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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Seminar Nasional Teknologi Informasi Komunikasi dan Industri
Mustafa Mat Deris
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

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Performance Analysis of Partitional and Incremental Clustering Zuriana Abu Bakar; Mustafa Mat Deris; Arifah Che Alhadi
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2005
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

The partitional and incremental clustering are the common models in mining data in large databases.However, some models are better than the others due to the types of data, time complexity, and spacerequirement. This paper describes the performance of partitional and incremental models based on the numberof clusters and threshold values. Experimental studies shows that partitional clustering outperformed when thenumber of cluster increased, while the incremental clustering outperformed when the threshold value decreased.Keywords: Clustering, partitional, incremental, distance.
INDONESIAN-MALAYSIAN STOCK MARKET MODELS USING FUZZY RANDOM TIME SERIES Riswan Efendi; Nureize Arbaiy; Mustafa Mat Deris
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2017: SNTIKI 9
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Various fuzzy and non-fuzzy models have been presented to forecast the stock market with multiple inputs data or variables. In other words, some of the researchers have overlooked the key success in financial time series forecasting which is minimizing number of inputs. Moreover, most of the existing time series models have been focused on data consisting of single values, or fuzzy numbers without randomness into consideration. In real situations, there exists a genuine need to cope with data that involves the factors of fuzziness and probability. To address the drawbacks, we propose an enhanced fuzzy random auto-regression model for better stock market forecasting using the low-high procedure. This procedure is able to represent the daily prices variations in stocks. The daily stock markets of Indonesia-Malaysia are used as numerical examples and efficiency of the proposed procedure is compared with baselines models.
Co-Authors Arifah Che Alhadi Nureize Arbaiy Riswan Efendi Zuriana Abu Bakar