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Jurnal ULTIMATICS
ISSN : 20854552     EISSN : 2581186X     DOI : -
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.
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Articles 190 Documents
Sistem Pendukung Keputusan Penerima Beasiswa UMN dengan Profile Matching Marvin Apriyadi; Seng Hansun
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1803.487 KB) | DOI: 10.31937/ti.v10i1.702

Abstract

This paper describes about the design and development of UMN scholarship decision support system using Profile Matching method. At Universitas Multimedia Nusantara (UMN), there are scholarships for students in order to ease the burden of education costs. There are achievement scholarships, scholarships for students whose parents died, and non-academic scholarships. Decision support systems play an important role in the termination of the final decision, and therefore this application is built by implementing the method of Profile Matching to aid in the selection of the scholarship decisions for students whose parent were died and non-academic scholarship. Profile Matching is a method that aims at taking decisions by assuming that there is an ideal level of predictor variables that must be met by the subjects studied, instead of the minimum rate that must be met or passed. From the results, it can be concluded that this method successfully implemented into applications that can help in decision making process. Result of user satisfaction level for this application is 72%, the result of manual calculation with the application calculation results is not much different so that this application can assist in supporting the UMN scholarship decision. Index Terms— decision support system, non-academic scholarship, Profile Matching, scholarships for student whose parents died, UMN
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1355.624 KB) | DOI: 10.31937/ti.v10i1.708

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1436.767 KB) | DOI: 10.31937/ti.v10i1.709

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2797.145 KB) | DOI: 10.31937/ti.v10i1.710

Abstract

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
Sistem Penunjang Keputusan Penilaian Kinerja Karyawan Berprestasi Menggunakan Acuan MBO dan Metode AHP Menggunakan Aplikasi Expert Choice Rudi Sutomo; Johny Hizkia Siringo Ringo
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2584.502 KB) | DOI: 10.31937/ti.v10i1.756

Abstract

In the determination of employees who have the achievement required assessment of the assessment. There are several policy setting criteria to be able to prevent subjective decision-makers such as the influence of "likes and dislikes", so it is often wrong to judge employees. This paper is intended to provide a solution to the problem of choosing qualified and qualified employees using the AHP method and using decision support systems application Expert Choice to assist decision making in determining outstanding employees based on MBO method references. From the result of comparison of criteria weight that has been inputted and has been adjusted with comparison matrix Sub Criteria of Achievement then got that occupy the highest priority data that is consumer satisfaction with point 0,434, discipline with point 0,285, operational performance with point 0,071 and achievement with point 0,058 with inconsistency 0, 03 with 0 missing judgments. The results of AHP calculations will be applied to produce the highest intensity of employee priority outputs so that employees with the highest score are eligible for rewards or rewards. Index Terms—AHP, Aplikasi Expert Choice, MBO, SPK
Ekstraksi Kebutuhan Aplikasi Berdasarkan Feedback Pengguna Menggunakan Naïve Bayes dan Gamifikasi Andre Rusli
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2251.751 KB) | DOI: 10.31937/ti.v10i1.778

Abstract

Requirements engineering is a series of activities which aims to elicit, analyze, evaluate, and document the requirements of a system that is being developed. The activities do not stop after the product is deployed but continues as the users use the product and provide feedbacks to the system and matter how decent the functionalities of a product are, if it cannot address the correct problem and/or opportunities of the stakeholders or users, the product cannot be considered useful. That being said, not all stakeholders are willing to participate in providing useful feedbacks to improve the product after deployment, for many reasons. Gamification is considered as an opportunity that can be utilized to improve the motivation of user to use a product by implementing game design elements into an existing software product, thus increasing user participation to contribute in providing useful feedbacks and evolving requirements of a software product. This research proposes a model to support engineers in motivating users to provide feedbacks using gamification and also Naïve Bayes Classifier to classify user feedbacks into categories needed by the developer to extract the requirements stated in the feedback, such as bug reports, feature request, user experiences, etc. Kata Kunci—requirements engineering, gamification, Naïve Bayes, user feedback
Situsparu: Sistem Pakar Untuk Deteksi Penyakit Tuberkulosis Paru Ricky Surya; Dennis Gunawan
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1975.853 KB) | DOI: 10.31937/ti.v10i1.781

