Evidence map›Paper›PMID 38360895›Full record

ArticleScientific reports2024

The improvement of block chain technology simulation in supply chain management (case study: pesticide company).

Lina Gozali, Helena Juliana Kristina, Andrew Yosua, Teuku Yuri M Zagloel, Maslin Masrom, Sani Susanto, Harto Tanujaya, Agustinus Purna Irawan, Ariawan Gunadi, Vikas Kumar and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
9.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 3 countries.

Lina GozaliIndustrial Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia. linag@ft.untar.ac.id.
Helena Juliana KristinaIndustrial Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia.
Andrew YosuaIndustrial Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia.
Teuku Yuri M ZagloelIndustrial Engineering Department, Universitas Indonesia, Depok, Indonesia.
Maslin MasromRazak Faculty of Technology and Informatics, Universiti Teknologi Malaysia Kuala Lumpur, Kuala Lumpur, Malaysia.
Sani SusantoIndustrial Engineering Department, Universitas Katolik Parahyangan, Bandung, Indonesia.
Harto TanujayaMechanical Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia.
Agustinus Purna IrawanMechanical Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia.
Ariawan GunadiDepartment of Law, Universitas Tarumanagara, Jakarta, Indonesia.
Vikas KumarFaculty of Business, Law and Social Sciences, Birmingham City University, Birmingham, UK.
Jose Arturo Garza-ReyesCentre for Supply Chain Improvement, University of Derby Business School, Derby, UK.
Tji Beng JapFaculty of Information Technology, Universitas Tarumanagara, Jakarta, Indonesia.
Frans Jusuf DaywinIndustrial Engineering Department, Universitas Tarumanagara, Jakarta, Indonesia.
Tarumanagara University · IDBirmingham City University · GBParahyangan Catholic University · IDUniversity of Derby · GBUniversity of Indonesia · IDUniversity of Kuala Lumpur · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research was conducted on industrial agriculture in Indonesia. Risk analysis was carried out based on previous research. One source of risk was obtained, namely raw materials that did not meet specifications, which was then proposed to be mitigated by evaluating supplier performance. This activity involves a lot of data, requiring efficient and effective data storage and access. The level in the simulation layout includes analysing system needs, using problem diagrams, compiling activity diagrams, deciding subprocesses, and filtering information. The analysis is carried out by comparing the use of supply chains with Blockchain and without Blockchain, which is then obtained to determine whether there is an increase. A sequentially stored data scenario describes a situation when the transaction process is in progress and is stored sequentially according to the process that occurs. Storing data in groups explains a problem when a transaction has been completed and stored in groups with similar data, making it easier to track specific data. In this regard, a simulation will be carried out using a website, namely a blockchain demo. The design stage starts with identifying system requirements, creating use case diagrams, compiling activity diagrams, determining subprocesses, and selecting information. The simulation results obtained will be analysed to determine the feasibility of Blockchain as a means of supporting risk mitigation related to data using aspects, including security, trust, traceability, sustainability, and costs.

Indexed as

BlockchainPesticide industryRisk mitigationSimulationSupply chain management

Identifiers

PMID38360895
PMCPMC10869690
OpenAlexW4391842854

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.