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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sains dan Informatika IKRA-ITH Informatika : Jurnal Komputer dan Informatika ILKOM Jurnal Ilmiah Building of Informatics, Technology and Science Jurnal Mantik JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi
Chusna, Nuke L
Universitas Krisnadwipayana
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary

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Classification of Fruits High in Vitamin C Using Self-Organizing Map and the K-Means Clustering Algorithm Nuke L Chusna; Nurhasan Nugroho; Umbar Riyanto; Ahmad Ari Aldino
Building of Informatics, Technology and Science (BITS) Vol 5 No 2 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i2.4104

Abstract

Vitamin C-rich fruits not only taste fresh and delicious but also have the potential to increase the body's resistance to various diseases and maintain a proper nutritional balance. Information about fruits high in vitamin C is very important in order to increase public knowledge about which fruits contain high levels of vitamin C. However, to classify fruits high in vitamin C based on their image, a model is needed that is able to analyze the characteristics present in the image of the fruit. The purpose of this study is to build a classification model for high-vitamin C fruits with a combination of the Self-Organizing Map (SOM) artificial neural network algorithm and K-Means Clustering. Prior to classification, an image segmentation process is carried out using the K-Means Clustering algorithm, which will separate the image into parts that have similar visual characteristics. After the segmented image, the features of the object are extracted based on shape and texture. After the features of the image have been obtained, proceed with classifying images using the SOM algorithm by mapping multidimensional data into a lower-dimensional spatial representation to obtain the appropriate group or class. The accuracy test results for the built model produce an accuracy value of 93.33% and are included in the good category
Pengembangan Aplikasi Deteksi Stunting di Kelurahan Duren Sawit Nur Hikmah; Herry Wahyono; Herwanto Herwanto; Nuke L Chusna; Adam Elvandi Yusup
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 2 No. 3 (2023): Agustus 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v2i3.2495

Abstract

Stunting is a condition in which toddlers experience a lack of nutritional intake for a long period of time so that children experience growth disorders, namely their height is shorter than the age standard. This community service activity was carried out in the Duren Sawit Village. Based on the results of the team's interviews with related parties, so far the process of recording and monitoring children's growth and development data is still done manually. For this reason, an application was developed that is expected to help and facilitate related parties in recording and monitoring child growth and development data. In addition, this application is also expected to be able to provide a visualization of the condition of child growth and development in an area through the process of early detection of stunting on child growth and development data that is inputted at the time of measurement. Bootstrap is a CSS framework that is most in demand by website developers. By using bootstrap we can easily design a responsive website appearance. For this reason, a stunting detection application was made using the bootstrap framework, with the aim that users can more easily use and access this stunting detection application.
Implementasi Penggunaan Website E-Commerce Sebagai Sarana Pemberdayaan Masyarakat pada Kecamatan Pasar Rebo Jakarta Timur Avip Kurniawan; Herry Wahyono; Nuke L Chusna; Risanto Darmawan; Mega Wahyu Rhamadani
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 2 No. 3 (2023): Agustus 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v2i3.2496

Abstract

In order to empower the community in Pasar Rebo District, this study concentrates on the e-commerce website platform. It will do this by supplying in-depth details about goods and services, facilitating online transactions for the community, and educating the community so that they can launch an online business. To learn more about how people view and interact with e-commerce websites, this study strategy combines surveys, interviews, and data analysis. This study also examines how e-commerce will affect the economy, including how it will open up new markets for regional goods and whether it would raise people's incomes. The constraints of handwritten information are overcome by this platform through the use of dynamic technologies and database connectivity. There is a need for more efficient access to information, particularly in the One Million Orchid Village Program, in the context of community service activities for the subdistrict, community empowerment through increasing access to information, digital skills, and participation in the digital economy. This study created a responsive and effective display using the E-Commerce framework, guaranteeing consistency and accessibility across different devices. In conclusion, the community can gain more economically and socially by using this technology, fostering a competitive and sustainable environment in Pasar Rebo District, East Jakarta.
Comparison of Convolutional Neural Network Models for Feasibility of Selling Orchids Chusna, Nuke L; Khumaidi, Ali
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2006.296-304

Abstract

Orchid flowers are one of the most popular ornamental plants, widely appreciated for their unique features and aesthetic appeal, making them highly potential for sales in the global market. While numerous studies have explored Orchid flower characteristics and disease detection, research on the classification of Orchid salability remains unexplored. This study addresses this gap by classifying Orchid flowers into three categories: saleable, potential saleable, and not saleable. Convolutional Neural Networks (CNN), known for their effectiveness in image-based classification, were employed in this study with performance enhancement through the application of transfer learning. Two prominent transfer learning architectures, VGG-16 and ResNet-50, were implemented and compared to evaluate their suitability for Orchid salability classification. The results demonstrated that the VGG-16 model significantly outperformed ResNet-50 in all evaluation metrics. The VGG-16 model achieved an accuracy of 98%, precision of 99%, recall of 97%, and an F1 score of 98%. In contrast, the ResNet-50 model yielded lower performance, with an accuracy of 69%, precision of 68%, recall of 56%, and an F1 score of 56%. The study also observed that increasing the training epochs from 25 to 50 had no significant impact on the performance of either model. This research highlights the superior performance of VGG-16 in Orchid salability classification and underscores the potential of transfer learning in advancing ornamental plant research.
Pendekatan Deep Learning Untuk Klasifikasi Kematangan Tempe Mendoan Menggunakan Convolutional Neural Network Chusna, Nuke L; Sampoerno, Ahmad RIzqi; Wiliani, Ninuk
Jurnal Sains dan Informatika Vol. 11 No. 1 (2025): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/jsi.v11i1.1245

Abstract

Tempe mendoan dikenal dengan makanan yang memiliki kematangan yang berbeda dalam tiap jenisnya. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi tingkat kematangan tempe mendoan menggunakan algoritma Convolutional Neural Network (CNN). Dataset yang digunakan terdiri dari 400 data citra tempe mendoan yang dikategorikan ke dalam empat level kematangan: Level 1 (6 jam pertama), Level 2 (12 jam), Level 3 (18 jam), dan Level 4 (24 jam). Berbagai arsitektur CNN diuji dalam penelitian ini, dan hasil terbaik diperoleh menggunakan arsitektur VGG16 dengan nilai AUC sebesar 0,94 atau 95%, menunjukkan kemampuan klasifikasi yang sangat baik. Sistem ini dirancang untuk membantu produsen, seperti karyawan dan penjual tempe mendoan, dalam menentukan tingkat kematangan tempe secara tepat. Dengan sistem ini, tempe yang dihasilkan memiliki kualitas kematangan optimal, sehingga dapat meningkatkan daya tarik produk dan minat konsumen. Penelitian ini memberikan kontribusi pada penerapan teknologi berbasis deep learning untuk meningkatkan kualitas produksi dalam industri makanan tradisional.
Co-Authors Adam Elvandi Yusup Adriyan Priyatma Ahmad Ari Aldino Ali Khumaidi Amat Damuri Andrian Muljadi Avip Kurniawan Avip Kurniawan Fachri, Moch Herry Wahyono Herry Wahyono Herwanto Herwanto Herwanto Herwanto M.Ageng Laksono Mega Wahyu Rhamadani Moch Fachri Muhammad Syamsul Arif Nur Hikmah Nur Hikmah Nurhasan Nugroho Risanto Darmawan Sampoerno, Ahmad RIzqi Uci Dwi Rahayu Umbar Riyanto Wiliani, Ninuk Yonas Prima Arga Rumbyarso