possibilities that can be obtained from watching films, by utilizing visual storytelling techniques. The film acts as a medium that influences conveying information and messages to the audience so that the moral values contained in it can be understood and studied by the audience. This research aims to identify the various moral values presented in the film Zootopia and reveal the moral values implied in the narrative. This research uses library research with a qualitative descriptive method approach. The data for this research are the moral values contained in the dialogue scripts spoken by the characters when shown in the film. The data source for this research comes from the film entitled "Zootopia". Writing uses documentation techniques to collect data. Apart from that, researchers used data analysis. The findings should that the values contained in the moral values in Zootopia. By applying qualitative methodology, The main data source is the Zootopia film itself which is equipped with subtitle files. The research results show that several moral values contained in the film "Zootopia" are stories that raise several important moral values in life, including respect, justice, self�confidence, tolerance, helping each other, and altruism

PERENCANAAN SISTEM PERAWATAN MESIN DENGAN MENGGUNAKAN METODE RELIABILITY CENTERED MAINTENANCE (RCM) PADA PT. INDOPHERIN JAYA, PROBOLINGGO

The study aimed to identify the right preventive care for corrective treatment formerly used in the company. When the production process, the breakdown of the production of frequently caused by the production process operating 24 hours, and led to activities in the production process. The company has several: the boiler of a steam engine, thermal oil heater, conveyor, and chiller water. As for the data thesis research needed in this primary data conducted interviews directly with the heads of the technique, operators and mechanics. n its management will be arranged in table containing column function descriptor components and component failure of function, data - this data will be used for analysis Failure Mode and Effect Analysis (FMEA). Based on the result analysis and processing the data was already performed in pt indhoperin jaya, through a failure by both fmea analysis method known components valves expansion and be a failure for the highest of an RPN 162 and 180. Of engineering treatment with rcm keandalannya mengunnakan methods to find, reliability of expansion valves from components originally 36,8 % into 73,6 %. For the reliability of components to be 28,4 % 56,8 %

THE INFLUENCE OF SPECIAL ITEMS TO CORE EARNINGS IN EARNINGS MANAGEMENT AT MANUFACTURING COMPANIES LISTED IN JAKARTA STOCK EXCHANGE

This paper examines the classification of items within the income statement as an earnings management tool. Evidence is consistent with managers opportunistically shifting expenses from core expenses (cost of goods sold and selling, general, and administrative expenses) to special items. This vertical movement of expenses does not change bottom-line earnings, but overstates ‘‘core’’ earnings. Keywords: earnings management; earnings components; special items

Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments

The feasibility of deep neural networks (DNNs) to address data stream problems still requires intensive study because of the static and offline nature of conventional deep learning approaches. A deep continual learning algorithm, namely autonomous deep learning (ADL), is proposed in this paper. Unlike traditional deep learning methods, ADL features a flexible structure where its network structure can be constructed from scratch with the absence of an initial network structure via the self-constructing network structure. ADL specifically addresses catastrophic forgetting by having a different-depth structure which is capable of achieving a trade-off between plasticity and stability. Network significance (NS) formula is proposed to drive the hidden nodes growing and pruning mechanism. Drift detection scenario (DDS) is put forward to signal distributional changes in data streams which induce the creation of a new hidden layer. The maximum information compression index (MICI) method plays an important role as a complexity reduction module eliminating redundant layers. The efficacy of ADL is numerically validated under the prequential test-then-train procedure in lifelong environments using nine popular data stream problems. The numerical results demonstrate that ADL consistently outperforms recent continual learning methods while characterizing the automatic construction of network structures

RELATIONSHIP BETWEEN URBANIZATION AND DENGUE HAEMORRHAGIC FEVER INCIDENCE IN SEMARANG CITY

Unplanned urbanization can cause unhealthy urban environment, which in turn increases the population of mosquitoes carrying the dengue vector. Consequently, this would reduce the urban life quality because public health is an important aspect of it. The increasing incidence of Dengue Haemorrhagic Fever (DHF) in Semarang City has been alarming. In 2013, the incidence was 2,364 cases, which increased up to 89.11% from the 1,250 cases of 2012. So, it is necessary to study about what relationship is there between the level of urbanization and the incidence of DHF in Semarang. This study used quantitative and spatial approach. The unit of analysis is sub-district with time series data from 2006 to 2013. The analysis technique is spatial analysis through image interpretation, regression, and descriptive analysis. The level of urbanization has been measured through the variables of population growth, population density, land use change, and building density. The results have shown that there is no significant correlation between the level of urbanization and the incidence of dengue fever. The urbanization is acknowledged as influencing only about 28% of the DHF incidence in the city, while the other 72% has been influenced by other factors

