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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Journal Global Technology Computer
Fawwaz, Insidini
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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Classification of beetle type using the Convolutional Neural Network algorithm Fawwaz, Insidini; Candra, Tomy; Marpaung, Delima Agustina Margareta; Dinis, Arun; Fachrozi, M Reza
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11673

Abstract

Beetles (Order Coleoptera) are the largest order of animals. Beetles are a group of insects that make up the order Coleoptera. Estimates of the total number of living beetle species are millions of beetle species whose features make it difficult to visually identify beetle species. Currently, the beetle classification process is still carried out using direct observation and personal assumptions. CNN model ResNet50 is one of the ResNet variants that has 50 layers and VGG16 is a CNN model that utilizes a convolutional layer with a small convolutional filter specification (3×3) and always uses the same padding and maxpool layers of a 2x2 filter. In this Algorithm (CNN) with the ResNet50 model, it succeeded in exploring beetles with accuracy, precision, recall and F-1 Score with values of 93%, 94.24%, 89.28%, 91.69%, while the VGG16 model succeeded in conducting research on beetle species with accuracy, precision, recall and F-1 Score with values of 86.9%, 87.5%, 87%, 87.2%, so it can be said that the classification of beetle species using the CNN algorithm with the ResNet50 model is better than the VGG16 model.
Implementation of Transfer Learning in CNN for Classification of Nut Type Fawwaz, Insidini; Sagala, Jimmy Deardo; Sijabat, Reivaldo Kevin Febriawan; Maringga , Novita Marissa
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12784

Abstract

Nut has a high nutritional value and is widely used as an ingredient in cooking and snacks. Nut is included in the group of grains and has many types. Each type of nut has different nutritional content. Some types of nuts can also cause allergies or negative reactions in certain people, so it is important to identify the type of nut to be consumed. There are many types of nut that are different from each other, but some of them are similar. This makes it difficult to distinguish between the types of nuts, so there is a need for technology that can accurately identify nut types. Transfer Learning method is used to utilize trained models and applied to nut type classification. The two CNN models used are Inception V3 and Xception. The dataset consists of 11 types of nuts consisting of 1,320 data. The data is divided into 60% for training data and 40% for validation data. Preprocessing is done to ensure the image size is consistent and clarify the focus on the data image to be tested. The training results show that the Xception model is superior to Inception V3, with an accuracy of 86.36% on the validation data, while Inception V3 only reached 74.05%. Xception is able to predict nut types more precisely.
The Optimization of CNN Algorithm Using Transfer Learning for Marine Fauna Classification Fawwaz, Insidini; Yennimar, Yennimar; Dharsinni, N P; Wijaya, Bayu Angga
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12893

Abstract

Marine fauna are all types of organisms that live in the marine environment. Marine fauna is also an important part of the marine ecosystem that has an important role in maintaining environmental balance. However, the survival of marine fauna is threatened due to activities carried out by humans, such as pollution, overfishing, industrial waste disposal into marine waters, plastic pollution and so on. Therefore, efforts are needed to monitor and protect marine fauna so that marine ecosystems can remain stable. One way to monitor marine fauna is by using classification technology. One of the technologies that can be used in marine fauna classification technology is Convolutional Neural Network (CNN). CNN is one of the classification methods that can be used to classify objects in images with a high level of accuracy. The CNN architecture models used are MobileNet, Xception, and VGG19. Furthermore, the method used to improve the performance of the CNN algorithm is the Transfer Learning method. The test results show that the MobileNet architecture model produces the highest accuracy value of 91.94% compared to Xception and VGG19 which only get an accuracy value of 87.64% and 88.42%. This shows that the MobileNet model has a more optimal performance in classifying marine fauna.
WEBSITE-BASED LIBRARY DATA PROCESSING DESIGN Fawwaz, Insidini; Firtan, Erwin Conery; -, Steven; Yawin, Helbert
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 1 (2023): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4029

Abstract

The main problem Indonesia faces, especially in education in the era of globalization, is the low quality of human resources. One of the efforts to improve the quality of human resources is to increase interest in reading and the habit of reading. From this fact, the library is expected to be the center of activities to develop interest in reading and reading habits. Libraries have a great responsibility to increase and generate interest in reading. Library data management is one of the essential activities in running a library. Librarians must be able to process and manage book data efficiently and effectively to avoid losing library property. This study uses PHP to create a website design to assist librarians in processing and storing data about existing books. This study designs a library data processing system that contains library book loans, such as recording books, transactions, and student data collection in the library. The results of this website design can facilitate library staff in organizing and tracking library management quickly and efficiently. Keywords: Digital Library, Library Website, Electronic Journal
Implementasi Metode Rule-Based dalam Sistem Pakar Pemilihan Program Studi Menggunakan Bahasa Prolog Faza, Sharfina; Rizka, Ade; Husna, Meryatul; Anugrahwaty, Rina; Fawwaz, Insidini
Journal Global Technology Computer Vol 4 No 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i2.7293

