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Risanuri Hidayat
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Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
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INDONESIA
Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Published by Universitas Gadjah Mada
ISSN : 23014156     EISSN : 24605719     DOI : 10.22146/jnteti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, Power Distribution, Power Conversion, Protection Systems, Electrical Material 3. Signals, Systems, and Electronics: Digital Signal Processing Algorithm, Robotic Systems and Image Processing, Biomedical Instrumentation, Microelectronics, Instrumentation and Control 4. Communication Systems: Management and Protocol Network, Telecommunication Systems, Wireless Communications, Optoelectronics, Fuzzy Sensor and Network
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 16 Documents
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Search results for , issue "Vol 7 No 3: Agustus 2018" : 16 Documents clear
Ekstraksi Frasa Kunci pada Penggabungan Klaster berdasarkan Maximum-Common-Subgraph Adhi Nurilham; Diana Purwitasari; Chastine Fatichah
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Document clustering based on topic similarities helps users in searching from a collection of scientific articles. Topic labels are necessesary for describing subjects of the document clusters. Clusters with related subjects or contextual similarities can be merged to produce more descriptive labels. Relations between those words in one context can be modelled as a graph. Instead of single word, this paper proposed cluster labeling of phrases from scientific articles withcluster merging based on graph. The proposed method begins with K-Means++ for clustering the scientific articles. Then, the candidates of word phrases from document clusters are extracted using Frequent Phrase Mining which inspired by Apriori algorithm. Each cluster result has a representation graph from those extracted word phrases. An indicator value from each graph shows any similarities of graph structures which is calculated with Maximum Common Subgraph (MCS). Those clusters are merged if there are any structure similarities between them. Topic labels of clusters are keyword phrases extracted from a representation graph of previous merged clusters using TopicRank algorithm. The merging process which becomes the contribution of this paper is considering topic distribution within clusters for phrase extraction. The proposed method evaluationis performed based on topic coherence of the merged clusterslabel. The results show that proposed method can improve topic coherence on the merged clusters with MCS graph size percentage as the key factor.Further observation shows that merged cluster labels consistent to MCS graph.
Pengenalan Viseme Dinamis Bahasa Indonesia Menggunakan Convolutional Neural Network Aris Nasuha; Tri Arief Sardjono; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1057.97 KB)

Abstract

There has been very little researches on automatic lip reading in Indonesian language, especially the ones based on dynamic visemes. To improve the accuracy of a recognition process, for certain problems, choosing suitable classifiers or combining of some methods may be required. This study aims to classify five dynamic visemes of Indonesian language using a CNN (Convolutional Neural Network) and to compare the results with an MLP (Multi Layer Perceptron). Varying some parameters theoretically improving the recognition accuracy was attempted to obtain the best result. The data includes videos on pronunciation of daily words in Indonesian language by 28 subjects recorded in frontal view. The best recognition result gives 96.44% of validation accuracy using the CNN classifier with three convolution layers.
Perancangan Alat Bantu Analisis Rapid Entire Body Assessment (REBA) Berbasis Aplikasi Android Dawi Karomati Baroroh; Ramadhan Ramadhan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Work posture analysis is important because the wrong work posture can cause discomfort and fatigue in workers that can cause musculoskeletal disorder (MSDs). Rapid entire body assessment (REBA) is one of semi-quantitative posture analysis methods that are sensitive to the risk of MSDs in various occupational types. REBA analysis is usually done manually, so it takes a long time and there is a possibility of error. Therefore, it is necessary to design an REBA tool based on Android application analysis to facilitate and accelerate in posture analysis. This paper designed a tool of REBA analysis based on the Android application using MIT App Inventor 2. Furthermore, verification tests, validation, and usability tests are performed on the application design. There is also time comparison of REBA analysis manually and by using application (case study in Small and Medium Industries Aluminum, Giwangan, Yogyakarta). The results of this study indicate that the design of REBA applications based on Android has met the verification and validation test. Based on the usability test performed using System Usability Scale (SUS) method, the value obtained is 63.5, which means quite useful. In addition, the results of comparative REBA analysis times indicate a significant difference between manual calculation time and using the application, with time savings of REBA analysis using application of 51.19%.
Penggunaan Smartphone Android sebagai Alat Analisis Kebutuhan Kandungan Nitrogen pada Tanaman Padi Eko Budi Setiawan; Risa Herdianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1505.406 KB)

Abstract

Nitrogen (N) is one of the most important nutrients for the growth of rice crops. Unbalanced and excessive use of N-fertilizers causes environmental pollution, reduces quality of the crop, and increases pest pressure, in addition to the increasingcost to farmers from excessively applied fertilizers and pesticides. The goal of this paper is to build mobile applications which can analyze and recommend nitrogen elemental requirements in rice plants based on the color of rice leaves. This application has embedded a set of stages of the process for image processing and classification which is used to analyze the color of rice leaves captured through a smartphone camera. Image processing in this application is a feature extraction of red, green, and blue (RGB) values to obtain a characteristic on the leaf color image. Then the result of feature extraction is used to classify the color level of rice leaf by using a K-Nearest Neighbor method. The results of accuracy test show that accuracy of the application in analyzing and recommending nitrogen fertilizer needed by rice crops, on average, is 66.67%.
Enkripsi SMS dengan Menggunakan One Time Pad (OTP) dan Kompresi Lempel-Ziv-Welch (LZW) Fitri Diani; Yudi Widhiyasana
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1137.011 KB)

