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All Journal Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Educational Science (IJES) Indonesian Journal of Community Services Klasikal: Journal of Education, Language Teaching and Science JOLLT Journal of Languages and Language Teaching Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Indo-MathEdu Intellectuals Journal TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Media Bina Ilmiah English Language, Linguistics, and Culture International Journal (ELSTIC-IJ)
Heri Alfian
Universitas Sembilanbelas November Kolaka
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Social Sciences Other

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Empowerment Of Msmes In Hakatutobu Village Through Artificial Intelligence-Based Digital Marketing Training Khartha, Aqzhariady; Alfian, Heri; A. Bohang, Muthmainnah Bahri; Dakka, Litha Nesidekawati; Wirawati, Nur; Nasir, Syarif Hidayat; Marhamah, Marhamah; Putra, Eko
TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Vol 6, No 1 (2026): April
Publisher : UNIVERSITAS MUHAMMADIYAH MATARAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/transformasi.v6i1.39265

Abstract

This community service aimed to empower seafood processing Micro, Small, and Medium Enterprises (MSMEs) in Hakatutobu Village through digital marketing training and the utilization of Artificial Intelligence (AI). The lack of digital marketing skills and technological limitations were the main obstacles faced by partners in expanding market reach. The method employed was Participatory Action Research (PAR) combined with hands-on training for 25 participants. The core material focused on AI prompting literacy to generate effective copywriting and promotional designs. Success was measured by comparing pre-test and post-test scores and paired sample t-test. Quantitative results showed an average increase in participants' understanding of 55% (from 50.0 to 77.5), which was proven statistically significant (p < 0.001). Qualitatively, participants were able to produce their first digital promotional content. The evaluation instrument comprised 20 items assessing five digital marketing competency indicators, with face validity confirmed by expert review. The PAR approach engaged partners iteratively through planning–action–reflection cycles rather than one-way training. These findings indicate that the AI-based hands-on intervention produced a statistically significant and practically meaningful improvement in MSMEs’ digital marketing competence, enabling local processed seafood products to reach a broader market.
BERT-Based Grammatical Error Analysis in Indonesia Senior High School Essays Tundreng, Syarifuddin; Alfian, Heri; Kartika, Parsya; Nisa, Azka Airin
JOLLT Journal of Languages and Language Teaching Vol. 14 No. 2 (2026): April
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jollt.v14i2.18551

Abstract

In high-resource languages, automated grammatical error detection has rapidly evolved; however, there are still few technologies that are comparable for Bahasa Indonesia, especially in secondary school settings. Although spelling, morphology, syntax, and diction are common problems for Indonesian senior high school students, AI-assisted feedback systems specifically designed for Indonesian writing are still in their infancy. The use of IndoBERT-base for grammatical error analysis in 82 senior high school student essays totaling 10,911 words is examined in this work. Following two expert raters' hand annotation, 1,872 grammatical mistakes were found in four different categories. Prior to analysis utilizing a refined IndoBERT-base model, the essays underwent pre-processing procedures including as tokenization, normalization, and alignment with gold-standard annotations. F1-score, which is calculated by comparing predicted labels with teacher-validated error tags, accuracy, precision, and recall were used to assess the model's performance. The model demonstrated good agreement (80%) with human raters and correctly identified 1,594 mistakes, yielding a detection rate of 85.1%. Due to their contextual and semantic complexity, syntax and diction showed reduced accuracy, whereas spelling and morphology identification showed especially good performance. These results suggest that automated grammatical analysis of Indonesian student writing can be successfully supported by transformer-based models. Nonetheless, shortcomings in managing discourse-level interdependence underscore the ongoing significance of human assessment. The study supports the incorporation of hybrid human–AI feedback systems to improve writing teaching in the classroom and advances the development of AI-assisted grammar tools for Indonesian education.
Co-Authors A. Bohang, Muthmainnah Bahri Alifiah Pratiwi Alifiah Pratiwi Aqzhariady Khartha Azis, Awalia Bohang, Muthmainnah Bahri A. eko putra, eko Hariadi Syam Hustiana Kadaruddin Kaimuddin Karman Karman Kartika, Parsya La Ode Hasnuddin S. Sagala Litha Nesidekawati Dakka Litha Nesidekawati Dakka Marhamah Marhamah Marhamah Marhamah Muh. Nurtanzis Sutoyo Muhammad Basri Mustari, Sri Hariati Muthmainnah Bahri A. Bohang Muthmainnah Bahri A. Bohang Muthmainnah Bahri A. Bohang Netty Huzniati Andas Nisa, Azka Airin Pratiwi, Alifiah Ray Suryadi, Ray Reskiawan, Bimas - Sri Hariati Mustari sultan Sultan Sultan Syarif Hidayat Nasir, Syarif Hidayat Tundreng, Syarifuddin Wirawati, Nur Yawan, Hendri