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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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Rancang Bangun Sistem Rekomendasi Resep Masakan Khas Indonesia Menggunakan Metode Collaboration Collective Intelligence dan Slope One Adhi Kusnadi; Daniel Daniel
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Today, recipes are not just physical, but some are digital. So users do not have to store recipe books that have been purchased to find recipes for a dish. One of a website providing recommendations for digital recipe guides is dapursaji. This application helps users to search for recipes only by entering the ingredients of the food owned by the user. And will produce a list of dishes that use the material entered by the previous user. In addition there will be related recommendations after opening one of the recipes after the search. Not only that, this website can also provide the freedom to innovate, by means of all users can fill a new recipe in accordance with the innovation and creation itself. Then the recipe will be published and read by the public. Collaborative Collective Intelligence and Slope One methods are implemented in this design, and evaluation results show that as many as 89% of users surveyed have been satisfied with the suitability and usefulness of the built system. Index Terms—recipes, dish, collaborative Collective Intelligence, slope one

Aplikasi Rekomendasi Buku Pada Katalog Perpustakaan Universitas Multimedia Nusantara Menggunakan Vector Space Model Richard Firdaus Oeyliawan; Dennis Gunawan
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Library is one of the facilities which provides information, knowledge resource, and acts as an academic helper for readers to get the information. The huge number of books which library has, usually make readers find the books with difficulty. Universitas Multimedia Nusantara uses the Senayan Library Management System (SLiMS) as the library catalogue. SLiMS has many features which help readers, but there is still no recommendation feature to help the readers finding the books which are relevant to the specific book that readers choose. The application has been developed using Vector Space Model to represent the document in vector model. The recommendation in this application is based on the similarity of the books description. Based on the testing phase using one-language sample of the relevant books, the F-Measure value gained is 55% using 0.1 as cosine similarity threshold. The books description and variety of languages affect the F-Measure value gained. Index Terms—Book Recommendation, Porter Stemmer, SLiMS Universitas Multimedia Nusantara, TF-IDF, Vector Space Model

Perbandingan Algoritma kNN, C4.5, dan Naive Bayes dalam Pengklasifikasian Kesegaran Ikan Menggunakan Media Foto Ni Made Satvika Iswari; Wella Wella; Ranny Ranny
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Indonesia merupakan negara kepulauan yang memiliki berbagai jenis keanekaragaman ikan. Potensi perikanan laut sebesar 6,5 juta ton per tahun, namun jumlah produksinya hanya mencapai 5,06 juta ton. Hal ini menunjukan proses produksi belum optimal. Proses produksi serta pemilahan yang masih tradisional membuat produksi berjalan lambat. Dalam penelitian ini dikembangkan sebuah metode untuk mengklasifikasikan kesegaran ikan berdasarkan citra digital ikan. Adapun algoritma yang digunakan adalah kNN, C4.5, dan Naïve Bayes. Berdasarkan hasil uji coba yang dilakukan, algoritma kNN memberikan nilai akurasi yang tertinggi diantara algoritma lainnya. Sehingga kNN dinilai cocok digunakan untuk mengklasifikasikan kesegaran ikan. Metode yang dihasilkan dalam penelitian ini diharapkan dapat membantu mengotomatisasi proses produksi yang sebelumnya manual. Index Terms — kNN, C4.5, Naïve Bayes, Pengolahan Citra Digital, Tingkat Kesegaran Ikan.

Perbandingan Local Binary Pattern untuk Klasifikasi Sel Darah Putih Felix Indra Kurniadi
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

In recent year, a lot of researches try to overcome problem in recognition and classify white blood cells to help hematologists diagnose white blood cells disease such blood cancer, leukemia and AIDS. This paper compares several methods Local Binary Pattern such as Local Binary Pattern Uniform, Local Binary Pattern Rotation Invariant and Local Binary Pattern Rotation Invariant Uniform to classify five types of white blood cells using two classifier: Support Vector Machine and K-Nearest Neighbour. Index Terms—LBP, LBP-U, LBP-RI, LBP-RIU, white blood cells

Sistem Pengenalan Bahasa Isyarat Indonesia dengan Menggunakan Metode Fuzzy K-Nearest Neighbor Agum Agidtama Gafar; Jayanti Yusmah Sari
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

The Indonesian Natural Sign System (SIBI) is one of the most natural languages of communication, especially for deaf and speech impaired. Deaf and speech impaired can understand and communicate with each other by using sign language, but some normal people will have difficulty understanding sign language with deaf and speech impunity to say. To overcome these problems need develop a system that is able to recognize the Indonesian Sign System (SIBI) which is expected capable of learning media in communicating between the deaf and normal humans. The introduction of the Indonesian Sign System (SIBI) will consists of three main stages: image acquisition, preprocessing and recognition. In this research the classification method used is Fuzzy KNearest Neighbor (FKNN) method. Based on the results of experiments conducted with the classification using the method Fuzzy K-Nearest Neighbor (FKNN) obtained an accuracy of 88%. Index Term— Fuzzy K-Nearest Neighbor, Sistem Isyarat Bahasa Indonesia (SIBI).

