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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

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%.

Klasterisasi udang berdasarkan ukuran berbasis pemrosesan citra digital menggunakan metode CCA dan DBSCAN Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.2.2020.106-112

The quality of farmed shrimps has several criteria, one of which is shrimp size. The shrimp selection was carried out by the contractor at the harvest time by grouping the shrimp based on their size. This study aims to apply digital image processing for shrimp clustering based on size using the connected component analysis (CCA) and density-based spatial clustering of applications with noise (DBSCAN) methods. Shrimp group images were taken with a digital camera at a light intensity of 1200-3200 lux. The clustering results were compared with clustering from direct observation by two experts, each of which obtained an accuracy of 79.81 % and 72.99 % so that the average accuracy of the method was 76.4 %.

Implementation of Web Scraping to Build a Web-Based Instagram Account Data Downloader Application Arif Himawan; Adri Priadana; Aris Murdiyanto
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09201

Instagram has been used by many groups, such as business people, academics, to politicians, to take advantage of the insights gained by processing and analyzing Instagram data for various purposes. However, before processing and analyzing data, users must first pass data collection or downloading from Instagram. The problem faced is that most data collection methods are still done manually as for many parties that offer Instagram account data download services with various price options. This research applied a web scraping method to automatically build a web-based Instagram account data download application so that several parties can use it. The web scraping method was chosen because by using this method, researchers do not need to use Instagram's Application Programming Interface (API), which has access restrictions in retrieving data on Instagram. In this study, application testing was conducted on 15 Instagram accounts with various publications, namely between 100 and 11000. Based on the download data analysis results, the application of the web scraping method to download Instagram account data can successfully download a maximum of 2412 account data. In this application, users can download Instagram account data to Data Collection and then manage it like deleting and exporting data collection in the form of CSV, Excel, or JSON.

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

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

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

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.

Metode Accumulative Difference Images untuk Mendeteksi Berhentinya Putaran Kincir Air Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 2 (2021): Mei 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Vannamei shrimp is one of Indonesia's fishery commodities with great potential to be developed. One of the essential things in shrimp farming is a source of dissolved oxygen (DO) or a sufficient amount of oxygen content, which can be maintained by placing a waterwheel driven by a generator set engine called a generator. To keep the waterwheel running, the cultivators must continue to monitor it in real-time. Based on these problems, we need a method that can be used to detect the cessation of waterwheel rotation in shrimp ponds that focuses on the rotation of the waterwheel. This study aims to analyze the performance of the Accumulative Difference Images (ADI) method to detect the stopped waterwheel-spinning. This method was chosen because compared with the method that only compares the differences between two frames in each process, the ADI method is considered to reduce the error-rate. After all, it is taken from the results of the value of several frames' accumulated movement. The ADI method's application to detect the stopped waterwheel-spinning gives an accuracy of 95.68%. It shows that the ADI method can be applied to detect waterwheels' stop in shrimp ponds with a very good accuracy value.

Metode SURF dan FLANN untuk Identifikasi Nominal Uang Kertas Rupiah Tahun Emisi 2016 pada Variasi Rotasi Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

In December 2016, Bank Indonesia (BI) officially launched the 2016 Year Emission Rupiah. With the development of technology, the process of buying and selling are not only possible between humans and humans, but humans with a machine. In addition, the machine must also be able to read and recognize the nominal banknotes in various variations of face and rotation. This is because humans can put money in machines with various variations of face and rotation. This study aims to apply and analyze the level of accuracy of nominal rupiah banknotes identification with the SURF and FLANN methods for rotation variation. Testing for identification of nominal rupiah banknotes is carried out with different rotation variations, namely 0o, 90o, 180o, and 270o. The proposed identification method provides 100% of accuracy.

