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All Journal Jurnal Pekommas Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi dan Sistem Komputer Compiler Journal of Dedicators Community Jurnal Penelitian Pers dan Komunikasi Pembangunan JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Berdaya Mandiri Indonesian Journal of Data and Science Jurnal Abdimas Kartika Wijayakusuma PELS (Procedia of Engineering and Life Science) Indonesian Journal on Data Science Teknomatika: Jurnal Informatika dan Komputer International Journal of Artificial Intelligence in Medical Issues
Aris Wahyu Murdiyanto
Universitas Jenderal Achmad Yani Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Journal : Compiler

 1 
Decision Support System of Keyword Selection Web Site Using Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Murdiyanto, Aris Wahyu
Compiler Vol 8, No 1 (2019): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (657.729 KB) | DOI: 10.28989/compiler.v8i1.429

Abstract

The keyword is one or a group of words used by websites to improve your visibility on search engines. The selection of keywords from the results displayed by Google's keyword planner still not match the expectations of the webmaster, so that needs to be determined the choice and order of priority keywords which will be optimized beforehand. Therefore, a system that supports webmasters in making decisions on choosing keywords that will be optimized previously for search engines is needed. The methods used in this research is Analytical Hierarchy Process (AHP) to find the weighting parameters and Simple Additive Weighting (SAW) applied to find the final value and rank. The results showed that the system is running as expected, so it can be used as a basis in support of the decision of the webmaster in determining the priority of the optimization of keywords that will be worked out with the results of the comparison between the manual system with 100%. 
Analysis of Deep Learning Approach Based on Convolution Neural Network (CNN) for Classification of Web Page Title and Description Text Aris Wahyu Murdiyanto; Muhammad Habibi
Compiler Vol 11, No 2 (2022): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (794.192 KB) | DOI: 10.28989/compiler.v11i2.1327

Abstract

The volume of digital documents available online is growing exponentially due to the increasing use of the internet. Categorization of information obtained online is needed to make it easier for recipients of information to determine and filter which information is needed. Classification of web pages can be based on titles and descriptions, which are text data that can be done by utilizing deep learning technology for text classification. This study aimed to conduct data training and analysis experiments to determine the accuracy of the proposed deep learning architecture in classifying web page titles and descriptions. In this research, we proposed a Convolution Neural Network (CNN) architecture that generates few parameters. The training and evaluation set was conducted on the web page dataset provided by DMOZ. As a result, the proposed CNN architecture with the number of N (Dropout + 1D Convolution + ReLU activation) equal to 1 achieves the best validation accuracy. It achieves 79.51% with only generates 825,061 parameters. The proposed CNN architecture achieved outperformed performance on the accuracy of the five other technologies in the state-of-the-art.
Decision Support System of Keyword Selection Web Site Using Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Aris Wahyu Murdiyanto
Compiler Vol 8, No 1 (2019): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (657.729 KB) | DOI: 10.28989/compiler.v8i1.429

Abstract

The keyword is one or a group of words used by websites to improve your visibility on search engines. The selection of keywords from the results displayed by Google's keyword planner still not match the expectations of the webmaster, so that needs to be determined the choice and order of priority keywords which will be optimized beforehand. Therefore, a system that supports webmasters in making decisions on choosing keywords that will be optimized previously for search engines is needed. The methods used in this research is Analytical Hierarchy Process (AHP) to find the weighting parameters and Simple Additive Weighting (SAW) applied to find the final value and rank. The results showed that the system is running as expected, so it can be used as a basis in support of the decision of the webmaster in determining the priority of the optimization of keywords that will be worked out with the results of the comparison between the manual system with 100%. 
Analysis of web scraping techniques to get keywords suggestion and allintitle automatically from Google Search Engines Aris Wahyu Murdiyanto; Aris Wahyu Murdiyanto; Adri Priadana
Compiler Vol 10, No 2 (2021): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (613.619 KB) | DOI: 10.28989/compiler.v10i2.1064

Abstract

Keyword research is one of the essential activities in Search Engine Optimization (SEO). One of the techniques in doing keyword research is to find out how many articles titles on a website indexed by the Google search engine contain a particular keyword or so-called "allintitle". Moreover, search engines are also able to provide keywords suggestion. Getting keywords suggestions and allintitle will not be effective, efficient, and economical if done manually for relatively extensive keyword research. It will take a long time to decide whether a keyword is needed to be optimized. Based on these problems, this study aimed to analyze the implementation of the web scraping technique to get relevant keyword suggestions from the Google search engine and the number of "allintitle" that are owned automatically. The data used as an experiment in this test consists of ten keywords, which each keyword would generate a maximum of ten keywords suggestion. Therefore, from ten keywords, it will produce at most 100 keywords suggestions and the number of allintitles. Based on the evaluation result, we got an accuracy of 100%. It indicated that the technique could be applied to get keywords suggestions and allintitle from Google search engines with outstanding accuracy values.
Co-Authors -, Purnawan Adri Priadana Adri Priadana Agung Purwanto Soedarbe Agung Satria Panca Ahmad Adita Shiddiq Ahmad Adita Shiddiq Ahmad Hanafi Ahmad Hanafi Alfun Roehatul Jannah Alfun Roehatul Jannah Almayanti Susillia Ningrum Alwiah, Izmy Angkotasan, Muhamad Arabi Rizki Arbintarso, Ellyawan Setyo Arif Himawan Arif Himawan Arif Himawan, Arif Aulia Puji Rahayu Bara Falah Adikaputra Catur Iswahyudi David Sulistiyantoro David Sulistiyantoro, David Sulistiyantoro Dewi, Tika Sari Dian Hafidh Zulfikar Dimas Pratama Jati Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Fitriatul Hasanah Gerlan Haha Nusa Gilang Argya Dyaksa Haha Nusa, Gerlan Hamada Zein Hariyanto, Satriawan Dini Ida Ristiana Iqbal Hadi Subekti Iqbal Hadi Subekti Kadir Parewe, Andi Maulidinnawati Abdul Kharisma Kharisma Kusumaningtyas, Kartikadyota Latipah, Asslia Johar M. Abu Amar Al Badawi Marausna, Gaguk Muhammad Habibi Muhammad Habibi Muhammad Luqman Bukhori Muhammad Rifqi Ma'arif Mukasi Wahyu Kurniawati Nafisa Alfi Sa'diya Naswin, Ahmad Nufia Alfi Rohyana Nufia Alfi Rohyana Nurcahyo, Raden Wisnu Nurul Fatimah Poetro, Bagus Satrio Waluyo Prasetiyo, Erwan Eko Puji Astuti, Nur Rochmah Dyah Purbobinuko, Zakharias Kurnia Purnawan Purnawan Putra, Fajri Profesio Putra, Ikbal Rizki Raden Wisnu Nurcahyo Risky Setyadi Putra Rosid, Ibnu Abdul Rudi Setiawan Samuel Kristiyana Septiyati Purwandari Siregar, Alda Cendekia Sisilia Endah Lestari, Sisilia Endah Sugeng Santoso Sumiyatun Suparni Setyowati Rahayu Surya Rizki Syahruddin, Fajar Tarigan, Thomas Edyson Umar Zaky Yulianto Prabowo, Fajar Zennul Mubarrok, Zennul Mubarrok