Implementasi Geofencing dalam Monitoring Rute Pengiriman Kendaraan di Sebuah Perusahaan Ekspedisi Joko Priono; Eko Budi Setiawan
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

This paper describe a geofencing approach in monitoring the routes used in the delivery of vehicles in a expedition company. Continuous technological development of information systems provide a variety approach on how to monitor a vehicle on the road. One of those approach is geofencing. Geofencing itself is an innovative technology that enables remote monitoring of a specific geographic areas. It can make a virtual area called geofence on a virtual map with different size and shape. This virtual area would be able to tracked mobile objects that enter or leave these area, and even how long the objects inside the area. The mobile objects that are going to be tracked are object that have GPS Tracking Unit. GPS Tracking Unit is an application or a tool that is used to figure out the position of an object. The position are based on geographical coordinate, latitude and longitude, and the data is received through a Global Positioning System. The implementation of the geofencing are going to use library from Google API. The combination of GPS Tracking and geofencing would be able to track, prevent or even restrict on specific routes that are going to be used in vehicle delivery. Index Terms— Pengawasan, GPS Tracker, Geofence area, Route information, Google API

Perbaikan Kualitas Citra Untuk Klasifikasi Daun Menggunakan Metode Fuzzy K-Nearest Neighbor Asih Setiyorini; Jayanti Yusmah Sari
Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Plants have many benefits for human life such as food, medicine, industry, environmental protection, even oxygen provider for other organisms. To know the types of plants is necessary. Classification of plants can be done with additional features of leaves in these plants. In determining whether or not the image identification process is needed a process of image quality improvement. Improved image quality is used to prepare the image in an ideal form so as not to cause problems and interpellation results as well. In this research the method used is Fuzzy K-Nearest Neighbor (FKNN) method. The Fuzzy K-Nearest Neighbor (FKNN) method is the most objective method. Based on the results of experiments conducted, Fuzzy K - Nearest Neighbor (FKNN) modeling method was obtained for 93% completeness. Keywords-Image quality improvement, Fuzzy KNearest Neighbor (FKNN)

Penggunaan Heaviside Activation Function pada Regresi Linear untuk Klasifikasi Diabetes Felix Indra Kurniadi; Vinnia Kemala Putri
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Diabetes is one of the diseases that rapidly increase in the world. One of the most used dataset for diabetes is Pima indian dataset. Pima indian have 8 features such as pregnancies, glucose, blood pressure, insulin, BMI, diabetes pedigree function and age. In this research we are comparing between Linear Regression using Heaviside Activation Function and Logistic Regression. Logistic regression gives better result compare linear regression using Heaviside Activation Function. Index Terms—Diabetes, Regresi, Heaviside Activation Function, Logistic Regression

Klasifikasi Diabetes Menggunakan Model Pembelajaran Ensemble Blending Vinnia Kemala Putri; Felix Indra Kurniadi
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Diabetes mellitus is one of the deadliest disease and it is increasing in occurrence through the world. This can be prevented by conducting early diagnosis and treatment. However, in developing countries, less than half of people with diabetes are diagnosed correctly which lead to lose of human lives. In this Big Data era, medical databases have enormous quantities of data about their patients. But this medical data may contain noise and a lot of useless information which may mislead the expert in making a decision for medical diagnosis. Data mining is a technique to that is very effective for medical applications for identifying patterns and extracting useful information for databases. This paper proposed a data mining approach using an ensemble blending method to tackle a diabetes prediction problem in Pima Indian Diabetes Dataset. We proposed a blending ensemble classifier approach using a combination of Decision Tree and Logistic Regression as base classifiers, and Support Vector Machine as a top blender classifier. Our approach reached accuracy of 81% and F1-score of 0.81 proves to be higher when compared with basic classifier without combination. Index Terms—diabetes, ensemble, data mining

Analisis Kesiapan Kebutuhan Infrastruktur Replikasi Basis Data pada Sekolah Musik Indonesia Solo Willy Sudiarto Raharjo; Gani Indriyanta; Amsal Maestro
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Sekolah Musik Indonesia (SMI) Solo is the center of SMI which has internal data using web-based application at appssmi.com site with SQL Server database and has not been backed up regularly. Database replication is a technique for copying and distributing data and database objects from one database to another and implementing synchronization so data consistency can be guaranteed. Replication can be implemented to the cloud by requiring Internet access. The main concern in SMI Solo was the quality access of the Internet connection and also infrastructure used in SMI Solo. The purpose of this research is to analyze the readiness of data replication infrastructure needs at SMI Solo. The results of the analysis are then used as the basis for making recommendations and design of information technology architecture in the implementation of SMI database replication. We concluded that the infrastructure owned by SMI Solo is sufficient to be used for database replication. This is demonstrated by the very satisfactory performance of the SMI Solo server network with 3.85 Mbps download throughput, 3.49 Mbps upload throughput, 0% packet loss, 25.88 ms delay, and 0.09 ms jitter. On database replication performance thorough test scenarios, average performance on snapshot replication is using for CPU 4.78%, DTU 5.94%, I/O 0.06% and log data I/O 5.25%. The average performance on transactional replication is CPU 0.09%, DTU 0.09%, data I/O 0%, and log I/O 0.04%. Some of the challenges in developing database replication infrastructure to be implemented in all SMI’s can run efficiently if each SMI has a local server and Internet network albeit with unstable throughput. Index Terms—Network Performance, Replication, Snapshot, Transactional

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Contact Name
Ni Made Satvika Iswari

Contact Email
satvika@umn.ac.id

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Journal Mail Official
ultimatics@umn.ac.id

Editorial Address
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Location
Kota tangerang,

Banten

INDONESIA