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Perancangan Sistem Informasi Persediaan dan Penjualan Pada Mini Market Varia Mitra Sungai Ambawang Christina Iil Damayanti; Riyadi J. Iskandar; Thommy Willay
Jurnal Mahasiswa Teknik Informatika Vol. 4 No. 2 (2025): Volume 4 Nomor 2 Oktober 2025
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data processing system of inventory and sales at the Mini Market Varia Mitra is still done manually by recording the process of inventory and sales transactions and in preparing reports. This can decrease the effectiveness and efficiency which will affect the increase in turnover. Therefore, it is necessary to design an information system of inventory and sales, the presentation of the information required will be more precise and accurate in improving operational performance Mini Market Varia Mitra. Forms of research by the author uses descriptive model, while the data collection methods used were interviews, observation, documentation studies, data analysis techniques with UML (Unified Modeling Language), and the design of systems using Microsoft Visual Basic 6.0. and Crystal Report 8.5. Results of research conductedat the Mini Market Varia, the authors designed an information system inventory and sales of goods that can process transaction data inventory, sales, purchase returns and sales returns and in preparing reports inventory  and  sales  information  systems  at  the  Mini  Market  Varia  Mitra,  is  expected  to  improve  operational performance in the data processing inventory and sales transactions. In addition, to optimize the proposed system which designed the necessary training to the user who will use the application so it can run properly in accordance with its function. Keywords: Information System, Inventory, Sales, Minimarket, Barcode   Sistem pengolahan data persediaan dan  penjualan pada Mini Market Varia Mitra  masih dilakukan secara manual  dengan  melakukan  pencatatan  pada  proses  transaksi  persediaan  dan  penjualan  serta  dalam  pembuatan laporan.   Hal ini dapat menurunkan efektifitas dan efisiensi kerja yang nantinya akan berpengaruh pada peningkatan omset. Maka dari itu, perlu dirancang suatu sistem informasi persediaan dan penjualan barang berbasis komputer, sehingga penyajian informasi yang dibutuhkan akan semakin tepat dan akurat dalam meningkatkan kinerja operasional Mini Market Varia Mitra. Bentuk penelitian yang dilakukan penulis menggunakan model deskriptif,sedangkan metode pengumpulan data yang digunakan adalah wawancara,observasi, studi dokumentasi,teknik analisis data dengan UML (Unified Modelling Language),dan perancangan sistem menggunakan Microsoft Visual Basic 6.0. dan Crystal Report 8.5.   Hasil penelitian yang dilakukan oleh penulis   pada Mini Market Varia Mitra, yaitu penulis merancang suatu sistem informasi persediaan dan penjualan barang yang dapat mengolah data transaksi persediaan, penjualan, retur pembelian dan retur penjualan serta   dalam pembuatan laporan.Perancangan sistem informasi persediaan dan penjualan pada Mini Market Varia Mitra, diharapkan dapat meningkatkan kinerja operasional dalam proses pengolahan data transaksi persediaan dan penjualan. Selain itu, untuk mengoptimalkan sistem usulan yang dirancang maka diperlukan pelatihan pada user yang akan menggunakan aplikasi tersebut sehingga dapat berjalan dengan baik sesuai dengan fungsinya. Kata Kunci: Sistem Informasi, Persediaan, Penjualan, Mini Market, Barcode.
Aplikasi Klasifikasi Penyakit Pada Tanaman Jambu Air Menggunakan Metode CNN Antonius Oktavian Jethro; Tony Darmanto; Riyadi J. Iskandar
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.17810146

Abstract

Diseases in water apple plants can significantly reduce the quality and quantity of the harvest, thus an accurate early classification system is needed. This research aims to develop an automatic classification system to assist in the early diagnosis of diseases in water apple plants. This system uses a Convolutional Neural Network (CNN) model with the MobileNetV2 architecture optimized through fine-tuning techniques. The dataset was obtained from Kaggle, Roboflow, and direct data collection, with a distribution of 80 percent training data, 10 percent validation data, and 10 percent testing data. The model was trained to recognize nine different conditions from images of leaves and fruits, then integrated into a web application. Testing results showed very good performance, with a final accuracy of 94 percent and a balanced F1-Score of 93 percent on unseen test data. However, the model faces challenges in distinguishing diseases with high visual similarity, especially in the class of leaves with brown spots. Overall, this research successfully produced an effective and accurate classification system. The developed application has high practical potential as an early diagnosis aid to improve plant health management and reduce the potential for crop loss.