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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Algoritma Jurnal Edukasi dan Penelitian Informatika (JEPIN) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jiko (Jurnal Informatika dan komputer) Jurnal Perspektif Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) JISA (Jurnal Informatika dan Sains) Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Science, Engineering, Technology, and Education Journal of Applied Data Sciences Jurnal Algoritma Gunung Djati Conference Series Intellect : Indonesian Journal of Learning and Technological Innovation Jurnal Informatika Polinema (JIP) Khazanah Pendidikan Islam International Journal of Islamic Khazanah Khazanah Journal of Religion and Technology
Maylawati, Dian Sa'adillah
Department Of Informatics, UIN Sunan Gunung Djati Bandung
Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Weighted inverse document frequency and vector space model for hadith search engine Septya Egho Pratama; Wahyudin Darmalaksana; Dian Sa'adillah Maylawati; Hamdan Sugilar; Teddy Mantoro; Muhammad Ali Ramdhani
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp1004-1014

Abstract

Hadith is the second source of Islamic law after Qur’an which make many types and references of hadith need to be studied. However, there are not many Muslims know about it and many even have difficulties in studying hadiths. This study aims to build a hadith search engine from reliable source by utilizing Information Retrieval techniques. The structured representation of the text that used is Bag of Word (1-term) with the Weighted Inverse Document Frequency (WIDF) method to calculate the frequency of occurrence of each term before being converted in vector form with the Vector Space Model (VSM). Based on the experiment results using 380 texts of hadith, the recall value of WIDF and VSM is 96%, while precision value is just around 35.46%. This is because the structured representation for text that used is bag of words (1-gram) that can not maintain the meaning of text well).
Flexibility of Indonesian text pre-processing library Dian Sa'adillah Maylawati; Hilmi Aulawi; Muhammad Ali Ramdhani
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp420-426

Abstract

This study aimed to achieve and measure flexibility as a software quality factor of text pre-processing libraries with Indonesian text from social media. Library was built based on a review of some text mining applications that did not yet have a special pre-process for Indonesian text. Text pre-processing libraries were designed and built using an object-oriented approach that was modular to achieve flexibility. Flexibility was measured by the Mc Call Cyclomatic Complexity (CC) metric. Flexibility of library was tested by implementing the library into text mining applications. The results of experiment showed that text pre-processing libraries could be flexible and easy to use without much configuration in text mining applications. It was proved by the value of CC of 2.51 which meant the library or software was not too complex, simple enough, and also flexible to use.
Indonesian news classification using convolutional neural network Muhammad Ali Ramdhani; Dian Sa’adillah Maylawati; Teddy Mantoro
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1000-1009

Abstract

Every language has unique characteristics, structures, and grammar. Thus, different styles will have different processes and result in processed in natural language processing (NLP) research area. In the current NLP research area, data mining (DM) or machine learning (ML) technique is popular, especially for deep learning (DL) method. This research aims to classify text data in the Indonesian language using convolutional neural network (CNN) as one of the DL algorithms. The CNN algorithm used modified following the Indonesian language characteristics. Thereby, in the text pre-processing phase, stopword removal and stemming are particularly suitable for the Indonesian language. The experiment conducted using 472 Indonesian news text data from various sources with four categories: ‘hiburan’ (entertainment), ‘olahraga’ (sport), ‘tajuk utama’ (headline news), and ‘teknologi’ (technology). Based on the experiment and evaluation using 377 training data and 95 testing data, producing five models with ten epoch for each model, CNN has the best percentage of accuracy around 90,74% and loss value around 29,05% for 300 hidden layers in classifying the Indonesian News data.
Model-view-controller approach for e-Zakah Ah. Fathonih; Dian Sa’adillah Maylawati; Muhammad Ali Ramdhani
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp1054-1065

