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Analisis Morfometrik dan Klasifikasi Bentuk Lutjanus spp. Berdasarkan Gambar Digital Muhammad Ikhwani Saputra; Ishak Ariawan; Riad Sahara
Jurnal Ilmiah FIFO Vol 12, No 2 (2020)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2020.v12i2.008

Abstract

Lutjanus spp is a genus of the Lutjanidae family. The number of Lutjanus spp in waters around the world are 72 species. For this amount, 33 of them living on Indonesian waters. According to the IUCN List (2020), about ten species have decreased in population. One of the causes that population decline in several species is, the recording of capture fisheries has very limited production data. This is caused by the difficulty of identification in the field, which results in the overfishing of certain species. The identification process can be carried out based on morphometric features. Geometric morphometrics can be explaining morphological variations objectively and accurately. There are several methods used to represent the shape of an image in general. Namely point linking, complex coordinate, tangent angle, contour curvature, and triangle-area representation.Lutjanus spp by calculating the value of landmark positions, landmark curvature, changes in landmark angle, landmark distance, and landmark inclination. The results of feature extraction were used to classify Lutjanus spp (Lutjanus argentimaculatus, Lutjanus bohar, Lutjanus carponotatus, Lutjanus fulviflamma, and Lutjanus sebae). The results of this study indicate that the morphometric geometric approach can extract the feature values of the position of landmarks, a curvature of landmarks, changes in the angle of the landmark, distance of landmark, and the inclination of the landmark. The classification results using the Support Vector Machine (SVM) classification technique can distinguish Lutjanus spp with an accuracy rate of 65.03%. Thus, the application of SVM can be used to classify Lutjanus spp species, which will be useful in the identification process. Keywords: clasificasion, identification, morphometric geometric, Lutjanus spp, support vector machine. AbstrakLutjanus spp. adalah salah satu marga dari famili Lutjanidae. Jumlah spesies Lutjanus spp di perairan seluruh dunia yaitu 72 spesies. Dari 72 spesies tersebut 33 diantaranya hidup di perairan Indonesia. Menurut IUCN (2020) sekitar 10 spesies mengalami penurunan populasi. Salah satu penyebab menurunnya populasi pada beberapa spesies yaitu pencatatan data produksi perikanan tangkap masih sangat terbatas. Hal ini disebakan oleh sulitnya identifikasi di lapangan sehingga mengakibatkan overfishing pada spesies tertentu. Proses identifikasi dapat dilakukan berdasarkan ciri morphometrik. Geometri Morfometrik dapat menjelaskan variasi morfologi secara objektif dan akurat. Ada beberapa metode yang digunakan dalam merepresentasi bentuk suatu citra secara umum. yaitu point linking, complex coordinate, tangent angle, contour curvature, serta triangle-area representation. Pendekatan morphometric geometric pada penellitian ini digunakan untuk mengekstraksi fitur bentuk Lutjanus spp. dengan menghitung nilai posisi landmark, kelengkungan landmark, perubahan sudut landmark, jarak landmark, dan kemiringan landmark. Hasil ekstraksi fitur digunakan untuk mengklasifikasikan spesies Lutjanus spp. (Lutjanus argentimaculatus, Lutjanus bohar, Lutjanus carponotatus, Lutjanus fulviflamma, dan Lutjanus sebae). Hasil penelitian ini menunjukkan, bahwa pendekatan Geometri Morfometrik dapat melakukan ekstraksi nilai fitur posisi landmark, kelengkungan landmark, perubahan sudut landmark, jarak landmark, dan kemiringan landmark.  Adapun hasil klasifikasi menggunakan teknik klasifikasi Support Vector Machine (SVM) mampu membedakan spesies Lutjanus spp. dengan tingkat akurasi sebesar 65.03%. Dengan demikian, penerapan SVM dapat digunakan untuk melakukan klasifikasi terhadap spesies Lutjanus spp yang akan bermanfaat pada proses identifikasi.Kata kuncis: klasifikasi, identifikasi, geometri morfometrik, spesies lutjanus spp., support vector machine. 
Integration Design of Academic Information Systems And Learning Management Systems Using Web Services Rest-Based External Database Riad Sahara; Syahid Abdullah; Muhammad Ikhwani Saputra; Cian Ramadhona Hassolthine
Jurnal Ilmiah FIFO Vol 14, No 2 (2022)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2022.v14i2.010

