Evidence map›Paper›PMID 39968171›Full record

ArticleFrontiers in artificial intelligence2025

Strategic technological innovation through ChatMu: transforming information accessibility in Muhammadiyah.

Muhammad Syahriandi Adhantoro, Dedi Gunawan, Harun Joko Prayitno, Rahayu Febri Riyanti, Eko Purnomo, Adi Jufriansah

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Muhammad Syahriandi AdhantoroFaculty of Communication and Informatics, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia.
Dedi GunawanFaculty of Communication and Informatics, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia.
Harun Joko PrayitnoFaculty of Teacher Training and Education, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia.
Rahayu Febri RiyantiFaculty of Teacher Training and Education, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia.
Eko PurnomoFaculty of Teacher Training and Education, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia.
Adi JufriansahFaculty of Teacher Training and Education, Universitas Muhammadiyah Maumere, Maumere, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines the effectiveness of the ChatMu application in improving access to information for members of Muhammadiyah, a prominent socio-religious organization. The research employs a mixed-methods approach, combining qualitative and quantitative analyses to evaluate the application's performance, usability, and user satisfaction. Findings reveal that ChatMu significantly enhances the accessibility and accuracy of Muhammadiyah-related information, highlighting its potential as an innovative tool for addressing community-specific information needs. However, several usability challenges were identified, including navigation inefficiencies and inconsistencies in content delivery. These limitations suggest the need for further refinement to optimize user experience and functionality. Despite these issues, ChatMu demonstrates strong capabilities in providing relevant and reliable information, fostering digital literacy, and supporting information dissemination within the Muhammadiyah community. The study concludes that ChatMu represents a promising application of chatbot technology in empowering communities through improved access to knowledge. Future development efforts should focus on comprehensive usability testing, maintaining information relevance, and incorporating advanced interactive features to enhance engagement. With continuous improvements, ChatMu has the potential to become an effective medium for advancing literacy and knowledge-sharing in the Muhammadiyah community.

Indexed as

artificial intelligencechatbot technologyChatMu applicationdigital literacyMuhammadiyahsystem usability scaleuser engagement

Identifiers

PMID39968171
PMCPMC11832483

What OpenQuestion holds

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LicenceCC BY
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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.