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Jurnal ULTIMATICS

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Published by Universitas Multimedia Nusantara

ISSN : 20854552 EISSN : 2581186X DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Jurnal ULTIMATICS merupakan Jurnal Program Studi Teknik Informatika Universitas Multimedia Nusantara yang menyajikan artikel-artikel penelitian ilmiah dalam bidang analisis dan desain sistem, programming, algoritma, rekayasa perangkat lunak, serta isu-isu teoritis dan praktis yang terkini, mencakup komputasi, kecerdasan buatan, pemrograman sistem mobile, serta topik lainnya di bidang Teknik Informatika. Jurnal ULTIMATICS terbit secara berkala dua kali dalam setahun (Juni dan Desember) dan dikelola oleh Program Studi Teknik Informatika Universitas Multimedia Nusantara bekerjasama dengan UMN Press.

Arjuna Subject : -

Articles 292 Documents

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"Animal Introduction" Application For Children Fadjaruddin Qadr; Agung Budi Prasetijo; Ike Pertiwi Windasari
Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Introducing animals in early childhood can foster children's love for animals. Some media for introducing animals to children are diverse, one of which is a book about animals. Books about animals display various types of animals and information on these animals. But books about animals are less effective in helping parents teach children about animals because they are less interactive. With the development of technology, especially smart phones can help users spread information. Smartphones can load images, videos& text. To help parents introduce animals to children, an animal recognition application on smart phones was developed. The development method used is MDLC, which consists of 6 stages: concept, design, material collection, merging, testing, and distribution. This application is made using the Java programming language on Android with Android Studio. This applications can be used as an interactive learning media to introduce animals to children. This application can display images, videos, animal information and some quizes.

Pengembangan Sistem Pariwisata Belitung tri wahyu widyaningsih; Didi Didi
Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

This system was developed to increase the number of tourists in the Belitung region, especially in Tanjung Kelayang which is one of the Special Economic Zones (KEK) in Indonesia. Increasing the number of tourists can be done by providing technology-based facility services to tourists. The facility in question is a mobile-based application, making it easier for users to access applications. The system has been developed and tested using black box techniques with good results, and according to 31 questionnaire responses with good results of 88.71%. The system was developed using Agile, with UML system design, and Android Studio software.

Purwarupa Sistem Monitoring Kualitas Air pada Kolam Ikan Air Tawar Arif Supriyanto; Fathurrahmani Fathurrahmani; agustian noor; yunita prastyaningsih
Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

In freshwater fish cultivation, the most important thing to guard and pay attention to is the quality of pond water for the survival of these fish. The resilience of the body of the fish is very dependent on the quality of the water, if the water quality is good then the resistance of the body of the fish to the attack of the disease will be better too. This research was conducted to design and build a prototype monitoring system for freshwater fish pond water quality that can provide information about the condition of freshwater fish ponds in real-time. This monitoring system is made using Arduino as a data processor and several sensors such as water pH sensors, water turbidity, and water temperature. Next is a web-based monitoring application. This system can be monitored directly by fish farmers via LCD screens and smartphones. Based on the test results, the temperature sensor has an offset value of 0.34, pH sensor 0.37, turbidity sensor 0.22 and the fish management monitoring system application can function properly.

Sistem Informasi Layanan Puskesmas Berbasis Web Farica Perdana Putri; Florentina Kurniasari
Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Puskesmas must always improve their quality so that the services provided are faster and more effective. One of the efforts in improving the quality is the construction of information systems regarding types of services, programs, operating hours, and availability of inpatient rooms. Puskesmas Keranggan is one of the Puskesmas where the use of inpatient rooms is still done manually, without a system, so that medical personnel in different health services find it difficult to know the exact number of rooms that are still available. Therefore, Puskesmas Keranggan built a web-based information system that can be accessed quickly and easily using internet. The information system was built using the Laravel framework, Bootstrap, and MySQL. The web application is ready to use and has been built in accordance with the requirements.

Pembangunan Dashboard Beasiswa dan Pinjaman Program Studi Informatika UKDW Agustinus Rendi Walewowan; Willy Sudiarto Raharjo; Gloria Virginia
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Ketua program studi (kaprodi) memiliki banyak tugas dan tanggung jawab yang harus dilaksanakan dalam kegiatan akademik. Salah satu tugas dari seorang kaprodi adalah melaporkan seluruh pelaksanaan kegiatan di suatu prodi. Untuk itu, diperlukan suatu sistem yang dapatdigunakan untuk memantau kegiatan operasional sehari-hari dan memberikan laporan. Dashboard adalah sebuah tampilan panel informasi yang digunakan dalam suatu organisasi untuk mengevaluasi suatu masalah sehingga memudahkan seseorang untuk mengambil keputusan. Penelitian ini bertujuan melakukan perancangan sebuah dashboard beasiswa dan pinjaman dengan menggunakan metode prototyping. Prototyping adalah metode pengembangan perangkat lunak, yang berupa model fisik kerja sistem dan berfungsi sebagai versi awal dari sistem. [1]. Hasil rata-rata pengujian task success pada kedua iterasi, yaitu 96,66 sehingga sistem yang dibangun dapat dikatakan cukup efektif dalam menampilkan informasi beasiswa dan pinjaman serta mudah untuk dipelajari. Evaluasi desain antarmuka yang dilakukan menggunakan System Usability Scale (SUS) kepada 5 orang responden pada masing-masing iterasi dan menghasilkan skor SUS 75,2 pada iterasi I dan 76,6 pada iterasi II. Berdasarkan hasil tersebut diperoleh rata-rata skor SUS untuk kedua iterasi, yaitu 75,9. Dengan demikian, antarmuka sistem dinyatakan baik dengan grade scale bernilai C, adjective rating bernilai Good, dan acceptability ranges dapat diterima (acceptable).