Abstract

Zakah (alms) has a strategic position in terms of Islamic value and terms of the development of the welfare of the people. In the current digital era, the use of technology can facilitate zakah worship more easily, quickly, efficiently, and secure. This study aims to analyze and design electronic zakah (e-Zakah) structurally and systematically using the Model-View-Controller (MVC) approach. MVC is an approach or pattern of object-oriented analysis and design for software development that widely used today. MVC is implemented in the analysis and design modelling using Unified Modeling Language (UML) for e-Zakah. Based on the traceability result of analysis and design of e-Zakah, it can be concluded that the e-Zakah analysis and design model has been met all of zakah concept, user and software requirements, and all of models can be traced to each other. Therefore, e-Zakah analysis and design model in this study is ready to be built as a software.
Analisis Perbandingan Algoritma FP-Growth dan CP-Tree untuk Data Teks Dian Sa’adillah Maylawati
Jurnal Algoritma Vol 15 No 1 (2018): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (845.353 KB) | DOI: 10.33364/algoritma/v.15-1.1

Abstract

Frequent Pattern Growth (FP-Growth) dan Compact Pattern Tree (CP-Tree) adalah algoritma Frequent Itemset Mining (FIM) yang menghasilkan frequent itemset dari transaksi database. Frequent itemset dapat digunakan sebagai representasi terstruktur untuk data teks yang merupakan data tidak terstruktur atau semi terstruktur. CP-Tree adalah algoritma FIM yang dikembangkan dari algoritma FP-Growth. Namun, CP-Tree melakukan proses data secara inkremental sedangkan FP-Growth non-inkremental. Artikel ini membahas analisis terhadap algoritma FP-Growth dan CP-Tree dalam menghasilkan representasi terstruktur dari data teks. Berdasarkan hasil analisis dan evaluasi terhadap algoritma FP-Growth CP-Tree diperoleh bahwa frequent itemset yang dihasilkan dari representasi pohon kedua algoritma tersebut sama. Secara proses algoritma FP-Growth lebih sederhana dibandingkan algoritma CP-Tree. Namun, algoritma CP-Tree lebih fleksibel terhadap penambahan transaksi baru dibandingkan algoritma FP-Growth. Hal ini dikarenakan CP-Tree tidak mengulang dari awal untuk proses scanning data dan membuat struktur pohon seperti FP-Growth apabila ada data transaksi baru.
Penerapan Algoritma Association Rule Pada Sistem Rekomendasi Untuk Menunjang Pemasaran Hasil Pertanian Rizkiansyah Dewantara; Dian Sa’adillah Maylawati; Rinda Cahyana
Jurnal Algoritma Vol 17 No 1 (2020): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.861 KB) | DOI: 10.33364/algoritma/v.17-1.147

Abstract

Sektor pertanian memegang peranan penting dalam kehidupan manusia dikarenakan sektor pertanian termasuk bagian integral pada sistem pembangunan nasional oleh sebab itu sektor pertanian berperan penting dalam kelangsungan hidup dikarenakan sektor pertanian rermasuk bagian integral dari kesatuan pembangunan dalam negri. Saat ini teknologi informasi yang digunakan untuk memasarkan produk telah menerapkan algoritma untuk merekomendasikan pilihan konten produk berdasarkan pilihan konten sebelumnya maka dari itu harus ada sistem menerapkan algoritma Association Rule pada sistem rekomendasi menggunakan data-set pertanian. Manfaat dari penerapan algoritma Association Rule dalam sistem rekomendasi akan memudahkan penyedia produk pertanian, petani maupun masyarakat dalam pemasaran produk hasil pertanian dan menjadi nilai tambah untuk kesejahteraan. Perancangan sistem ini menggunakan Rational Unified Process sebagai metodologinya yang terdiri dari tahapan inception, elaboration dan contruction, dan0Unified Modelling0Language0yaitu memakai use0case0diagram,0activity0diagram,0sequence0diagram dan class0diagram sebagai pemodelannya. penelitian ini menghasilkan sebuah sistem prototype dimana sistem rekomendasi menggunakan algoritma Association Rule yang dapat digunakan untuk teknologi e-commerce. Sistem rekomendasi yang meggunakan penerapan ini nantinya dapat menjadi suatu fitur atau pengembangan dari aplikasi atau sistem penjualan khususnya untuk pengelolaan admin dalam menentukan suatu rekomendasi produk penjualan berdasarkan itemset transaksi yang terjadi agar dapat merekomendasikan produk kepada pembeli.
Media Pembelajaran Rumah Adat Indonesia Berbasis Android Menggunakan Algoritma Fisher Yates Shuffle Marwah Maulana Sidik; Dian Sa'adillah Maylawati; Ridwan Setiawan
Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.273 KB) | DOI: 10.33364/algoritma/v.17-2.218

