PENGARUH KUALITAS DAN HARGA PERUMAHAN KOTA CITRA GRAHA TERHADAP MINAT BELI MASYARAKAT
Bibliographic record
Abstract
Abstract, The main objective in this study is to examine and analyze (1) the effect of quality and price on people's buying interest in Citra Graha City housing. (2) the effect of quality on people's buying interest in Citra Graha City housing. (3) the effect of prices on people's buying interest in Citra Graha City housing. (4) To see which variable has greater influence on people's buying interest in Citra Graha City housing. The targets in this study include (1) To be able to see how much influence the two variables in this study are quality and price in influencing public buying interest in Citra Graha City housing. (2) Being a reference material for consumers to be able to determine the purchasing policy after knowing about the quality and price set by the City of Citra Graha. (3) From the results of this study, it can be used as a reference as a policy making in product pricing strategies. (4) Making the results of this research as textbook reference material, especially in the field of marketing management. This research was conducted with a quantitative method and using the analysis method with SPSS Windows For Data as a data analysis tool. To facilitate the justification, a 5-point Likert scale is used. Likert scale is a scale used in questionnaires to facilitate respondents in answering questions, then respondents answer questions in accordance with the code in the questionnaire. Before testing with regression analysis, the research data were tested with a classic assumption test consisting of: normality test, heterokedasticity test, and multicollinearity test. Then for simultaneous hypothesis testing using the F test, and for partial hypothesis testing using the t test. Meanwhile, to determine the most dominant variable affecting the level of employee job satisfaction using the standardized coefficient beta. Based on the results of the study it can be found that the variable of quality and price is very significant in influencing the buying interest of consumers or prospective consumers to be able to purchase housing units in the City of Citra Graha, this can be proven with a probability level of more than 0.05 or less than 5%. In addition to the level of probability can also be proven by table 5.8 it turns out that F count is greater (33,108) than F table (2.3092), so the decision is to reject H0 and accept Ha, which means the variables X1, X2 together affect the consumer's buying interest will the purchase of housing units in the City of Citra Graha. Job Characteristics Variable has a significant and positive effect on the level of employee job satisfaction with a significance level of 0.473 or 47.3%. This means that if the characteristics of this work are considered it will increase employee job satisfaction by 47.3%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.006 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".