Dirgantara, Muhammad Ihsan
Unknown Affiliation

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Klasifikasi Adopsi Berbasis Kecerdasan Buatan pada UMKM di Indonesia Menggunakan Algoritma Random Forest Dirgantara, Muhammad Ihsan; Sepriansyah, Fakhri; Izzatul Maula, Nulry; Daffazka, Farhan; Ditha Tania, Ken; Meiriza , Alsella
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp35-44

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in the Indonesian economy; however, digital transformation based on artificial intelligence (AI) remains a significant challenge. This study aims to classify AI adoption among MSMEs in Indonesia using the Random Forest algorithm and to identify the factors that influence it. The dataset was obtained from the Zenodo repository, consisting of questionnaire results regarding AI adoption in MSMEs. The research stages included data cleaning, encoding, splitting the data into training (80%) and testing (20%) sets, implementing the Random Forest algorithm, evaluation, and result analysis. The evaluation results show an accuracy of 80.3% with an ROC-AUC of 0.884. The weighted precision, recall, and F1-score values are 81.2%, 80.3%, and 80.4%, respectively. These evaluation results indicate that the Random Forest algorithm performs well on this dataset. Furthermore, the feature importance analysis revealed several influential variables in AI adoption among MSMEs, including strategic decision-making (10.9%), digital leadership (8.3%), and respondent position (7.8%). In conclusion, the implementation of the Random Forest algorithm demonstrates strong performance in classifying AI adoption among MSMEs in Indonesia and highlights key influential variables such as strategic decision-making, digital leadership, and respondent position.
Perancangan Knowledge Management System Berbasis Website Menggunakan Model SECI untuk Mendukung Knowledge Sharing Guru pada SMP Bina Karya Dirgantara, Muhammad Ihsan; Sepriansyah, Fakhri; Izzatul Maula, Nurly; Daffazka, Farhan; Ditha Tania, Ken; Yamani, Zaqqi
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp112-126

Abstract

The design of a website-based Knowledge management system (KMS) using the SECI model at SMP Bina Karya is motivated by several problems, including knowledge that remains stored individually with each teacher, the unavailability of centralized learning materials and lesson plans (RPP), and the difficulty faced by substitute teachers in delivering lessons when replacing the main teacher who is absent. The Knowledge management system serves as a solution to document, distribute, and prevent the loss of knowledge, while also acting as a medium to enhance the culture of knowledge sharing among teachers. The design method used is a qualitative approach consisting of data collection through observation, interviews, and literature studies, identification of knowledge management using the SECI model, system requirements analysis, system design, and testing using Focus Group Discussion (FGD). This study produces a website-based KMS equipped with features such as user account management, substitute teacher schedule management, learning material management, lesson plan management, and discussion forums. The results of the FGD testing show an average acceptance rate of 94.2% for all developed features, with the substitute teacher schedule management feature serving as the main differentiator that successfully addresses the specific problems at SMP Bina Karya.