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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 2,614 Documents
 106   107   108   109   110 
An Early Detection Method of Type-2 Diabetes Mellitus in Public Hospital Bayu Adhi Tama; Rodiyatul F. S.; Hermansyah Hermansyah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 2: August 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i2.699

Abstract

Diabetes is a chronic disease and major problem of morbidity and mortality in developing countries. The International Diabetes Federation estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type-2 diabetes mellitus (T2DM) is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of T2DM from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context, data mining and machine learning could be used as an alternative way help us in knowledge discovery from data. We applied several learning methods, such as instance based learners, naive bayes, decision tree, support vector machines, and boosted algorithm acquire information from historical data of patient’s medical records of Mohammad Hoesin public hospital in Southern Sumatera. Rules are extracted from Decision tree to offer decision-making support through early detection of T2DM for clinicians. 
Hierarchical Bayesian of ARMA Models Using Simulated Annealing Algorithm S. Suparman; Michel Doisy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 1: March 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i1.12

Abstract

When the Autoregressive Moving Average (ARMA) model is fitted with real data, the actual value of the model order and the model parameter are often unknown. The goal of this paper is to find an estimator for the model order and the model parameter based on the data. In this paper, the model order identification and model parameter estimation is given in a hierarchical Bayesian framework. In this framework, the model order and model parameter are assumed to have prior distribution, which summarizes all the information available about the process. All the information about the characteristics of the model order and the model parameter are expressed in the posterior distribution. Probability determination of the model order and the model parameter requires the integration of the posterior distribution resulting. It is an operation which is very difficult to be solved analytically. Here the Simuated Annealing Reversible Jump Markov Chain Monte Carlo (MCMC) algorithm was developed to compute the required integration over the posterior distribution simulation. Methods developed are evaluated in simulation studies in a number of set of synthetic data and real data.
APLIKASI MASTER SWITCH OTOMATIS BERBASIS MIKROKONTROLER AT89C51 Prastyono Eko Pambudi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 5, No 2: August 2007
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v5i2.1350

Abstract

Listrik merupakan salah satu kebutuhan penunjang yang sangat penting bagi kelangsungan hidup manusia. Dari aspek paling sederhana sampai ke proses penting yang melibatkan pembuatan alat-alat pendukung kehidupan manusia, keseluruhan proses-proses tersebut memerlukan tenaga listrik. Permasalahan yang timbul dengan adanya kebutuhan listrik yang bersifat kontinyu akan terjadi pada saat pembangkit tenaga utama mengalami kerusakan atau kegagalan operasi. Penelitian ini merancang suatu prototipe dari sebuah sistim otomatis yang dikendalikan oleh mikrokontroler. Dengan metode pengaturan ini, sistem pensaklaran tegangan 220Vac dari PLN dan 220Vac keluaran DC to AC converter (pengganti genset) dapat dikendalikan menggunakan master switch secara otomatis. Selain itu proses stater dan mematikan kembali juga dapat dikendalikan secara otomatis. Hasil pengujian dan analisis yang telah dilakukan menunjukkan bahwa pengaturan motor stater dan choke selenoid genset menggunakan mikrokontroler terbukti dapat dilakukan termasuk pengaturan proses stater dan mematikan genset secara otomatis. Sistem akan tetap stabil dan akurat selama DC to AC converter (pengganti genset) dan batere yang digunakan berada dalam kondisi prima. Persyaratan ini mutlak harus diperhatikan agar proses stater genset tidak terlalu lama dan genset mudah dimatikan hanya dengan menutup choke.
Critical Success Factor in Monetizing Blog Andika Rizky; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3041

Abstract

Blog usage has transformed from its initial function as a digital diary into a legitimate form of mainstream media. Nowadays any member of the public can generate income from blogging through monetization even though various factors affect the results of this process. Four factors were identified: traffic, search engine optimization (SEO), post frequencies, and media usage. This study examines the level of importance of these factors through practical implementation into blogs then quantitatively determine which factor is critical for the success of blog monetization. An empirical analysis based on thirty samples of blogs were performed to assess the impact of the received income. The finding showed that the revenue for most of the blogs increased after the implementation of critical factors with SEO being the most critical of all the factors.
FPGA Based Pattern Generation and Synchonization for High Speed Structured Light 3D Camera Muhammad Atif; Sukhan Lee
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6146

Abstract

Recently, structured light 3D imaging devices have gained a keen attention due to their potential applications to robotics, industrial manufacturing and medical imaging. Most of these applications require high 3D precision yet high speed in image capturing for hard and/or soft real time environments. This paper presents a method of high speed image capturing for structured light 3D imaging sensors with FPGA based structured light pattern generation and projector-camera synchronization. Suggested setup reduces the time for pattern projection and camera triggering to 16msec from 100msec that should be required by conventional methods.
Wireless Sensor Network over High Altitude Platform Veronica Windha Mahyastuty; Iskandar Iskandar; Hendrawan Hendrawan; M. Sigit Arifianto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 1: February 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i1.8391

