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Contact Name
Nizirwan Anwar
Contact Email
nizirwan.anwar@esaunggul.ac.id
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telkomnika@ee.uad.ac.id
Editorial Address
Ahmad Yani st. (Southern Ring Road), Tamanan, Banguntapan, Bantul, Yogyakarta 55191, Indonesia
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INDONESIA
TELKOMNIKA (Telecommunication Computing Electronics and Control)
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
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)
Articles 2,614 Documents
Sentiments analysis of customer satisfaction in public services using K-nearest neighbors algorithm and natural language processing approach Elik Hari Muktafin; Pramono Pramono; Kusrini Kusrini
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.17417

Abstract

Customer satisfaction is very important for public service providers, customer satisfaction can be delivered with a survey application or writing criticism that can be used to evaluate and improve service. Unfortunately, there are only a few customers who are willing to give an assessment. The survey application cannot represent the overall feeling of the customer, so it is necessary to analyze the content of the conversation between the customer and the service personnel to determine the level of customer satisfaction. In small amounts, it can be done manually, but in large quantities it is more effective to use the system. A solution is needed in the form of a system that converts voice conversations into text and analyzes customer satisfaction to obtain information for evaluation and improvement of services. This research uses K-nearest neighbors (KNN) and term frequency-inverse document frequency (TF-IDF) algorithm with natural language processing (NLP) approach to classify conversations into 2 classes, "satisfied" and " dissatisfied ". The results of this study received 74.00% accuracy, 76.00% precision and 73.08% recall. In conversations with the label "satisfied" shows customers satisfied with the service and fulfillment of customer desires, while in conversations with the label "not satisfied" customers are less satisfied with the waiting time.
Numerical Simulation of Chip Formation in Metal Cutting Process Zhao Yongjuan; Pan Yutian Pan Yutian; Huang Meixia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 3: September 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i3.827

Abstract

In order to study the chip formation mechanism in metal cutting process, based on finite element software ABAQUS, the paper established finite element model and carried out numerical simulation on serrated chip formation of Ni-base superalloy GH4169 and ribbon chip formation of 45# steel respectively. In addition, this paper also analyzed the influence law of three factors (cutting speed, feed rate, back cutting depth) on cutting force and the distribution rule of cutting heat in serrated chip formation of GH4169.
Resolution Improvement in Fabry-Perot Displacement Sensor Based on Fringe Counting Method Nur Izzati Ismail; Nor Hafizah Ngajikin; Nor Fadzlina Mohd Zaman; Maisarah Awang; Asrul Izam Azmi; Nik Noordini Nik Abd. Malik; Norazan Mohd Kassim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i4.123

Abstract

This paper presents an improved Fringe Counting Method (FCM) technique in order to enhance the displacement resolution of a Fabry-Perot Displacement Sensor (FPDS). A simulation model of a FPDS based on the improved FCM has been developed and simulated for nanometer displacement range by using MATLAB mathematical software. Unlike conventional FCM that analyzed the number of fringes produced over one time period, the improved FCM analyzed the number of fringes for one largest Free Spectral Range (FSR). In this work, the initial length of Fabry-Perot Interferometer (FPI) cavity has been set at 75 μm due to limitation of the machining precision equipment. For the displacement analysis, the improved FCM technique is used as an algorithm. The research results prove that this FPDS could detect displacement at 10nm resolution over a working range of 40 nm. It showed that the improved FCM technique managed to enhance the capability of the conventional FCM in detecting nanometer displacement. 
Balanced the Trade-offs Problem of ANFIS using Particle Swarm Optimization Dian Palupi Rini; Siti Mariyam Shamsuddin; Siti Sophiayati Yuhaniz
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1146

Abstract

Improving the approximation accuracy and interpretability of fuzzy systems is an important issue either in fuzzy systems theory or in its applications . It is known that simultaneous optimization both issues was the trade-offs problem, but it will improve performance of the system and avoid overtraining of data. Particle swarm optimization (PSO) is part of evolutionary algorithm that is good candidate algorithms to solve multiple optimal solution and better global search space. This paper introduces an integration of PSO dan ANFIS for optimise its learning especially for tuning membership function parameters and finding the optimal rule for better classification. The proposed method has been tested on four standard dataset from UCI machine learning i.e. Iris Flower, Haberman’s Survival Data, Balloon and Thyroid dataset. The results have shown better classification using the proposed PSO-ANFIS and the time complexity has reduced accordingly.
Expert System Modeling for Land Suitability based on Fuzzy Genetic for Cereal Commodities: Case Study Wetland Paddy and Corn Fitri Insani; Imas S Sitanggang; Marimin Marimin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1735