Abstract

Indonesia merupakan negara kepulauan yang memiliki berbagai suku bangsa, adat, maupun budaya, seiring dengan berjalannya waktu, dan adanya unsur-unsur budaya baru yang masuk ke Indonesia dapat menimbulkan perubahan yang sangat besar, sehingga minat dalam belajar mengenai budaya Indonesia sangatlah kurang, sedikit demi sedikit masyarak Indonesia melupakan budaya nya. Salah satu dari budaya tersebut yaitu rumah adat yang semakin ditinggalkan dan diganti dengan unsur-unsur moderen. media pembelajaran yang menarik dengan memanfaatkan teknologi sekarang yang salah satunya yaitu android, sebagai sarana untuk mempermudah dalam pemelajar. Penelitian ini bertujuan untuk membangun media pembelajaran berbasis android untuk mempermudah dalam pembelajaran mengenai rumah adat, agar dapat menarik minat belajar masyarakat Indonesia khususnya anak-anak yang dalam fase belajar. Aplikasi ini dibangun dengan menggunakan metodologi Multimedia Development Life Cycle versi Luther Sutopo dengan tahapan concept , design, material collecting, assembly, testing dan distribution. Selain itu, juga menggunakan algoritma Fisher Yates Shufle sebagai algoritma untuk pengacakan agar media pembelajaran lebih interaktif dan membantu dalam mengukur tingkat pemahaman pada peroses pembelajaran. Pengujian yang dilakukan menggunakan pengujian alpha test dan beta test dengan jenis pengujian black box dan white box. Adapun hasil dari aplikasi yang telah dievaluasi melalui kuesioner dengan jumlah 20 responden, aplikasi ini sangat membantu, mudah dipelajari dan dipahami, begitu pula perandoman yang dilakukan menggunakan Algoritma fisher yates shuffle depat berjalan dengan sangat baik, pada perhitungan pengujian setiap langkah-langkah dalam melakukan peroses pengacakan bernilai sama.
Comparison of Classification Algorithms for Sentiment Analysis on Movie Comments Dian Sa'adillah Maylawati; Melani Nur Mudyawati; Muhammad Humam Wahisyam; Riki Ahmad Maulana
Gunung Djati Conference Series Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The film industry is growing rapidly nowadays, various genres and storylines are nicely packaged to convey messages and entertain audiences. Sentiment analysis technology can be used for the advancement of the film industry as well as film recommendations that need to be presented next. This study aims to compare several algorithms used for sentiment analysis of movie reviews or comments. The algorithms used in this study are K-Nearest Neighbor (k-NN), Naïve Bayes Classifier (NBC), and Logistic Regression. The experimental results using 25,000 film comment datasets show that Logistic Regression has the highest accuracy rate with an accuracy of 89%, compared to Naïve Bayes' accuracy of 86%, while k-NN is 65.22%.
Feature-based approach and sequential pattern mining to enhance quality of Indonesian automatic text summarization Dian Sa'adillah Maylawati; Yogan Jaya Kumar; Fauziah Binti Kasmin
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1795-1804

Abstract

Indonesian automatic text summarization research is developed rapidly. The quality, especially readability aspect, of text summary can be reached if the meaning of the text can be maintained properly. Therefore, this research aims to enhance the quality of extractive Indonesian automatic text summarization with considering the quality of structured representation of text. This research uses sequential pattern mining (SPM) to produce This research use SPM to produce sequence of words (SoW) as structured text representation using PrefixSpan algorithm. Then, SPM is combined with feature-based approach using sentence scoring method to produce summary. The experiment result using IndoSum dataset shows that even though the combination of SPM and sentence scoring can increase the precision value of recall-oriented understudy for gisting evaluation (ROUGE)-1, ROUGE-2, and ROUGE-L, from 0.68 to 0.76, 0.54 to 0.69, and 0.51 to 0.72. Especially, combination of SPM and Sentence Scoring can enhance precision, recall, and f-measure of ROUGE-L that consider the order of word occurance in measurement. SPM increases ROUGE-L f-measure value of sentence scoring from 0.32 to 0.36. Moreover, combination of sentence scoring and SPM is better than SumBasic that used as feature-based approach in the previous Indonesian text summarization research.
Combination of Graph-based Approach and Sequential Pattern Mining for Extractive Text Summarization with Indonesian Language Dian Sa'adillah Maylawati; Yogan Jaya Kumar; Fauziah Binti Kasmin
Khazanah Informatika Vol. 9 No. 2 October 2023
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v9i2.21495

