Optimization of the Automatic Bell System of STMIK Kaputama with Time Control Based on Smartphone Using Nodemcu
Why this work is in the frame
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Bibliographic record
Abstract
This research aims to design and implement an Internet of Things (IoT)-based automatic bell system integrated with a smartphone using the ESP32 microcontroller. The background of this study is the limitation of the previous automatic bell system at STMIK Kaputama, which had unclear sound quality and lacked flexibility in scheduling. The developed system utilizes the RTC DS3231 for time management, the DFPlayer Mini for audio playback, and the Blynk application as a remote control interface. The research method includes hardware design, software development, and system functionality testing The results show that the system operates according to the class schedule with clearer sound output, can be controlled via a smartphone, and supports the concept of an efficient and modem smart campus. Therefore, this system can be an effective solution to optimize the time management of academic activities on campus.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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