Evolving Ensemble Fuzzy Classifier

The concept of ensemble learning offers a promising avenue in learning from data streams under complex environments because it addresses the bias and variance dilemma better than its single model counterpart and features a reconfigurable structure, which is well suited to the given context. While various extensions of ensemble learning for mining non-stationary data streams can be found in the literature, most of them are crafted under a static base classifier and revisits preceding samples in the sliding window for a retraining step. This feature causes computationally prohibitive complexity and is not flexible enough to cope with rapidly changing environments. Their complexities are often demanding because it involves a large collection of offline classifiers due to the absence of structural complexities reduction mechanisms and lack of an online feature selection mechanism. A novel evolving ensemble classifier, namely Parsimonious Ensemble pENsemble, is proposed in this paper. pENsemble differs from existing architectures in the fact that it is built upon an evolving classifier from data streams, termed Parsimonious Classifier pClass. pENsemble is equipped by an ensemble pruning mechanism, which estimates a localized generalization error of a base classifier. A dynamic online feature selection scenario is integrated into the pENsemble. This method allows for dynamic selection and deselection of input features on the fly. pENsemble adopts a dynamic ensemble structure to output a final classification decision where it features a novel drift detection scenario to grow the ensemble structure. The efficacy of the pENsemble has been numerically demonstrated through rigorous numerical studies with dynamic and evolving data streams where it delivers the most encouraging performance in attaining a tradeoff between accuracy and complexity.Comment: this paper has been published by IEEE Transactions on Fuzzy System

Evolving Large-Scale Data Stream Analytics based on Scalable PANFIS

Many distributed machine learning frameworks have recently been built to speed up the large-scale data learning process. However, most distributed machine learning used in these frameworks still uses an offline algorithm model which cannot cope with the data stream problems. In fact, large-scale data are mostly generated by the non-stationary data stream where its pattern evolves over time. To address this problem, we propose a novel Evolving Large-scale Data Stream Analytics framework based on a Scalable Parsimonious Network based on Fuzzy Inference System (Scalable PANFIS), where the PANFIS evolving algorithm is distributed over the worker nodes in the cloud to learn large-scale data stream. Scalable PANFIS framework incorporates the active learning (AL) strategy and two model fusion methods. The AL accelerates the distributed learning process to generate an initial evolving large-scale data stream model (initial model), whereas the two model fusion methods aggregate an initial model to generate the final model. The final model represents the update of current large-scale data knowledge which can be used to infer future data. Extensive experiments on this framework are validated by measuring the accuracy and running time of four combinations of Scalable PANFIS and other Spark-based built in algorithms. The results indicate that Scalable PANFIS with AL improves the training time to be almost two times faster than Scalable PANFIS without AL. The results also show both rule merging and the voting mechanisms yield similar accuracy in general among Scalable PANFIS algorithms and they are generally better than Spark-based algorithms. In terms of running time, the Scalable PANFIS training time outperforms all Spark-based algorithms when classifying numerous benchmark datasets.Comment: 20 pages, 5 figure

Hubungan elastisitas permintaan dengan usaha mikro, kecil dan menengah (UMKM) di Jawa Timur

Perkembangan ekonomi saat ini sangatlah pesat dari tahun ke tahun. Khususnya pulau jawa, salah satu pulau yang perkembangnya sangatlah pesat dibandingkan pulau pulau lainnya. Serta di provinsi Jawa Timur inilah juga merupakan provinsi yang terbilang pesat yang berada di pulau jawa. Maka dari itu, kali ini saya membuat jurnal yang akan membahas elastisitas permintaan barang yang dapat dipengaruhi oleh faktor faktor lain serta akan berhubungan dengan perkembangan usaha mikro, kecil, dan manengah (UMKM)

VIDEO STREAMING WITH GIGABIT PASSIVE OPTICAL NETWORK TECHNOLOGY

Perkembangan teknologi berpengaruh kepada kebutuhan user untuk mengakses data lebih cepat, perlahan sistem dengan menggunakan Fiber Optic mulai menggeser posisi kabel tembaga dalam transmisi data karena lebih cepat. Tren user saat ini adalah membutuhkan transmisi data yang lebih cepat dan lebih besar, seperti Video Streaming. Penelitian ini bertujuan untuk membuat system Video Streaming dengan infrastruktur GPON (Gigabit Passive Optical Network). Dalam penelitian dilakukan konfigurasi Video Streaming dengan GPON kemudian juga dilakukan dengan system Ethernet. Keduanya dibandingkan dengan parameter kecepatan dan frame rate untuk Video Streaming. Hasil yang dapat diperoleh dari penelitian dengan menggunakan system GPON adalah kestabilan untuk melakukan Streaming Video dibandingkan Ethernet