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All Journal International Journal of Advances in Applied Sciences Jurnal Informatika dan Teknologi Komputer ( J-ICOM) ALMUJTAMAE: Jurnal Pengabdian Masyarakat J-SIGN (Journal Of Informatics, Information System, And Artificial Intelligence) Journal of Information System and Education Development
Putra, Dwipa Junika
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Other

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Penerapan Ekonomi Kreatif dalam Pengolahan dan Pemasaran Ikan Lele Rumahan Menggunakan Metode Digital Marketing Widia, Elsa; Putra, Dwipa Junika
ALMUJTAMAE: Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2023): Agustus
Publisher : Universitas Djuanda Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/almujtamae.v3i2.8145

Abstract

Indonesia memiliki potensi yang luar biasa di bidang perikanan, khususnya pada perikanan air tawar. Seiring meningkatnya permintaan pasar, masyarakat mulai membudidayakan beberapa ikan jenis tertentu salah satunya ikan lele. Namun peternak seringkali mengalami kesulitan untuk memasarkan ikan lele jika usia dan besar ikan lele melebihi dengan permintaan pasar. Untuk menghindari resiko kerugian maka pengabdian kepada masyarakat kali ini akan mengadakan pelatihan untuk membantu masyarakat dan peternak melalui kegiatan pengolahan ikan lele untuk menciptakan nilai ekonomis tinggi untuk dipasarkan. Pelatihan ini juga akan dilengkapi dengan pelatihan digital marketing untuk memasarkan produk olahan tersebut. Produk olahan dapat diversifikasi menjadi daging fillet, siomay, nugget, bakso, abon, atau kerupuk yang dapat dipasarkan dalam bentuk frozen food. Kemudian untuk pemasaran diutamakan menggunakan digital marketing melalui website atau media online lainnya. Kegiatan ini diikuti oleh peternak ikan lele dan masyarakat sekitar Kelurahan Aia Pacah Kecamatan Koto Tangah Kota Padang. Hasil dari kegiatan pengabdian ini diharapkan mampu memberikan motivasi peternak untuk menghasilkan produk olahan yang berdaya jual tinggi dan mampu memasarkannya secara digital.
Pengukuran Tingkat Kepuasan Mahasiswa Terhadap Pelayanan di Kantin Kampus Menggunakan Algoritma K-means Clusterring Carelsa, Hasnah Vithon; Malik, Rio Andika; Putra, Dwipa Junika
Journal of Information System and Education Development Vol. 1 No. 3 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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Abstract

The K-means Clustering algorithm technique is being used in this study to gauge how satisfied students in the Universitas Perintis Indonesia Digital Business programme are with the cafeteria's offerings. The study focuses on customer service characteristics such meal quality, cost, speed of service, cleanliness, and comfort in the cafeteria setting. The goal of the research is to provide deeper insights into student expectations and preferences for cafeteria services by utilising K-means to uncover distinct satisfaction patterns among student groups. When used to measure student satisfaction with cafeteria services, the K-means Clustering method is successful at identifying groups of students who have similar patterns of satisfaction. Some student groups score food quality and cleanliness favourably, according to the clustering data, while other groups may be more critical. In light of the preferences of each student group, cafeteria management can use this data to develop more specialised plans for improving services. The study also shows that using the K-means Clustering method to evaluate customer satisfaction offers a potentially advantageous strategy for enhancing service quality across a variety of service sectors.
Rancang Bangun Sistem Informasi Manajemen dan Monitoring Aset IT Laboratorium Komputer Berbasis Web Putra, Dwipa Junika
J-SIGN (Journal of Informatics, Information System, and Artificial Intelligence) Vol 3, No 01 (2025): May
Publisher : Department of Informatics, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/j-sign.v3i01.43291

Abstract

This research aims to develop a web-based IT asset management and monitoring information system for the Informatics computer laboratory. The system is designed to address issues such as manual inventory recording, inadequate reporting, non-integrated asset management processes, and limitations in real-time monitoring. The system includes a reporting form menu for IT assets in the computer laboratory that experience issues or damage. Users can submit reports through the application, which is designed with a user-friendly interface, allowing the reports to be forwarded to the laboratory manager for further inspection. The system not only provides more efficient inventory management features but also ensures transparency in reporting asset conditions. Employing the Waterfall methodology, the research encompasses the stages of requirement analysis, system design, implementation, testing, and maintenance. Key features include asset inventory recording with QRCode integration, detailed inventory tracking, periodic asset condition monitoring, and systematic mechanisms for asset damage reporting. This system is expected to enhance efficiency, accuracy, transparency, and ease in IT asset management, aligning with the operational needs of a modern, effective, efficient, and technology-driven laboratory.
Analisis Kepuasan Pengguna E-Commerce Shopee Menggunakan Model End-User Computing Satisfaction (EUCS) Asasunnaja, Rinny; Fatwanto, Agung; Putra, Dwipa Junika
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 6 No 1 (2025): Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v6i1.11056

Abstract

Technology is currently developing very rapidly, one of the advantages with the presence of technology is that business can be done online without being limited by distance and time and the activity of business transactions is known as e-commerce. One of the e-commerce that is famous and in demand by many buyers in Indonesia is the shopee e-commerce application, this research aims to determine the satisfaction of e-commerce customers in using the shopee application using the EUCS model. This research used a quantitative method with a purposive sampling technique which resulted in a sample of 277 respondents. The results of the research conducted on the R2 test, it is known that the R Square value is 0.686, which means that variable of content, accuracy, format, ease of use and timeliness simultaneously affects the satisfaction variable by 68.6%. Furthermore, from the results of the T test, it can be seen that there is an effect of the variables of content, format, ease of use and timeliness on the satisfaction variable, but the accuracy variable has no effect on the satisfaction variable. And the researcher carried out an F test in this study, and the results of the F test showed that the significant value for the influence of the variables content, accuracy, format, ease of use and timeliness simultaneously had an influence on the user satisfaction variable.
Enrichment of microscopic photographs by utilizing CNN regarding soil-transmitted helminths identification Malik, Rio Andika; Frimadani, Marta Riri; Putra, Dwipa Junika
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp46-53

Abstract

Soil-transmitted helminth (STH) infection remains a significant global health challenge, affecting millions of people, particularly in developing countries. A convolutional neural network (CNN) approach to optimize the detection of STH infections in microscopic images. The study aims to assess the effectiveness of the CNN model in identifying and classifying STH worm eggs accurately. The research employs MATLAB as the primary tool for conducting experiments and validation tests. By implementing image preprocessing techniques to enhance image quality and applying precise segmentation methods, the CNN model is trained on a dataset of microscopic images to learn and classify STH infections effectively. The validation test results demonstrate that the CNN model achieved a high accuracy rate of 92.31% in classifying STH infections. This accuracy surpasses traditional methods, which are time-consuming and susceptible to human errors. This study underscores the importance of integrating artificial intelligence, particularly CNN, into the healthcare domain to support detecting and diagnosing diseases requiring specialized expertise, such as STH infections. The findings of this research can serve as a valuable reference for researchers, medical practitioners, and data scientists in leveraging artificial intelligence to enhance the quality of healthcare services, leading to positive impacts on society worldwide.
Co-Authors Agung Fatwanto, Agung Asasunnaja, Rinny Carelsa, Hasnah Vithon Elsa Widia Frimadani, Marta Riri Malik, Rio Andika