A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems

Data mining concepts and methods can be applied in various fields. Many methods have been proposed and one of those methods is the classical 'rough set theory' which is used to analyze the complete data. However, the Rough Set classical theory cannot overcome the incomplete data. The simplest method for operating an incomplete data is removing unknown objects. Besides, the continuation of Rough Set theory is called tolerance relation which is less convincing decision in terms of approximation. As a result, a similarity relation is proposed to improve the results obtained through a tolerance relation technique. However, when applying the similarity relation, little information will be lost. Therefore, a limited tolerance relation has been introduced. However, little information will also be lost as limited tolerance relation does not take into account the accuracy of the similarity between the two objects. Hence, this study proposed a new method called Relative Tolerance Relation of Rough Set with Reduct and Core (RTRS) which is based on limited tolerance relation that takes into account relative similarity precision between two objects. Several incomplete datasets have been used for data classification and comparison of our approach with existing baseline approaches, such as the Tolerance Relation, Limited Tolerance Relation, and NonSymmetric Similarity Relations approaches are made based on two different scenarios. In the first scenario, the datasets are given the same weighting for all attributes. In the second scenario, each attribute is given a different weighting. Once the classification process is complete, the proposed approach will eliminate redundant attributes to develop an efficient reduce set and formulate the basic attribute specified in the incomplete information system. Several datasets have been tested and the rules generated from the proposes approach give better accuracy. Generally, the findings show that the RTRS method is better compared to the other methods as discussed in this study

Design of Cooling and Air Flow System Using NDLC Method Based on TIA-942 Standards in Data Center at CV Media Smart Semarang

CV Media Smart is a company that involved in the procurement of IT tools in schools and offices. With wide range coverage of schools and companies, CV Media Smart want to add more business process, therefore data center is needed to support existing and added later business process. The focus of this research is on cooling system and air flow. To support this research, NDLC (Network Development Life Cycle) is used as research method. NDLC is a method that depend on development process, like design of business process and infrastructure design. The reason why this research is using NDLC method is because NDLC is method that depend on development process. The standard that used in this research is TIA-942. Result of this research is a design of data center that already meet TIA-942 standard tier 1

Path apps for box of ramadhan

Map helps to track targeted location but still unable to find actual destination of rural area due to unclear addresses. This problem also faced by owner and members of the Box of Ramadhan when they need to give delivery services to underprivileged people cause low efficiency of service provided. Thus, this project is conducted to design and develop an application called Path Apps for Box of Ramadhan for Android device user to solve problems of reach destination and get related information to reduce overall time spending. Unified Modelling Language diagram used to show the relationship and interaction among all classes. The proposed system is categories into two different interfaces as admin interface and user interface. The application consists of few modules such as login and registration, user list, profile, current location, route, multiple markers and address list and chat modules. Time management, route planning and inventory will be under control by user according to program schedule. This contribute to high efficiency of work

PERANCANGAN DESAIN MONITORING JARINGAN KOMPUTER UNTUK EASY MAINTENANCE DI TELKOM UNIVERSITY LANDMARK TOWER

Infrastruktur jaringan pada gedung Telkom University Landmark Tower (TULT) yang saat ini dikelola oleh Direktorat Pusat Teknologi Informasi (PuTI) masih memiliki beberapa kendala diantaranya, gedung tersebut memiliki keterbatasan Sumber Daya Manusia (SDM), dalam hal penanganan troubleshooting jaringan. Adapun masalah lainnya yaitu kurangnya transparansi informasi dalam menangani masalah terhadap jaringan, karena saat ini infrastruktur jaringan tersebut memiliki aplikasi monitoring yang belum maksimal untuk troubleshooting jaringan. Dengan adanya permasalahan tersebut di dalam penelitian ini digunakan metodologi Network Development Life Cycle (NDLC) sebagai tahapan untuk melakukan penyelesaian masalah. Urutan tahapan dari metodologi NDLC ini di antaranya yaitu tahap analisis, tahap desain, dan tahap simulasi prototyping. Berdasarkan hasil penelitian yang telah dilaksanakan, maka dapat diketahui bahwa pada saat ini pihak PuTI memiliki SOP (Standard Operating Procedure) dalam melakukan pemantauan jaringan pada perangkat yang sedang mengalami down, dan juga sudah menerapkan Network Monitoring System (NMS) untuk melakukan pemantauan jaringan di Universitas Telkom. Tetapi SOP dan NMS yang dijalankan oleh PuTI saat ini kurang maksimal dalam hal easy maintenance di gedung TULT. Oleh karena itu, maka di dalam penelitian ini menghasilkan rekomendasi mengenai SOP pada monitoring jaringan di gedung TULT, dan juga dashboard monitoring khusus pada Fakultas Rekayasa Industri untuk lantai 4, 8, 9, dan 18 di gedung TULT. Rekomendasi tersebut dibuat untuk easy maintenance dalam hal monitoring, controlling, dan handling di gedung TULT

ANALYSIS OF WIRELESS AND CABLE NETWORK QUALITY-OF-SERVICE PERFORMANCE AT TELKOM UNIVERSITY LANDMARK TOWER USING NETWORK DEVELOPMENT LIFE CYCLE (NDLC) METHOD