Abstract

Tuberculosis is an infectious disease caused by mycobacterium tuberculosis. It can affect some parts of the body: lungs, lymph nodes, intestines, kidneys, endometrium, bones, and brain. According to the survey of tuberculosis prevalence conducted by Republic of Indonesia Ministry of Health in 2013-2014, Indonesia was the second country in the world with the most case of tuberculosis. It makes Indonesia become a country with emergency in lungs tuberculosis. An expert system for lungs tuberculosis detection is built to help people detecting the possibility of suffering from lungs tuberculosis. Therefore, it is hoped that the lungs tuberculosis patient can have early treatment. Certainty factor is used to solve the uncertainty problem delivered by the doctor when examining the patient. Thus, certainty factor is an appropriate method to be used in the expert system for detecting certain disease. This method has been correctly implemented, proved by comparing system detection result to manual calculation result. The expert system has 81.25% accuracy, 83.49% success using DeLone and McLean model, and a cronbach alpha of 0.82 which indicates a good reliability based on the indicators used in the questionnaire. Index Terms— Certainty Factor, Disease Detection, Expert System, Pulmonary Tuberculosis, Situsparu
Aplikasi Survei Ubinan Berbasis Android Betti Noviyani; Eko Budi Setiawan
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2609.206 KB) | DOI: 10.31937/ti.v10i1.837

Abstract

Central Bureau of Statistics is one of the institutions that collect data in all fields and one of them is data of food crops. The Central Bureau of Statistics conducted the ubinan survey to obtain food crop data. Found some obstacles in the field in conducting ubinan survey. This can reduce the quality of food crop data if not quickly addressed. Given food crop data is very important for the life of the community, it takes a tool that can help the surveyor so that the data produced can be more quickly and accurately. In this research will be made an application with a given feature that is to store the coordinate point of survey implementation, to provide location information on harvest measurement in the field, to detect harvest income writing errors, display compass as a tool for determining the direction of the wind. So that the work of ubinan survey can be further improved the quality of food crop data in the Central Bureau of Statistics. Index Terms— Android, Survei, Ubinan, Tanaman Pangan.
Pencarian Question-Answer Menggunakan Convolutional Neural Network Pada Topik Agama Berbahasa Indonesia Rizqa Raaiqa Bintana; Chastine Fatichah; Diana Purwitasari
Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2494.968 KB) | DOI: 10.31937/ti.v10i1.842

Abstract

Community-based question answering (CQA) is formed to help people who search information that they need through a community. One condition that may occurs in CQA is when people cannot obtain the information that they need, thus they will post a new question. This condition can cause CQA archive increased because of duplicated questions. Therefore, it becomes important problems to find semantically similar questions from CQA archive towards a new question. In this study, we use convolutional neural network methods for semantic modeling of sentence to obtain words that they represent the content of documents and new question. The result for the process of finding the same question semantically to a new question (query) from the question-answer documents archive using the convolutional neural network method, obtained the mean average precision value is 0,422. Whereas by using vector space model, as a comparison, obtained mean average precision value is 0,282. Index Terms—community-based question answering, convolutional neural network, question retrieval
Identifikasi Tingkat Kematangan Buah Pisang Menggunakan Metode Ektraksi Ciri Statistik Pada Warna Kulit Buah nina sularida limin; Jayanti Yusmah Sari; Ika Purwanti Ningrum Purnama
Ultimatics : Jurnal Teknik Informatika Vol 10 No 2 (2018): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1526.79 KB) | DOI: 10.31937/ti.v10i2.1004

Abstract

Abstract—The Banana (musa paradical) is one of the national superior fruit production which is rich in vitamins. The level of banana production in Indonesia is above other fruit commodities. However, one of the postharvest problems for bananas produced on a large scale or industry is in the sorting of bananas. During this time the banana fruit is identified by the level of maturity based on the analysis of the skin color of the fruit visually the human eye that has limitations. The identification process like this has several disadvantages including requiring more energy to sort, and the level of perception of fruit maturity produced can be different because humans can experience fatigue, not always consistent, and human judgment is also subjective. To overcome this problem, this study builds a system to identify the maturity level of bananas using the extractive method of statistical features based on the skin color of bananas. The statistical feature extraction method used in this study is the maximum, minimum, and mean values ​​of pixels for RGB and HSV color spaces. The system built has been tested using 40 datasets of image of bananas and shows the results of good accuracy. Index Terms—enter key words or phrases in alphabetical order, separated by commas

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