scholarly journals Analisis Pangsa Pasar Beberapa Merek Produk Minuman Susu Fermentasi dalam Kemasan dengan Metode Rantai Markov di Lingkungan Kampus Universitas Udayana

2019 ◽  
Vol 7 (4) ◽  
pp. 561
Author(s):  
Keisa Az-zahra ◽  
A. A. P. A. Suryawan Wiranatha ◽  
Luh Putu Wrasiati
Keyword(s):  
Markov Chain ◽  
Market Share ◽  
Fermented Milk ◽  
Primary Data ◽  
Markov Chain Method ◽  
Stable Conditions ◽  
Products Analysis ◽  
Milk Market ◽  
Average Consumption

The objectives of this research were to determine the consumer characteristics of fermented milk products, analysis market share of several packaged fermented milk brands at this time until next five years ahead and determine the long-term market balance at Udayana University. The data used in the study was primary data collected through a questionnaire, for analysis this research was using the markov chain method by software QM 5.3. The result of the characteristics consumers of fermented milk were dominated by women with an average age 21-25 years old and mostly profession are students, with an average spending money for snacks/drinks was Rp 100,000-300,000/month with an average consumption of fermented milk 2-3 times/week. The reason of respondents consuming fermented milk was because of the taste was so special and respondents also get the information from advertisements on television, respondents usually buy the products from supermarkets on their own initiative by planning them first. The result of the research market share analysis was Yakult brand always leads market share, in the 2019 the Yakult brand was 55%, Cimory 30%, Calpico 8%, Vitacharm 4% and other brands 3%. in 2020 there was an increase for Yakult to 56%, a decrease for Cimory 29.5%, Calpico 7.5%, Vitacharm 3.9% and other brands rising to 3.1%. In 2021 only for Yakult change to 56.1% and Vitacharm 3.8%. In 2022 all brands were still in the same percentage but in 2023 Yakult change to 56.2% and Vitacharm 3.7%. The market share will reach stable conditions where the market share of each brand was Calpico 7.0%, Cimory 25.7%, Vitacharm 3.4% and Yakult 60.6% and other brands 3.3%. Keywords: fermented milk, market share, markov chain method

scholarly journals ANALISIS PERPIDAHAN PENGGUNAAN MEREK SIMCARD DENGAN PENDEKATAN RANTAI MARKOV

2018 ◽  
Vol 7 (1) ◽  
pp. 56
Author(s):  
NURMA ALIYUWANINGSIH ◽  
I WAYAN SUMARJAYA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Markov Chain ◽  
Market Share ◽  
Data Transfer ◽  
Transition Probabilities ◽  
Internet User ◽  
Equilibrium Conditions ◽  
Probabilistic Information ◽  
Brand Switching ◽  
Markov Chain Method ◽  
Usage Data

The aim of this research is to know the displacement made by consumers of GSM cards and predictions of market share when reaching equilibrium conditions for each of the displacements made by consumers of GSM cards. This research uses Markov chain method. Markov chain method produces probabilistic information that can be used to assist for making decision. In Markov’s analysis, the equilibrium conditions are conditions in which the variables in the system ultimately bring the transition probabilities in stable or unchanged conditions. Data from this research is divided into two categories namely data about brand switching of GSM cards and data about the transfer of GSM cards brand usage. Data brand switching of GSM cards obtained from users who use one GSM cards, while the data transfer use of GSM cards obtained from user more than one GSM cards. The results of this research indicate that GSM card displacement equilibrium conditions was achieved in the 9th period, whereas the results of switching the use of GSM card shows that equilibrium conditions for phone and SMS users is in the 15th period, and equilibrium conditions for internet user is reached in 5th period.

scholarly journals Markov Chain and Techno-Economic Analysis to Identify the Commercial Potential of New Technology: A Case Study of Motorcycle in Surakarta, Indonesia

2018 ◽  
Author(s):  
Wahyudi Sutopo ◽  
Indah Kurniyati ◽  
Roni Zakaria
Keyword(s):  
Markov Chain ◽  
Economic Analysis ◽  
Market Share ◽  
New Technology ◽  
Lithium Ion ◽  
Economic Feasibility ◽  
Commercial Potential ◽  
Markov Chain Method ◽  
Technology Market

LiFePO4 (LFP) or Lithium-ion battery with its advantages compared to common current motorcycle battery is an appropriate alternative in substituting wet and dry cell battery. Huge amount of demand of motorcycle along with the battery in Indonesia also make it an interesting product for business. In order to assess the commercial potential for such a new technology, market share needs to be estimated as well as the techno-economic feasibility. Hence, market share prediction using the residents of Surakarta Region and techno-economic analysis using NPV, IRR and PBP indicators have been conducted in this study. Calculation using markov chain method shows that LFP battery tends to dominate the market after certain period. Techno-economic analysis also figures out that the commercialization is feasible in three conditions - first mover, even with market leader and equilibrium point. Therefore, there is a great commercial potential for LFP battery especially in Indonesia.