There are some infrastructure problems in the Telkom University Landmark Tower building, which still lacks human resources to help troubleshoot the network when an interference happens. The second problem is that the TULT has a closed concept building, which will be an issue for the network stability. The last problem is the lack of information transparency when handling a network problem. In this research, the author uses the NDLC (Network Development Life Cycle) method as a step to solve the problem. The sequence of the NDLC methodology starts from the initial stage, the analysis stage, the design stage, the prototype simulation stage, and the final stage. Based on the analysis of the current wireless and wired network condition, it can be concluded that it is still in good condition, which only requires good and scheduled maintenance to prevent the internet connection from going down. The current wireless and wired connections are tested during peak and free times by adjusting the lecture conditions with the Hybrid Blended Learning (HBL) learning model, where not too many people use the internet connection from TULT building. Tests on wireless and cable networks during peak and off-peak hours revealed results for the 4th, 8th, 9th, and 18th floors with a very good delay index, a very good throughput index, and a very good packet loss index on all floors. All wireless and wired network test results have a very good index categor

A review on missing tags detection approaches in RFID system

Radio Frequency Identification (RFID) system can provides automatic detection on very large number of tagged objects within short time. With this advantage, it is been using in many areas especially in the supply chain management, manufacturing and many others. It has the ability to track individual object all away from the manufacturing factory until it reach the retailer store. However, due to its nature that depends on radio signal to do the detection, reading on tagged objects can be missing due to the signal lost. The signal lost can be caused by weak signal, interference and unknown source. Missing tag detection in RFID system is truly significant problem, because it makes system reporting becoming useless, due to the misleading information generated from the inaccurate readings. The missing detection also can invoke fake alarm on theft, or object left undetected and unattended for some period. This paper provides review regarding this issue and compares some of the proposed approaches including Window Sub-range Transition Detection (WSTD), Efficient Missing-Tag Detection Protocol (EMD) and Multi-hashing based Missing Tag Identification (MMTI) protocol. Based on the reviews it will give insight on the current challenges and open up for a new solution in solving the problem of missing tag detection

Comparison between ANN and Multiple Linear Regression Models for Prediction of Warranty Cost

Nowadays, warranty has its own priority in business strategy for a manufacturer to protect their benefit as well as the intense competition between the manufacturers. In fact, warranty is a contract between manufacturer and buyer in which the manufacturer gives the buyer certain assurances as the condition of the property being sold. In industry, an accurate prediction of warranty costs is often counted by the manufacturer. Underestimation or overestimation of the warranty cost may have a high influence to the manufacturers. This paper presents a methodology to adapt historical maintenance warranty data with comparison between Artificial Neural Network (ANN) and multiple linear regression approach

A Comparative Analysis of Rough Sets for Incomplete Information System in Student Dataset

Rough set theory is a mathematical model for dealing with the vague, imprecise, and uncertain knowledge that has been successfully used to handle incomplete information system. Since we know that in fact, in the real-world problems, it is regular to find conditions where the user is not able to provide all the necessary preference values. In this paper, we compare the performance accuracy of the extension of rough set theory, i.e. Tolerance Relation, Limited Tolerance Relation, Non-Symmetric Similarity Relation and New Limited Tolerance Relation of Rough Sets for handling incomplete information system in real-world student dataset. Based on the results, it is shown that New Limited Tolerance Relation of Rough Sets has outperformed the previous techniques.

Phylogenetic Study of Presumptive Oil-degrading Microbes Isolated from The North-western Tip of Pahang

Many construction areas are often contaminated with petroleum compounds. The aim of this work were to isolate and characterize indigenous bacteria isolated at a moderate temperature site as well as to study the pattern of phylogenetic tree among bacterial communities associated with oil degradation. No profound studies have yet been done in the construction site at Tanah Rata. Hence, this research was carried out to find existing status of microbial community from a few selected spots. Enrichment culture technique by using MSM broth has been used to isolate the desired microorganisms. Isolation and characterization tests using phenotypic and genotypic approaches (based on genes encoding 16S rRNA) had led to the discovery of 18 isolates. The 16S rRNA was used due to its functional constant, universally distributed and moderately well discovered across broad phylogenetic distances. The successfully identified genera were Pseudomonas, Bacillus, Exiguobacterium, Stenotrophomonas, Acinetobacter, Serratia and Gamma Proteobacterium

Analysis of Attribute Selection and Classification Algorithm Applied to Hepatitis Patients

Data mining techniques are widely used in classification, attribute selection and prediction in the field of bioinformatics because it helps to discover meaningful new correlations, patterns and trends by sifting through large volume of data, using pattern recognition technologies as well as statistical and mathematical techniques. Hepatitis is one of the most important health problem in the world. Many studies have been performed in the diagnosis of hepatitis disease but medical diagnosis is quite difficult and visual task which is mostly done by doctors. Therefore, this research is conducted to analyse the attribute selection and classification algorithm that applied to hepatitis patients. In order to achieve goals, WEKA tool is used to conduct the experiment with different attribute selector and classification algorithm . Hepatitis dataset that are used is taken from UC Irvine repository. This research deals with various attribute selector namely CfsSubsetEval, WrapperSubsetEval, GainRatioSubsetEval and CorrelationAttributeEval. The classification algorithm that used in this research are NaiveBayesUpdatable, SMO, KStar, RandomTree and SimpleLogistic. The results of the classification model are time and accuracy. Finally, it concludes that the best attribute selector is CfsSubsetEval while the best classifier is given to SMO because SMO performance is better than other classification techniques for hepatitis patients