Abstract

One of Machine Type Communication (MTC) applications is Wireless Sensor Network (WSN). WSN is an intelligent network application system to collect, integrate, and transmit data autonomously. Sensor nodes in WSN, communicate over short distance via a wireless medium and collaborate to accomplish a common task, such as enviroment monitoring, military surveillance and industrial process control. The constraining aspect of WSN usage is the limited power of each sensor node, so energy efficiency becomes an important issue in WSN. Routing is a function in WSN, which consumes a substantial amount of energy. One of the routing protocols that can increase the energy efficiency of WSN is Low Energy Adaptive Clustering Hierarchy (LEACH). In this paper, High Altitude Platform (HAP) is used to replace Base Station (BS) as sink node in WSN. HAP is designed at altitudes of 17, 20 and 22 km. Then WSN over HAP using the LEACH routing protocol evaluated its performance. Performance indicators that we evaluated are engergy consumption, number of dead nodes and total average packets which is sent to HAP. From a series of simulations conducted, the results obtained that the higher the laying of HAP, then the coverage area will be greater. So that the energy consumption will be smaller, the number of dead node less and the avarage of total packet delivered to the HAP will be greater.
Fuzzy Rule-based Classification Systems for the Gender Prediction from Handwriting Lala Septem Riza; Aldi Zainafif; Rasim Rasim; Shah Nazir
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.9478

Abstract

The handwriting is an object that can describe information about the author implicitly. For example, it is able to predict the gender. Recently, the gender prediction based on handwriting becomes an interesting research. Even in 2013, an competition for prediction gender from handwriting has been held by Kaggle. However, the accuracies of current approaches are relatively low. So, in this study, we attempt to implement Fuzzy Rule-Based Classification Systems (FRBCSs) for gender predictions from handwriting. Three stages are conducted to achieve the objective, as follows: defining some features based on Graphology Techniques (e.g., pressure, height, and margin on writing), collecting real datasets, processing on digital images (i.e., image segmentation, projection profiles, and margin calculation, etc.), and implementing FRBCSs. The implemented algorithm based on FRBCSs in this research is Chi’s Algorithm, which is a method based on Fuzzy Logic for classification tasks. Moreover, some experiments and analysis, involving 75 respondents consisting of 36 males and 39 females, have been done to validate the proposed model. From the simulations, the classification rate obtained is 76%. Besides improving the accuracy rate, the proposed model can provide an understandable model by utilizing fuzzy rule-based systems.
Dissemination of technology information through YouTube: a case of renewable energy technology Muhammad Kunta Biddinika; Mochamad Syamsiro; Srikandi Novianti; Bakhtiyor Nakhshiniev; Muhammad Aziz; Fumitake Takahashi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.10124

Abstract

Internet video sharing has been used by scholars for two main purposes. First, it is for informal scholarly communication including teaching and academic conferences. Second, it is for engagement tool by contemporary society. Renewable energy technology has also been utilizing internet video sharing technology for those purposes. It is a promotional tool to disseminate information about the technology as well as a media for public engagement with renewable energy issues. This paper reviews how YouTube, the most popular internet video sharing website whose content is created and accessed publicly for free of charge, has been elaborated in scholarly publication in the various fields prior to showing how renewable energy is portrayed in YouTube. By using a hundred YouTube most viewed videos, this paper presents an in-depth and systematic measurement study on the characteristics of YouTube videos on renewable energy issues.
Time-based α+ miner for modelling business processes using temporal pattern Yutika Amelia Effendi; Riyanarto Sarno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.12733

Abstract

Business processes are implemented in an organization. When a business process is run, it generates event log. One type of event log is double timestamp event log. Double timestamp has the start and complete time of each activity executed in the business process and has a close relationship with temporal pattern. In this paper, seven types of temporal pattern between activities were presented as extended version of relations used in the double timestamp event log. Since the event log was not always executed in sequential way, therefore using temporal pattern, event log was divided into several small groups to mine the business process both sequential and parallel. Both temporal pattern and Time-based α+ Miner algorithm were used to mine process model, determined sequential and parallel relations and then evaluated the process model using fitness value. This paper was focused on the advantages of temporal pattern implemented in Time-based α+ Miner algorithm to mine business process. The results also clearly stated that the proposed method could present better result rather than that of original α+ Miner algorithm.
Power system state estimation using teaching learning-based optimization algorithm Surender Reddy Salkuti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14159

Abstract

The main goal of this paper is to formulate power system state estimation (SE) problem as a constrained nonlinear programming problem with various constraints and boundary limits on the state variables. SE forms the heart of entire real time control of any power system. In real time environment, the state estimator consists of various modules like observability analysis, network topology processing, SE and bad data processing. The SE problem formulated in this work is solved using teaching leaning-based optimization (TLBO) technique. Difference between the proposed TLBO and the conventional optimization algorithms is that TLBO gives global optimum solution for the present problem. To show the suitability of TLBO for solving SE problem, IEEE 14 bus test system has been selected in this work. The results obtained with TLBO are also compared with conventional weighted least square (WLS) technique and evolutionary based particle swarm optimization (PSO) technique.

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