Abstract

ICT products that are widely used in universities in Indonesia are E-Learning with a Learning Management System (LMS) and Academic Information System (SIA). The existence of these two products from ICT will greatly assist the running of academic business processes in a higher education institution. Of course, if the two are well integrated, especially for managing existing academic data. However, in many tertiary institutions, the two systems are still not integrated, such as in managing academic data. The huge amount of data and the complexity of these two systems will make the management and integration process difficult and inefficient if done conventionally. Seeing these problems, the researcher intends to conduct research on the integration of the two REST-based Web Service systems and use the External Database feature which will be used to synchronize data from SIA to E-Learning in real time.
AN EVALUATION OF THE USE OF ONLINE PROGRAMMING SIMULATOR TO INCREASE THE PARTICIPATION RATE OF CLASSROOM STUDENT ATTENDANCE Sahara, Riad; Abdullah, Syahid; Ramadhona Hassolthine, Cian; Ikhwani Saputra, Muhammad
Jurnal PTK dan Pendidikan Vol. 10 No. 1 (2024): Januari - Juni
Publisher : Fakultas Tarbiyah dan Keguruan Universitas Islam Negeri Antasari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18592/ptk.v10i1.11699

Abstract

The Informatics Distance Learning Study Program at UNSIA is one of the study programs that employs a significant number of practicum-type courses as part of its learning process. The implementation of the practicum is carried out through joint simulations to achieve 21st-century graduate competencies. The implementation of learning for practicum-type courses is carried out through the utilization of the Learning Management System (LMS) and zoom. In practicum-type courses, students are required to install the software necessary for the lecture process, particularly for joint simulations. A significant number of students have encountered difficulties in installing the requisite software. These issues led to a dearth of student engagement during the joint simulations conducted via Zoom, particularly in terms of active participation. The implementation of an appropriate online programming simulator (OPS) is expected to enhance participation in practicum-type courses during synchronous sessions, thereby facilitating the acquisition of the greatest possible learning. The results of the analysis conducted before the implementation of OPS revealed that the lowest active class participation rate was 36.7% (22 students) out of a total of 60 students, while the highest active class participation rate was 50.0% (30 students) out of a total of 60 students. Following the implementation of OPS, the lowest participation rate was 83.3% (53 students) of the total 60 students, while the highest active class participation rate reached 96.7% (58 students) of the total 60 students. Keywords: Class Participants, E-Learning, Higher Education, Online Programming Simulator
E-Commerce Product Review Sentiment Analysis: A Comparative Study of Naïve Bayes Classifier and Random Forest Algorithms on Marketplace Platforms Hassolthine, Cian Ramadhona; Haryanto, Toto; Adline Twince Tobing, Fenina; Ikhwani Saputra, Muhammad
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v12i1.4246

Abstract

Achieving customer satisfaction and trust is a major challenge for success in the business world. Entrepreneurs must identify problems that arise from reviews given by customers. However, reading and sorting each review is time-consuming and considered inefficient. In order to overcome this, a study was conducted that aims to analyze sentiment on products sold in the Shopee marketplace using the Naïve Bayes Classifier and Random Forest algorithms. The focus of this study is on product reviews from XYZ Store. The main objective of this study is to determine a more accurate and efficient algorithm in classifying review sentiment, which can help companies in marketing strategies and product development. The results of this study can provide insight for companies about consumer responses to marketed products, so that they can be used as a basis for making strategic decisions to improve the quality of services and products. The results of the Random Forest method classification produce superior predictions compared to the Naïve Bayes Classifier method with an accuracy value of 92.5%, precision of 93%, Recall of 92.5% and F1-Score of 90%.