The Decision Tree C5.0 Classification Algorithm for Predicting Student Academic Performance Natanael Benediktus; Raymond Sunardi Oetama
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Student’s performance is often used as a benchmark and a student’s activeness is frequently used as a criteria of how well a student academically perform at school. Where in this study would try to find out whether the activeness of a student can predict their academic performance. The data used is an educational dataset is collected using a learning management system (LMS), which is a learner activity tracker tool that is connected by the internet. This data has numerical and categorical variables, so it is needed to have the right algorithm to classify data accurately and ensure data validity. In this study, the C.50 algorithm is used to test the data, where the data is divided into training data by 75% and testing data by 25%. And the result from the tested data, an accuracy of 71.667% is obtained.

Gray Level Co-ocurence Matrix untuk Pengekstrasian Ciri Topeng Cirebon Felix Indra Kurniadi; Vinnia Kemala Putri
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Cirebon mask is one of the intangible cultural heritage in Indonesia. It is one of the prominent cultural assets from Cirebon and becoming one of the identity Cirebon culture. However, the current condition people tend to forget the cultural asset and lack of help from the government makes the Cirebon mask become the third-rate assets. Our concern lays on the extinction of this Mask. We want to implement digitation and automatic identification using image processing techniques. In this paper, we applied the Gray Level Co-occurrence Matrix for extracting the features. K-Nearest Neighbour as the classifier. The best accuracy of this research is 40,67%

Visualisasi Algoritma sebagai Sarana Pembelajaran K-Means Clustering Alethea Suryadibrata; Julio Christian Young
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Algorithm Visualization (AV) is often used in computer science to represents how an algorithm works. Educators believe that visualization can help students to learn difficult algorithms. In this paper, we put our interest in visualizing one of Machine Learning (ML) algorithms. ML algorithms are used in various fields. Some of the algorithms are used to classify, predict, or cluster data. Unfortunately, many students find that ML algorithms are hard to learn since some of these algorithms include complicated mathematical equations. We hope this research can help computer science students to understand K-Means Clustering in an easier way.

Pengenalan Wajah Bebas Ekspresi Menggunakan Metode Nearest Feature Line dengan Representasi Ciri dalam Ruang Eigen Is Mardianto
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Facial recognition with different expressions is one part of the pattern recognition problem which is quite complex when compared to pattern recognition on a normal profile. The expression-free face recognition method using the Nearest Feature Line (NFL) technique works by finding the closest projection distance between feature vectors, assuming that the closer the projection distance of a feature vector (face) to another feature vector (face), the more similar the properties will be physical feature vector (face) which are close together. The NFL distance calculation is performed on the eigen dimensional space with the aim that the calculated feature vector (face) dimension has a much smaller dimension in order to increase the level of recognition accuracy and speed up computational time. The test results obtained indicate the NFL method provides a fairly good level of recognition accuracy in the average value of 76.7% with the advantage of low computational time needed when compared with other intelligent methods such as artificial neural network systems.

Komparasi Metode Multilayer Perceptron (MLP) dan Long Short Term Memory (LSTM) dalam Peramalan Harga Beras Steven Sen; Dedy Sugiarto; Abdul Rochman
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Rice is one of the main commodities in Indonesian society. The main problem with rice nationally is inflation of rice prices. Therefore, this research predicts the price of rice using Multilayer Perceptron (MLP) artificial neural network architecture and deep learning: Long Short Term Memory (LSTM) to anticipate these problems. The data used in this study are real data on rice prices during 2016 - 2019 obtained from PT. Food Station. The total dataset is 1307 with the distribution of 1123 as data train and 184 as test data. The final results obtained in this study are LSTM superior to MLP, with the value of Root Mean Square Error (RMSE) training data: 0.49 RMSE loss value of test data is 0.27. The most optimal LSTM model from 3 tests was carried out, namely the number of hidden layers = 16 and epochs = 150 times.

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Ni Made Satvika Iswari

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Kota tangerang,

Banten

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