Abstract

 Nowadays, threats of food shortages are happen in Indonesia. Most of crops that are consumed as main food are cereals commodities. Cereals cultivation often experience some problems in determining whether land is suitable or not for the crops. Expert system can help researcher and practitioners to identify land suitability for cereal crops. In this research, an expert system model of land suitability for cereals crop was built. The model implemented soft computing methods to develop inference engine which combines fuzzy system and genetic algorithm. There are 16 parameters to define land suitability which consists of 12 numeric parameters and 4 categorical parameters. Two types of cereal crops that were used in this study namely wetland paddy and corn. Trapezoid membership function was used to represent fuzzy sets for numerical parameters. Genetic algorithm was used for tuning the membership function of fuzzy set for land suitability which consists of very suitable (S1), quite suitable (S2), marginal suitable (S3) and not suitable (N). This expert system is able to choose land suitability classes for cereals using the fuzzy genetic model with accuracy of 90% and 85% for corn and wetland paddy respectively.
Optimal Modulation Algorithm for Hybrid Clamped Three-Level Inverter Yi Liu; Guojun Tan; Xiaoqun He
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 4: December 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i4.3871

Abstract

The principle of a three phase hybrid clamped three-level inverter was presented. Taking sixty-four switch states into consideration, the operational states of hybrid clamped three-level inverter and different current circuits in different switch states were detailed derived. Optimal modulation algorithm was proposed based on the neutral small vectors by different combination, which can realize the automatic balancing of the neutral-point voltage with few switching cycles and did not need to measure the voltage of the clamped capacitors. The proposed modulation algorithm was also capable of restraining the turn-off over-voltage of the power switching devices effectively. Simulation results were given to verify the feasibility and correctness. Experimental results obtained by DSP-based implementation of the controller on 1 MW prototype show good performance in terms of DC-bus voltages regulation (small neutral point potential function and low DC ripple coefficient) and good sinusoidal current.
Important Parameters for Hand Function Assessment of Stroke Patients H. Abdul Rahman; C. F. Yeong; K. X. Khor; E. L.M. Su
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.7228

Abstract

Clinical scales such as Fugl-Meyer Assessment and Motor Assessment Scale are widely used to evaluate stroke patient's motor performance. However, the scoring systems of these assessments provide only rough estimation, making it difficult to objectively quantify impairment and disability or even rehabilitation progress throughout their rehabilitation period. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessment scales are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear. This paper discusses the important parameters in order to assess the hand function of stroke patients. This knowledge will provide a contribution to the development of a new robot-based assessment device effectively by including the important parameters in the device. The important parameters were included in development of iRest and yielded promising results that illustrate the potential of the important parameters in assessing the hand function of stroke patients.
Self-adaptive Software Modeling Based on Contextual Requirements Aradea Aradea; Iping Supriana; Kridanto Surendro
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7032

Abstract

The ability of self-adaptive software in responding to change is determined by contextual requirements, i.e. a requirement in capturing relevant context-atributes and modeling behavior for system adaptation. However, in most cases, modeling for self-adaptive software is does not take into consider the requirements evolution based on contextual requirements. This paper introduces an approach through requirements modeling languages directed to adaptation patterns to support requirements evolution. The model is prepared through contextual requirements approach that is integrated into MAPE-K (monitor, anayze, plan, execute - knowledge) patterns in goal-oriented requirements engineering. As an evaluation, the adaptation process is modeled for cleaner robot. The experimental results show that the requirements modeling process has been able to direct software into self-adaptive capability and meet the requirements evolution.
The antecedent of citizen intention use of e-government service Taqwa Hariguna; Chung-Wen Hung; Husni Teja Sukmana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.11588

Abstract

The purpose of this study was to integrate citizen perceived value into an expectation- confirmation model (ECM) and to explain citizen intention use of e-government services. After reviewing both ECM and citizen perceived values, integrated models were designed. This study was compared to the basic ECM; this study revealed that the integration of ECM with citizen perceived value can provide a concerted solution to illustrate some factors and how it can influence citizen intention use for e-government services.
Depression and anxiety detection through the closed-loop method using DASS-21 Setiyo Budiyanto; Harry Candra Sihombing; Fajar Rahayu I. M.
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12619

Abstract

The change of information and communication technology has brought many changes in daily life. The way humans interacting is changing. It is possible to express each form of communication directly and instantly. Social media has contributed data in size, diversity and capacity and quality. Based on it, the idea was to see and measure the tendency of depression and anxiety through social media using the Closed-Loop method using Facebook text mining posts. Through the stages of pre-processing including text extraction using the Naïve Bayes machine learning model for text classification, the early signs of depression and anxiety are measured using DASS-21 parameter. In total, 22,934 Facebook posts were contributed as training and learning data collected from July 2017 until July 2018. As a results, analysis and mapping of social demographics of users that are usually as a trigger of depression, and anxiety, such as grief, illness, household affairs, children education and others are available.

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