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Record W4280601294 · doi:10.24167/jbt.v2i1.4526

The Use of An Accounting Information System for Monitoring Website-Based Sales Call Activities in Garment Company

2022· article· en· W4280601294 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Business and Technology · 2022
Typearticle
Languageen
FieldComputer Science
TopicInformation Retrieval and Data Mining
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsRevenueProcess (computing)Sales managementAccounting information systemSales journalInformation systemBusinessComputer scienceMarketingEngineeringAccounting

Abstract

fetched live from OpenAlex

There are several ways that can be used to increase sales, one of which is using a sales call. At PT. Ricky Mumbul Daya, sales call is one of the main activities carried out to increase sales. Although the process of recording revenues and costs related to sales call activities at that company has used the system, but the process is still not optimal. This is because the data input process is only done by the cashier. Meanwhile, the monitoring process is still done manually. The purpose of this research is to create a Website-Based Accounting Information System for Sales Call Monitoring and tested whether the level of performance and effort expectations of the system has an influence on user behavioral intention. The system development method used is the System Development Life Cycle. Meanwhile, to test the level of the three variables, it will begin with collecting data with a questionnaire and then the data will be analyzed using several testing methods. The result of this research is that the information system created can complete the expected tasks and concluded that the level of performance and effort expectations of the system have an influence on the user’s behavioral intention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.231
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it