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Journal of ICT Research and Applications
Published by Institut Teknologi Bandung
ISSN : 23375787     EISSN : 23385499     DOI : https://doi.org/10.5614/itbj.ict.res.appl.
Core Subject : Science,
Computer Science & IT
Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 7 Documents
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Search results for , issue "Vol. 13 No. 1 (2019)" : 7 Documents clear
Accessibility Degradation Prediction on LTE/SAE Network Using Discrete Time Markov Chain (DTMC) Model Hendrawan Hendrawan
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.1

Abstract

In this paper, an algorithm for predicting accessibility performance on an LTE/SAE network based on relevant historical key performance indicator (KPI) data is proposed. Since there are three KPIs related to accessibility, each representing different segments, a method to map these three KPI values onto the status of accessibility performance is proposed. The network conditions are categorized as high, acceptable or low for each time interval of observation. The first state shows that the system is running optimally, while the second state shows that the system has deteriorated and needs full attention, and the third state indicates that the system has gone into degraded conditions that cannot be tolerated. After the state sequence has been obtained, a transition probability matrix can be derived, which can be used to predict future conditions using a DTMC model. The results obtained are system predictions in terms of probability values for each state for a specific future time. These prediction values are required for proactive health monitoring and fault management. Accessibility degradation prediction is then conducted by using measurement data derived from an eNodeB in the LTE network for a period of one month.
Modeling of Decision-making Processes to Ensure Sustainable Operation of Multiservice Communication Network Alevtina Aleksandrovna Muradova
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.4

Abstract

This paper shows the modeling of decision-making processes to ensure stable operation of multiservice communication networks (MCNs) using the mathematical apparatus of fuzzy logic models. A classification of the main factors affecting the stability of an MCN is given. The main factors affecting the structural stability of MCNs are external factors, internal factors, energy factors, and maintenance factors. A decision-making strategy (DM) was chosen. The main factors that affect the stability of the functioning of an MCN are characterized by heterogeneity. Therefore, the task of the DM to ensure stability of the functioning of the MCN was reduced to producing a sequential solution of the following interrelated tasks: identification of the MCN by a systematic analysis of the main factors affecting the stability of the MCN, ranking the states of the MCN, and definition of the decision-making criteria. The first point is implemented by setting up a complex model of the MCN based on integration of the principles of fuzzy set theory (FST). A promising method for choosing a rational alternative is the method of non-dominated alternatives (MNDA), based on the aggregation of fuzzy information to characterize the relationship between the alternatives according to certain criteria.
Automated Defect Detection and Characterization on Pulse Thermography Images Using Computer Vision Techniques Meghana V; Megha P. Arakeri; Sharath D; M. Menaka; B. Venkatraman
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.5

Abstract

Defect detection and characterization plays a vital role in predicting the life span of materials. Defect detection using appropriate inspection technologies at various phases has gained huge importance in metal production lines. It can be accomplished through wise application of non-destructive testing and evaluation (NDE). It is important to characterize defects at an early stage in order to be able to overcome them or take corrective measures. Pulse thermography is a modern NDE method that can be used for defect detection in metal objects. Only a limited amount of work has been done on automated detection and characterization of defects due to thermal diffusion. This paper proposes a system for automatic defect detection and characterization in metal objects using pulse thermography images as well as various image processing algorithms and mathematical tools. An experiment was carried out using a sequence of 250 pulse thermography images of an AISI 316 L stainless steel sheet with synthetic defects. The proposed system was able to detect and characterize defects sized 10 mm, 8 mm, 6 mm, 4 mm and 2 mm with an average accuracy of 96%, 95%, 84%, 77%, 54% respectively. The proposed technique helps in the effective and efficient characterization of defects in metal objects.
Real-Life Optimum Shift Scheduling Design Lee Kong Weng; Sze San Nah
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.2

Abstract

In many industries, manpower shift scheduling poses problems that require immediate solutions. The fundamental need in this domain is to ensure that all shifts are assigned to cover all or as many jobs as possible. The shifts should additionally be planned with minimum manpower utilization, minimum manpower idleness and enhanced adaptability of employee schedules. The approach used in this study was to utilize an existing manpower prediction method to decide the minimum manpower required to complete all jobs. Based on the minimum manpower number and shift criteria, the shifts were assigned to form schedules using random pick and criteria-based selection methods. The potential schedules were then optimized and the best ones selected. Based on several realistic test instances, the proposed heuristic approach appears to offer promising solutions for shift scheduling as it improves shift idle time, complies with better shift starting time and significantly reduces the manpower needed and the time spent on creating schedules, regardless of data size.
Individual Expert Selection and Ranking of Scientific Articles Using Document Length Fadly Akbar Saputra; Taufik Djatna; Laksana Tri Handoko
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.3

Abstract

Individual expert selection and ranking is a challenging research topic that has received a lot attention in recent years because of its importance related to referencing experts in particular domains and research fund allocation and management. In this work, scientific articles were used as the most common source for ranking expertise in particular domains. Previous studies only considered title and abstract content using language modeling. This study used the whole content of scientific documents obtained from Aminer citation data. The modified weighted language model (MWLM) is proposed that combines document length and number of citations as prior document probability to improve precision. Also, the author's dominance in a single document is computed using the Learning-to-Rank (L2R) method. The evaluation results using p@n, MAP, MRR, r-prec, and bpref showed a precision enhancement. MWLM improved the weighted language model (WLM) by p@n (4%), MAP (22.5%), and bpref (1.7%). MWLM also improved the precision of a model that used author dominance by MAP (4.3%), r-prec (8.2%), and bpref (2.1%).
Trust-based Selfish Node Detection Mechanism using Beta Distribution in Wireless Sensor Network Kanchana Devi V; Ganesan R
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.1.6

Abstract

Wireless sensor networks (WSNs) are placed in open environments for the collection of data and are vulnerable to external and internal attacks. The cryptographic mechanisms implemented so far, such as authorization and authentication, are used to restrict external sensor node attacks but cannot prevent internal node attacks. In order to evade internal attacks trust mechanisms are used. In trust mechanisms, firstly, the sensor nodes are monitored using the popular Watchdog mechanism. However, traditional trust models do not pay much attention to selective forwarding and consecutive packet dropping. Sometimes, sensitive data are dropped by internal attackers. This problem is addressed in our proposed model by detecting selective forwarding and consecutive failure of sending packets using the Beta probability density function model.
Cover JICTRA Vol. 13 No. 1, 2019 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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