Abstract

The alignment between study programs and students' interests and abilities is a crucial factor in academic success at the university level. Unfortunately, many prospective students face confusion when choosing majors due to limited knowledge about the characteristics of each program and its relationship with career prospects, potentially affecting their academic performance and career paths. To address this challenge, our research presents a solution in the form of a rule-based expert system developed using Prolog language. This system is designed to provide study program recommendations through analysis of user responses to various structured questions. Using score calculation methods and matching against established value parameters, the system can propose the most relevant majors among four options: Computer Engineering (CE), Information Management (MI), Multimedia Graphics Engineering Technology (TRMG), and Software Engineering Technology (TRPL). Through this implementation, prospective students receive recommendations aligned with their potential and interests, facilitating more accurate decision-making. In addition to functioning as an assistive instrument in career and academic counseling for high school students, this research also lays the foundation for the development of more sophisticated expert systems with enhanced assessment weights and precision levels in the future.
Pengabdian Kepada Masyarakat Penerapan Sistem Informasi Berbasis Web Dalam Mendukung Pemilihan Hewan Domba Selvida, Desilia; Fawwaz, Insidini; Nurrahmadayeni, Nurrahmadayeni; Putra, Purwa Hasan
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3818

Abstract

Abstract: The selection of sheep for qurban is an important process and must meet Islamic sharia criteria as well as aspects of livestock health and quality. At Arjuna Farm, the sheep selection process is still done manually, making it difficult for prospective buyers to obtain accurate and reliable information, especially for those who are outside the city. This Community Service (PKM) activity aims to implement an information system application that can help farmers record livestock digitally, and make it easier for buyers to choose qurban animals objectively and efficiently. The methods used in this activity include initial observation, application design and development, training for farmers, implementation systems, and evaluation of usage results. This application provides features for recording sheep data (age, weight, price, health conditions), searching based on qurban criteria, and stock availability information. The results of the activity show that this application increases the efficiency of the selection process, accelerates service to consumers, and encourages the adoption of technology by farmers. The implementation of this application not only improves existing technical problems, but also becomes the initial step in digitalizing sustainable community livestock management that is responsive to consumer needs in the digital era.            Keywords: Information System, Sheep Selection, Digital Application, Livestock, Arjuna Farm Abstrak: Pemilihan hewan domba untuk qurban merupakan proses yang penting dan harus memenuhi kriteria syariat Islam serta aspek kesehatan dan kualitas ternak. Di Arjuna Farm, proses pemilihan domba masih dilakukan secara manual, sehingga menyulitkan calon pembeli dalam memperoleh informasi yang akurat dan terpercaya, terutama bagi mereka yang berada di luar kota. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk menerapkan aplikasi sistem informasi yang dapat membantu peternak dalam mendata hewan ternak secara digital, serta memudahkan pembeli dalam memilih hewan qurban secara objektif dan efisien. Metode yang digunakan dalam kegiatan ini meliputi observasi awal, perancangan dan pengembangan aplikasi, pelatihan penggunaan bagi peternak, implementasi sistem, dan evaluasi hasil penggunaan. Aplikasi ini menyediakan fitur pencatatan data domba (usia, bobot, harga, kondisi kesehatan), pencarian berdasarkan kriteria qurban, serta informasi ketersediaan stok. Hasil kegiatan menunjukkan bahwa aplikasi ini meningkatkan efisiensi proses pemilihan, mempercepat layanan kepada konsumen, dan mendorong adopsi teknologi oleh peternak.  Penerapan aplikasi ini tidak hanya menyelesaikan masalah teknis yang ada, tetapi juga menjadi langkah awal digitalisasi manajemen peternakan rakyat yang berkelanjutan dan responsif terhadap kebutuhan konsumen di era digital. Kata kunci: Sistem Informasi, Pemilihan Domba, Aplikasi Digital, Peternakan, Arjuna Farm
Co-Authors -, Steven Bayu Angga Wijaya Candra, Tomy Dharsinni, N P Dinis, Arun Fachrozi, M Reza Faza, Sharfina Firtan, Erwin Conery Husna, Meryatul Maringga , Novita Marissa Marpaung, Delima Agustina Margareta Nurrahmadayeni, Nurrahmadayeni Putra, Purwa Hasan Rina Anugrahwaty, Rina Rizka, Ade Sagala, Jimmy Deardo Selvida, Desilia Sijabat, Reivaldo Kevin Febriawan Yawin, Helbert Yennimar, Yennimar