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All Journal Jurnal BALIRESO ILKOM Jurnal Ilmiah
Mukarramah, Rifqatul
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Agriculture, Biological Sciences & Forestry Computer Science & IT Education Public Health Social Sciences Other

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PEMBASIINDO (PEMBELAJARAN BAHASA ISYARAT INDONESIA) BESBASIS ANDROID DI SEKOLAH LUAR BIASA NEGERI 02 MAKASSAR Umar, Andi Achmad Zufadly; Satma, Satma; Mukarramah, Rifqatul; Agung, Riski Dewa; Amir, Nur Hikmah; Indra, Dolly; Hayati, Lilis Nur
Jurnal Balireso: Jurnal Pengabdian pada Masyarakat Vol 4, No 2 (2019)
Publisher : Jurnal Balireso: Jurnal Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (161.931 KB) | DOI: 10.33096/balireso.v4i2.124

Abstract

Many inhabitants of Indonesia, including individuals who have physical characteristics, thecharacters are different traits supplied by heredity and the formation of characteristics related tothe physical environment and social environment. Based on these factors, humans are classified asnormal people and those with special needs such as deaf. At Sekolah Luar Biasa Negeri 02Makassar the sign language learning process still considered less effective because of the limitedteaching team. In the PKM-M activities, it aims to introduce the features that provide in AndroidbasedPEMBASIINDO consisting of video tutorials. The benefit of this activity is the teachingteam can carry out an effective learning process and the program can be useful as a learning mediathat can be used by the deaf and the general society. The Implementation method of these activitiescarried out at SLBN starts from observation, design activities, coordination with partner related tothe activities, socialization, and training PEMBASIINDO application. The results of theseactivities are related to increasing knowledge about Indonesian sign language by PEMBASIINDOapplication media, helping teachers to the learning process and students with hearing impairmentto communicating with their friends and the environment related to support the learning process.
Performance comparison of support vector machine (SVM) with linear kernel and polynomial kernel for multiclass sentiment analysis on twitter Mukarramah, Rifqatul; Atmajaya, Dedy; Ilmawan, Lutfi Budi
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.851.168-174

Abstract

Sentiment analysis is a technique to extract information of ones perception, called sentiment, on an issue or event. This study employs sentiment analysis to classify societys response on covid-19 virus posted at twitter into 4 polars, namely happy, sad, angry, and scared. Classification technique used is support vector machine (SVM) method which compares the classification performance figure of 2 linear kernel functions, linear and polynomial. There were 400 tweet data used where each sentiment class consists of 100 data. Using the testing method of k-fold cross validation, the result shows the accuracy value of linear kernel function is 0.28 for unigram feature and 0.36 for trigram feature. These figures are lower compared to accuracy value of kernel polynomial with 0.34 and 0.48 for unigram and trigram feature respectively. On the other hand, testing method of confusion matrix suggests the highest performance is obtained by using kernel polynomial with accuracy value of 0.51, precision of 0.43, recall of 0.45, and f-measure of 0.51.
Co-Authors Agung, Riski Dewa Amir, Nur Hikmah Atmajaya, Dedy Dolly Indra Fadly Achmad lilis nurhayati Lutfi Budi Ilmawan, Lutfi Budi Satma, Satma