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Implementation of Management Information Systems in MSMEs Using E-Commerce Platforms Muhammad Yordan Dafarin Fadil; Aditya Ramadhan; Faisal Hairi
Escalate : Economics and Business Journal Vol. 4 No. 02 (2026): Escalate: Economics and Business Journal
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/escalate.v4i02.523

Abstract

The rapid growth of e-commerce in Indonesia, with a digital economy GMV of USD 90 billion in 2024, encourages MSMEs to adopt digital platforms as business channels. However, empirical evidence on whether e-commerce alone improves MSME performance remains mixed, and the role of Management Information Systems (MIS)-particularly accounting information systems-in this relationship is often overlooked. This article examines the contribution of MIS implementation to MSME performance through a literature review of empirically verified national and international sources (2019-2024). Results show that e-commerce's effect on MSME performance is inconsistent across studies-positive but not always significant-while the simultaneous use of accounting information systems together with e-commerce produces a more consistent positive and significant effect on performance. Key challenges include underutilized financial information systems, low cybersecurity awareness, and adoption driven more by external trading-partner pressure than internal strategic initiatives. The article concludes that MIS adoption success depends on technology, organizational readiness, and environmental factors as conceptualized in the Technology-Organization-Environment framework.
Estimasi Penyerapan Karbon di Kawasan Hutan dengan Tujuan Khusus ULM Menggunakan Metode Klasifikasi NDVI Dengan Citra Sentinel-2 MSI Aditya Ramadhan; Syam'ani Syam'ani; Ahmad Jauhari
Jurnal Sylva Scienteae Vol 9, No 1 (2026): Jurnal Sylva Scienteae Vol 9 No 1 Edisi Februari 2026
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jss.v9i1.11428

Abstract

ABSTRACT, Greenhouse gases such as carbon dioxide are significant contributors to global warming, threatening the global climate. Carbon in forest biomass has the potential to reduce GHG emissions. This research aims to develop a biomass model based on NDVI values and field data to estimate carbon sequestration in the ULM Forest Carbon Stock Area. The research utilizes two methods: NDVI and field measurements. Pre-field data management involves image management, image correction, and image clipping for NDVI analysis on the research area map. Sample point determination uses stratified and purposive sampling with a plot size of 20 m × 20 m, totaling 45 sample points. Field observation data collection at tree, pole, pile, understory vegetation, seedlings, and litter levels to assess the forest biomass potential. The research results, based on 38 samples, establish a linear regression model correlation of 715.62x-187.29 with an R2 of 0.701 and an RMSE measurement error rate of 41.72 kg/pixel, indicating an average field carbon potential of 217.11 kg/pixel. This shows the highest carbon potential in 2018 at 0.39 ton/pixel and 0.42 ton/pixel in 2022. The developed linear regression model indicates a carbon sequestration of 2585.07 tons or 1.63 tons/ha over a four-year period in the ULM Forest Carbon Stock Area.Keywords : Biomass, NDVI, Correlation, Carbon SequestrationABSTRAK. Gas rumah Kaca (GRK) seperti karbon dioksida menjadi kontributor utama pemanasan global yang mengancam iklim global. Karbon hutan dalam bentuk biomassa memiliki potensi menurukan emisi GRK. Penelitian ini bertujuan mengembangkan model biomassa antara nilai NDVI dan data lapangan sehingga mengestimasikan serapan karbon KHDTK ULM. Metode penelitian menggunakan dua metode NDVI dan pengukuran lapangan. Pengelolaan data pralapangan meliputi pengelolaan citra, koreksi citra, pemotongan citra untuk analisis NDVI pada peta wilayah penelitian. Teknik penentuan titik sampel menggunakan stratified sampling dan purposive sampling dengan ukuran plot 20 m × 20 m berjumlah 45 titik sampel. Pengambilan data hasil observasi lapangan pada tingkat pohon, tiang, pancang tumbuhan bawah, semai dan seresah untuk mengetahui potensi biomassa hutan. Hasil penelitian menunjukkan dari 38 sampel yang digunakan membangun korelasi model regresi linier yaitu 715,62x-187,29 dengan R2 (0,701) dengan RMSE tingkat eror pengukuran potensi karbon sebesar 41,72 kg/pixel, dengan rata-rata potensi karbon lapangan 217,11 kg/pixel. Menunjukkan potensi karbon terbesar tahun 2018 yaitu 0,39 ton/pixel dan tahun 2022 sebesar 0,42 ton/pixel. Model regresi linier yang dikembangkan menunjukkan penyerapan karbon KHDTK ULM sebesar 2585,07 ton atau 1,63 ton/ha dalam kurun waktu empat tahun.Kata Kunci: Biomassa, NDVI, Korelasi, Penyerapan Karbon