Instagram Hashtag Trend Monitoring Using Web Scraping Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Pekommas Vol 5, No 1 (2020): April 2020
Publisher : BBPSDMP KOMINFO MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2020.2050103

In recent years, Instagram has become one of the fastest growing social media platforms. Searching images on Instagram can be done by using a particular keyword or often known as the hashtag. The hashtag is one of the parameters that can use to find out the topics that are being talked about on social media. There are many advantages for knowing a hot topic on social media to support decision making. This study aims to monitor trends of hashtags on the Instagram platform using web scraping techniques. This research has succeeded in extracting and analyzing post data on Instagram to provide trend information from a #MerryChrismas hashtag. The results of this study are the visible trend in the #MerryChrismas hashtag experienced an increase in the last two days, namely on 24 and 25 December 2019. In addition, this research also succeeded in displaying posts with the most number of likes and comments from a hashtag at a certain time period.

Analisis Waktu Terbaik untuk Menerbitkan Konten di Instagram untuk Menjangkau Audiens Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Penelitian Pers dan Komunikasi Pembangunan Vol 24 No 1 (2020): Jurnal Penelitian Pers dan Komunikasi Pembangunan
Publisher : Balai Pengembangan SDM dan Penelitian Komunikasi dan Informatika (BPSDMP Kominfo) Banjarmasin

Instagram is a social media that allows us to easily promote products where one of them is done by publishing promotional content. However, posting promotional material at the right time to get an optimal response from the audience is a complex problem. This study aims to analyze the best publishing time to publish promotional content from 10 open trip service provider accounts on the Instagram platform. Researchers use the web scraping method to extract data from Instagram accounts and the aggregation, ordering, and selecting methods to analyze the best time. The basis used to determine the best time is the number of likes and comments on all posts. This research has succeeded in extracting Instagram's web data and analyzing post data from several Instagram accounts of open trip service providers. The results of this study indicate that each account has a different best time to publish content. For example, the best time to post content from an Instagram @hvtrip account is Friday between 20:00 and 20.59. The study can be used as a recommendation for Instagram account holders of open trip service providers regarding the best time to publish promotional content on Instagram to reach an optimal audience. Of course, this is not limited to Instagram accounts open service providers only. Keywords: social media analytics, Instagram data, marketing, open trip services, the best time ABSTRAK Instagram merupakan salah satu media sosial yang memungkinkan kita untuk mempromosikan produk dengan mudah dimana salah satunya dilakukan dengan cara menerbitkan konten promosi. Akan tetapi, penerbitan konten prosmosi pada waktu yang tepat untuk mendapatkan tanggapan dari audiens secara optimal merupakan masalah yang kompleks. Penelitian ini bertujuan menganalisis waktu penerbitan terbaik untuk menerbitkan konten promosi dari 10 akun penyedia jasa open trip pada platform Instagram. Peneliti menggunakan metode web scraping untuk mengekstrak data dari akun Instagram dan metode aggregation, ordering, dan selecting untuk menganalisis waktu terbaik. Dasar yang digunakan untuk menentukan waktu terbaik adalah jumlah suka dan komentar pada semua post. Penelitian ini telah berhasil mengekstraksi data web Instagram dan melakukan analisis data post dari beberapa akun Instagram penyedia jasa open trip. Hasil penelitian ini menunjukkan bahwa setiap akun memiliki waktu terbaik yang berbeda-beda untuk menerbitkan konten. Sebagai contoh, waktu terbaik untuk menerbitkan konten dari akun Instagram @hvtrip adalah hari Jumat antara jam 20.00 sampai jam 20.59. Hasil dari penelitian ini dapat dijadikan sebagai sebuah rekomendasi bagi pemilik akun Instagram penyedia jasa open trip mengenai waktu terbaik untuk menerbitkan konten promosi pada Instagram untuk menjangkau audiens secara optimal. Tentunya, hal ini tidak terbatas pada akun Instagram penyedia jasa open trip saja. Kata kunci: analisis media sosial, data Instagram, pemasaran, jasa open trip, waktu terbaik

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