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All Journal Arcitech: Journal of Computer Science and Artificial Intelligence Jurnal Semarak Mengabdi
Murlena
Universitas Pat Petulai
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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SOSIALISASI PEMBUKUAN KEUANGAN SEDERHANA PADA USAHA MIKRO KECIL MENENGAH KOPI LEGI DESA AIR PUTIH KALI BANDUNG dwi sinta; Dwita Prisdinawati; Murlena; Putri Milanda Bainamus
Jurnal Semarak Mengabdi Vol 2 No 2 (2023): Juli
Publisher : STIA Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56135/jsm.v2i2.127

Abstract

Usaha mikro kecil menengah Desa Air Putih Kali bandung pada pengelolaan kopi robusta didukung pada anggaran desa dan swadya masyarakat. Hal ini bertujuan untuk membuka lapangan pekerjaan bagi pemuda desa sehingga berperan aktiv dalam kegiatan yang positiv.Usaha rumahan yang dirancang untuk jangka panjang menekankan pada proses keberlangsungan usaha, untuk itu dibutuhkan sistem pencatatan keuangan yang tertata rapi maka perlu dilakukan sosialisasi pembukuan keuangan sederhana pada Usaha Mikro Kecil Menengah Kopi Legi Desa Air Putih Kali Bandung. Agar para pelaku usaha dapat membuat keputusan produksi yang tepat sehingga perputaran keuangan menjadi stabil.     ABSTRACK Micro small and medium enterprises (MSMEs) at Air Putih Village, Kali Bandung, in the management of Robusta coffee are supported by the village budget and community self-help. This aims to open up employment opportunities for village youth so that they play an active role in positive activities. Home-based businesses that are designed for the long term emphasize the business continuity process, for this reason a well-organized financial recording system is needed, it is necessary to socialize simple financial bookkeeping to Legi Coffee Micro, Small and Medium Enterprises, Air Putih Kali Bandung Village. So that business actors can make the right production decisions so that financial turnover becomes stable.   Keywords:MSMEs, bookeping, coffee
Model Klasifikasi Tingkat Kematangan Sayur Hijau Menggunakan Ekstraksi Fitur Warna dan Convolutional Neural Network Rini Widyastuti; Firna Yenila; Eko Syaputra; Wandi Syahindra; Murlena
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17403

Abstract

The maturity level of green vegetables is an important factor affecting product quality, market value, and shelf life. Maturity identification is generally performed visually based on leaf color changes, making the assessment subjective and potentially inconsistent. This study aims to develop a classification model for green vegetable maturity levels using a combination of color feature extraction and a Convolutional Neural Network (CNN) to provide a more objective and accurate system. The research began with image acquisition of green vegetables categorized into three maturity levels: immature, mature, and overripe. Preprocessing included image resizing, normalization, and segmentation. Color feature extraction was performed using RGB and HSV color spaces to represent maturity conditions. The dataset was divided into training and testing sets with a 90:10 ratio and processed using a CNN architecture. Model performance was evaluated using accuracy, precision, recall, and F1-score. Results showed that the proposed model achieved 95.2% accuracy, 94.8% precision, 95.6% recall, and 95.1% F1-score. These findings indicate that combining color features and CNN effectively supports automated vegetable sorting and quality control systems.
Co-Authors Dwi Sinta Dwita Prisdinawati Eko Syaputra Firna Yenila Putri Milanda Bainamus Rini Widyastuti Wandi Syahindra