Analysis of the Financial Performance of the Largest Consumer Goods Company in Indonesia Before and During the Covid-19 Pandemic (Case Study at PT. Unilever Indonesia Tbk)
Why this work is in the frame
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Bibliographic record
Abstract
This research is case study research at PT. Unilever Indonesia. PT. Unilever Indonesia Tbk is the largest consumer goods company in Indonesia. The novelty of this research is original research, there has never been a case study of financial performance analysis using net profit data for the 2018 to 2021 quarter/interim reports. This research is important to do because of the phenomenon of the COVID-19 pandemic condition in consumer goods companies. This is important considering that in 2020 the COVID-19 pandemic resulted in many sectors being affected by this pandemic, including the Consumer Goods sector. The purpose of this paper is to examine an in-depth analysis of the financial performance of PT. Unilever Indonesia Tbk. The analysis was carried out by comparing the condition of financial performance before and after the Covid-19 condition, with the mean difference analysis technique. Data testing was carried out for the mean conditions of Q1, Q2, Q3 2018 and 2019 before the Covid-19 pandemic with a mean of Q1, Q2, Q3 2020 and 2021 during the Covid-19 pandemic. The hypothesis proposed is that the condition of financial performance conditions before and during the Covid-19 pandemic. The results of this research found that there was no significant difference between the financial performance of PT. Unilever Indonesia Tbk. previous to a pandemic and during the event of pandemic covid-19.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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