Abstract

Short Message Service (SMS) is one of the features on a mobile phone. This feature is widely used because it is easy to use and does not require the latest telecommunications network connection. Short messages in the form of SMS consistsof 140 characters at the most.The message is sent through infrastructure in telecommunications providers. Using this process, there is a possibility that the sent message is leaked. Therefore, data encryption is required to maintain the message confidentiality. Unfortunately, encryption mechanism uses cipher to encrypt data, which causes another problem. The type of cipher is symmetric or asymmetric, and both cipher mechanism will increase the length of the sent messages. In this paper, One Time Pad encryption method and LZW compression method is used to optimize the message length.
Pendeteksi Sinyal Jual/Beli Saham dengan Fuzzy Rule-Based Evidential Reasoning dan C-means Clustering M. Lutfi Sulthon A.S.; Agung B. Prasetijo; Maman Somantri
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Stocks are securities indicating the share of ownership of a company. In stock market, most of traded stocks fluctuate in price at all times and traders take an advantage for taking profit. Traders often use technical analysis to determine the trend of stock price movements. The problem is on how traders take positions (buying/selling stocks) with minimal trading decision so they can maximize profits. Fuzzy rule-based evidential reasoning approach can map the conditions of stock movements. Clustering can help the mapping conducted with a high degree of equality with each other. One of the clustering methods is fuzzy C-means clustering. This method is used to determine the number of membership functions for each attribute. To increase profit/Return of Investment (ROI), verification of output decision is required to analyze stock trends when placing buy or sell. From the results experimented, an ROI of 83.80% profit is obtained.
Pengujian Statis pada Sistem Server Web Berbasis Cluster dengan Algoritme Never Queue Nongki Angsar
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

The increase of web traffic and the development of network bandwidth are relatively faster than the development of microprocessor technology. This causes one point server platform no longer adequate to meet the needs of system scalability web server. Thus, multiple server platforms are the answer. One solution that has been known is a cluster-based web server system. This paper designs and develops cluster based web server system with Never Queue Algorithm. The system is then tested with a web workload distribution testing. The testing iscarried out by generating HTTP workloads statically (with fixed HTTP request rate) from the client to a web server system pool. The result shows that HTTP requests are well-distributed to web server system pool by Never Queue Algorithm. HTTP reply rate tends to be stable at average of 1,031.8 replies/s because the system is saturated, while TCP connection rate, response time, and error, tend to rise along with the rise of HTTP request rate. As for throughput, the average is 2.983 Mbps. Correlation between stability and the rise of error is, at the saturated point, bigger HTTP requests yield bigger errors.
Edugame “Etam-Tainment” Pembelajaran Bahasa Kutai dengan Shuffle Random dan Agen Cerdas Sefty Wijayanti; Asep Nurhuda; Reza Andrea
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

The research entitled Educational Game (Edugame) "Etam-tainment" is a research development of Puzzle Game type, designed to hone memory in the form of language. In this game, players must arrange letters in random and create a word in Kutai language. Artificial Intelligence (AI) technology will also be applied to this research. Using the Finite State Machine model method, this game will have game agent character that will accompany a child to play like a teacher. Game agent in the form of virtual teacher can give a sad and happy expression accordingly from the game environment. The results of this study make this edugame become more interesting and interactive to children. Game agent AI will accompany child in this game is like teacher.
Klasifikasi Nyeri pada Video Ekspresi Wajah Bayi Menggunakan DCNN Autoencoder dan LSTM Yosi Kristian; I Ketut Eddy Purnama; Effendy Hadi Sutanto; Lukman Zaman; Esther Irawati Setiawan; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Babies are still unable to inform the pain theyexperience, therefore, babies cry when experiencing pain. With the rapid development of computer vision technologies, in the last few years, many researchers have tried to recognize pain from babies expressions using machine learning and image processing. In this paper, a research using Deep Convolution Neural Network (DCNN) Autoencoder and Long-Short Term Memory (LSTM) Network is conducted to detect cry and pain level from baby facial expression on video. DCNN Autoencoder isused to extract latent features from a single frame of baby face. Sequences of extracted latent features are then fed to LSTM sothe pain level and cry can be recognized. Face detection and face landmark detection is also used to frontalize baby facial imagebefore it i s processed by DCNN Autoencoder. From the testing on DCNN autoencoder, the result shows that the best architecture used three convolutional layers and three transposed convolutional layers. As for the LSTM classifier, the best model is using four frame sequences.
Optimasi Support Vector Machine untuk Memprediksi Adanya Mutasi pada DNA Hepatitis C Virus Berlian Al Kindhi; Tri Arief Sardjono; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Hepatitis C Virus (HCV) is a virus which capable of infecting RNA that can lead to changes in the DNA sequence. This change of DNA arrangement is called genetic mutation. Every mutation occurs in HCV, it will be called a new subtype. Over time, HCV subtypes increase, and will continue to grow as the HCV mutation cycle progresses faster. Therefore, a way to find a mutation in millions of sequences in the gene bank is needed. This study tested six types of Support Vector Machine (SVM) methods to determine the best SVM kernel performance in the application of HCV DNA sequence detection in isolatedDNA. The tested SVM kernel was linear, quadratic, cubic, fine Gaussian, median Gaussian, and coarse Gaussian. The data set is 1000 isolated DNA consisting of 500 isolated Homo Sapiens and 500 isolated HCV. Firstly, the data set will go through the pattern search process using the Edit Levenshtein Distance method, then the result of the processing will be the variable x in SVM. The target or variable y on SVM is the positive or negative value of the isolated against HCV. The results show that among the six types of SVM methods being tested, the method of fine Gaussian SVM has the lowest performance of 77.4%. The SVM method is tested by performing optimizations on the determination of the hyperplane. The test results proved that the SVM method is able to analyze the presence of HCV mutations in isolated DNA with an accuracy of 99.8%.

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