Abstract

The great challenge in Indonesian automatic text summarization research is producing readable summaries. The quality of text summary can be reached if the meaning of the text can be maintained properly. As a result, the purpose of this study is to improve the quality of extractive Indonesian automatic text summarization by taking into account the quality of structured text representation. This study employs Sequential Pattern Mining (SPM) to generate a sequence of words as a structured representation of text and a graph-based approach to generate automatic text summarization. The SPM algorithm used is PrefixSpan, and the graph-based approach uses the Bellman-Ford algorithm. The results of an experiment using the IndoSum dataset show that combining SPM and Bellman-Ford can improve the precision, recall, and f-measure of ROUGE-1, ROUGE-2, and ROUGE-L. When Bellman-Ford is combined with SPM, the F-measure of ROUGE-1 increases from 0.2299 to 0.3342. The ROUGE-2 f-measure increases from 0.1342 to 0.2191, and the ROUGE-L f-measure increases from 0.1904 to 0.2878. This result demonstrates that SPM can improve the performance of the Bellman-Ford algorithm in producing Indonesian text summaries.
Co-Authors Achmad Kholiq Adi Putra Andriyandi Agung Wahana Ahmad Fathonih, Ahmad Akhmad Ridlo Rifa'i Al-Amin, Muhammad Insan Aldi Fahluzi Muharam Ali, Hapid Barzan Faizin Cecep Nurul Alam Cecep Nurul Alam, Cecep Nurul Cepy Slamet Cepy Slamet Diena Rauda Ramdania Enjang AS, Enjang Fatonah, Fany Risti Fauziah Binti Kasmin Fauziah Binti Kasmin Fitri, Susanti Ainul Ghifari Munawar Hamdan Sugilar Harahap, Akbar Hidayatullah Hartawan, Gaduh Herdiyanto, Reza Fahlevi Hilmi Aulawi Ichsan Budiman Ichsan Taufik Imam Fahmi Fadillah Kasmin, Fauziah Kholiq, Achmad Khosyi'ah, Siah Kumar, Yogan Jaya Lillah, M. Rival Ridautal Lillah Marwah Maulana Sidik Melani Nur Mudyawati Mi’raj Fuadi Mohamad Irfan Muhammad Ali Ramdhani Muhammad Ali Ramdhani Muhammad Humam Wahisyam Muhammad Indra Nurardy Saputra Muhammad Insan Al-Amin Muhammad Khalifa Umana Muharam, Aldi Fahluzi Nugraha, Rizky Rahmat Nur Lukman Nurlatifah, Eva Nurrohman, Nurrohman Pitriani, Pitriani Rachmat Jaenal Abidin Rahman, Titik Khawa Abdul Ridwan Setiawan Riki Ahmad Maulana Rinda Cahyana Rio Guntur Utomo Riyan Naufal Hay's Rizkiansyah Dewantara Rizqullah, Naufal Rohmat Mulyana Rohmat Mulyana Sapdi Rully Agung Yudhiantara Saputra, Muhammad Indra Nurardy Septya Egho Pratama Siah Khosyi'ah Siah Khosyi'ah Syafi’i Syafi’i Syahrifudin, Umar Teddy Mantoro Tedi Priatna Teja Endra Eng Tju Ukan Saokani Umar Syahrifudin Utomo, Suharjanto Wahyudin Darmalaksana Wildan Budiawan Zulfikar Wisnu Uriawan, Wisnu Yana Aditia Gerhana, Yana Aditia Yniarto, Kurniawan Yogan Jaya Kumar Yogan Jaya Kumar Yuhendra AP