Evaluating the Financial Performance Through ‘Consumer Centric Decision’ Approach in Pharmaceutical Companies of Bangladesh: a Business Planning Perspective

2017 ◽  
Vol 9 (1) ◽  
pp. 168
Author(s):  
Md Mostafizur Rahman ◽  
Mahmud Uz Zaman
Keyword(s):  
Market Share ◽  
Swot Analysis ◽  
Financial Analysis ◽  
Pharmaceutical Companies ◽  
Short Term ◽  
The Public ◽  
Investment Choice ◽  
Good Investment ◽  
Business Analysis

Pharmaceuticals agglomerations consistently use their brand image and versatile product portfolios to consolidate their position in the financial sector, which is evident in their continuous profit making and expansion in market share. This paper explores the short-term and long-term investment attractiveness through ‘consumer centric decision’ approach in two selected pharmaceutical companies, Renata Limited and Orion Pharma Limited, of Bangladesh over the last three years’ period. This research adopts a systematic approach which primarily addresses the various concerns of investors to illustrate the decision-making process of the existing and future investors. Using primarily domestic transaction data, this study explores how the leading pharmaceuticals companies of Bangladesh effectively use the wide array of drug portfolios mix with appropriate branding techniques to increase their financial profit and market share simultaneously. Both SWOT analysis and Porters Five Forces Model explore the business analysis of Renata Limited in compare to Orion Pharma Limited that provides a conclusion regarding investors’ decision to invest in Renata Limited. Considering the financial analysis, Renata’s financial liquidity is not very satisfactory and could have been improved further if management is prudent on financial strategy settings. Findings of the business analysis indicate that Renata Limited would be a good investment choice for existing and prospective shareholders based on its opportunities for long term and short term growth and further expansion in developing the market. The results suggest that even lower liquidity coupled with higher interest borrowings can be balanced by posing positive picture to the public shareholders by returning the positive dividend to them.

UGLEO: A WEB BASED INTELLIGENCE CHATBOT FOR STUDENT ADMISSION PORTAL USING MEGAHAL STYLE

2018 ◽  
Vol 23 (3) ◽  
pp. 175-191
Author(s):  
Anneke Annassia Putri Siswadi ◽  
Avinanta Tarigan
Keyword(s):  
Markov Chain ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Information Need ◽  
Web Based ◽  
Markov Chain Method ◽  
Information Center

To fulfill the prospective student's information need about student admission, Gunadarma University has already many kinds of services which are time limited, such as website, book, registration place, Media Information Center, and Question Answering’s website (UG-Pedia). It needs a service that can serve them anytime and anywhere. Therefore, this research is developing the UGLeo as a web based QA intelligence chatbot application for Gunadarma University's student admission portal. UGLeo is developed by MegaHal style which implements the Markov Chain method. In this research, there are some modifications in MegaHal style, those modifications are the structure of natural language processing and the structure of database. The accuracy of UGLeo reply is 65%. However, to increase the accuracy there are some improvements to be applied in UGLeo system, both improvement in natural language processing and improvement in MegaHal style.

scholarly journals A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran

2021 ◽  
Vol 13 (5) ◽  
pp. 949
Author(s):  
Salman Qureshi ◽  
Saman Nadizadeh Shorabeh ◽  
Najmeh Neysani Samany ◽  
Foad Minaei ◽  
Mehdi Homaee ◽  
...  
Keyword(s):  
Urban Growth ◽  
Integrated Approach ◽  
Physical Growth ◽  
Support Vector ◽  
Markov Chain Method ◽  
Physical Expansion ◽  
Hierarchy Process ◽  
The City

Due to irregular and uncontrolled expansion of cities in developing countries, currently operational landfill sites cannot be used in the long-term, as people will be living in proximity to these sites and be exposed to unhygienic circumstances. Hence, this study aims at proposing an integrated approach for determining suitable locations for landfills while considering their physical expansion. The proposed approach utilizes the fuzzy analytical hierarchy process (FAHP) to weigh the sets of identified landfill location criteria. Furthermore, the weighted linear combination (WLC) approach was applied for the elicitation of the proper primary locations. Finally, the support vector machine (SVM) and cellular automation-based Markov chain method were used to predict urban growth. To demonstrate the applicability of the developed approach, it was applied to a case study, namely the city of Mashhad in Iran, where suitable sites for landfills were identified considering the urban growth in different geographical directions for this city by 2048. The proposed approach could be of use for policymakers, urban planners, and other decision-makers to minimize uncertainty arising from long-term resource allocation.

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

scholarly journals Calibration of Transition Intensities for a Multistate Model: Application to Long-Term Care

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 37
Author(s):  
Manuel L. Esquível ◽  
Gracinda R. Guerreiro ◽  
Matilde C. Oliveira ◽  
Pedro Corte Real
Keyword(s):  
Markov Chain ◽  
Continuous Time ◽  
Long Term Care ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Chain Model ◽  
Chain Process ◽  
Term Care ◽  
National Network

We consider a non-homogeneous continuous time Markov chain model for Long-Term Care with five states: the autonomous state, three dependent states of light, moderate and severe dependence levels and the death state. For a general approach, we allow for non null intensities for all the returns from higher dependence levels to all lesser dependencies in the multi-state model. Using data from the 2015 Portuguese National Network of Continuous Care database, as the main research contribution of this paper, we propose a method to calibrate transition intensities with the one step transition probabilities estimated from data. This allows us to use non-homogeneous continuous time Markov chains for modeling Long-Term Care. We solve numerically the Kolmogorov forward differential equations in order to obtain continuous time transition probabilities. We assess the quality of the calibration using the Portuguese life expectancies. Based on reasonable monthly costs for each dependence state we compute, by Monte Carlo simulation, trajectories of the Markov chain process and derive relevant information for model validation and premium calculation.

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