The implementation of Markov chain to predict market share smartphone customers in Surabaya during pandemic COVID-19 / Hilyatun Nuha ... [et al.]
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the second quarter of 2019, smartphone shipments in Indonesia reached the highest figure in history, which was 9.7 million units according to a market research Indonesia Digital Conference (IDC). The smartphone competition in Indonesia continues to increase drastically in 2018. Samsung survived on the top position with a market share of 25.4% followed by Xiaomi 20.5%, Oppo 19.5% and Vivo 15.9%. The four smartphone brands are the biggest market share smartphone in Indonesia. In this summary, this research will propose market share prediction for each smartphone brand in Surabaya up to 2023 using Markov Chain. This research will identify factors in the selection of smartphone brands. Then we will determine the weight of each factor using Analytical Hierarchy process (AHP). Finding the right marketing strategy with the expectation that smartphone vendor can maintain and increase the volume of sales of its products so that it can reach the desired market share. The purpose of this research is to be able to provide suggestion for smartphone businesses in Surabaya.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it