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All Journal Building of Informatics, Technology and Science Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Buana Informatika
Ariestiandy, Deny
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences Other

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Klasifikasi Jenis Tanaman Fast Growing Species Menggunakan Algoritma Radial Basis Function Berdasarkan Citra Daun Nuraini, Rini; Harlena, Silvia; Amalya, Farida; Ariestiandy, Deny
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3245

Abstract

Indonesia has vast forests, even ranked as the third largest forest in the world. However, currently many forest areas have been deforested or the phenomenon of losing tree cover and forest areas. Forest rehabilitation programs develop by prioritizing plant or tree species that have fast growth or are called fast growing species. However, many people do not know about these fast growing species. Even though knowledge about the types of fast growing plant species is very important for the community to have so that the community can find out which plants can accelerate forest rehabilitation. Fast growing species of plants can actually be identified from the shape of the leaves. This study aims to build a classification model for fast growing species plant images based on leaf images by applying the Radial Basis Function (RBF) artificial neural network algorithm with morphological feature extraction. Morphological feature extraction is used to identify the shape of an object in order to obtain feature values based on predetermined parameters. These features then become input for the RBF artificial neural network to obtain learning patterns. The RBF network has three layers that are feedforward so that it can support solving classification or pattern recognition problems. Based on the results of accuracy testing, an accuracy value of 87.50% was obtained. This means that the Radial Basis Function (RBF) neural network is able to classify fast growing plant species based on leaf images.
OPTIMIZING SME OPERATIONS THROUGH A WEB-BASED BREAD ORDERING SYSTEM: INTEGRATION OF WATERFALL METHODOLOGY AND LARAVEL FRAMEWORK FOR ENHANCED EFFICIENCY Khair Rakhman, Ligian; Faridi; Ariestiandy, Deny; Lizsa, Zain
Buana Informatika Vol 15 No 1 (2025): Buana Informatika
Publisher : LPPM AMIK CBI Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53918/bi.v15i1.119

Abstract

UMKM Roti Maryam Opay, located in Sukabumi, still uses a manual ordering system through WhatsApp or by customers coming directly to the production site. This system has many limitations, such as unstructured order recording, a high risk of data entry errors, and difficulties in summarizing daily, weekly, and monthly orders. In addition, customers find it difficult to place orders outside working hours or from certain areas. To address these problems, the author designed and developed a web-based bread ordering application using the Laravel framework and MySQL database. The application development follows the Waterfall method, which consists of requirement analysis, system design, program implementation, program testing, and program maintenance. In the analysis phase, the author conducted direct observation and interviews with the business owner to understand the ongoing ordering process. The analysis results showed that the manual system caused inefficiencies and inconveniences for both admins and customers. In the design phase, UML was used to create important diagrams such as Use Case Diagram, Activity Diagram, Sequence Diagram, and Class Diagram. The database structure was designed using ERD to clarify table relationships. The application features include user login and registration, product and bread variant management, ordering process with detailed delivery addresses, order management by admins, and automatic, structured transaction reports daily, weekly, and monthly.
Evaluasi Load Balancing: Studi Komparatif Least-Connection dan Round-Robin dalam Konteks Cloud Computing Ariestiandy, Deny; Suhery, Lilik; Jusmawati; Yanuardi
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6236

Abstract

Teknologi cloud computing membutuhkan metode load balancing yang efisien untuk mendistribusikan beban kerja secara merata ke seluruh node dalam jaringan. Penelitian ini bertujuan untuk menganalisis perbandingan efektivitas antara algoritma load balancing yaitu Round-Robin dan Least-Connection. Pengujian dilakukan melalui beberapa tingkat koneksi yang berbeda, dari 1000/600 hingga 5000/1000 untuk menilai hasil rata-rata response time yang diukur dalam millisecond (ms). Data empiris yang terkumpul mengindikasikan bahwa terjadi peningkatan linear response time sejalan dengan peningkatan jumlah koneksi pada kedua algoritma. Meskipun keduanya menunjukkan kinerja yang hampir serupa pada fase awal, dengan rata-rata response time Round-Robin pada 1000/600 koneksi adalah 2.8 ms, sedangkan Least-Connection mencapai 2.9 ms. Algoritma Least-Connection menunjukkan keunggulan yang konsisten di koneksi yang lebih tinggi. Pada 5000/1000 koneksi, Round-Robin tercatat memiliki response time 3.275 ms, sedangkan Least-Connection memiliki rata-rata response time 3.34 ms, yang mengindikasikan bahwa Least-Connection memiliki skalabilitas yang lebih baik dalam mengelola koneksi bertingkat tinggi. Temuan ini menyarankan bahwa untuk sistem yang mengharapkan jumlah koneksi yang relatif stabil dan dapat diprediksi maka direkomendasikan menggunakan Round-Robin. Namun, untuk sistem dengan beban kerja yang dinamis dan tidak terprediksi, maka Least-Connection memiliki kemampuan yang lebih baik.
Co-Authors Amalya, Farida Faridi Faridi Harlena, Silvia Jusmawati Khair Rakhman, Ligian Lilik Suhery, Lilik Lizsa, Zain Rini Nuraini, Rini Yanuardi