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The Algorithm Of Giving Automatic Harakat On Arabic Script Without Harakat Using Cyclomatic Complexity Testing Qudsi, Dini Hidayatul; Saf, Maksum Ro’is Adin
Prosiding International conference on Information Technology and Business (ICITB) 2017: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 3
Publisher : Prosiding International conference on Information Technology and Business (ICITB)

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Abstract

The majority of Arabic reference books in Arabic writing without a vowel/harakat cause students to have difficulty in learning Arabic. Reading Arabic Script without harakat requires an understanding of the science of Nahwu-Sharf (Arabic Grammar) to be able to understand its contents. Therefore, in this study the science of Nahwu-Sharf has been translated into an algorithm that can be used to provide an automatic harakat on Arabic script (without harakat). The generated algorithm has been examined using cyclomatic complexity and results in accordance with Nahwu-Sharf science, through an 9-path test case examination. It means that the algorithm is assumed to be well-structured, highly testable and maintainable. Keywords : Arabic, Harakat, Nahwu-Sharf, Algorithm, and Cyclomatic Complexity Testing.
PENGEMBANGAN ALGORITMA PENGENALAN JENIS KALIMAT PADA BAHASA ARAB DENGAN METODE AFFIX MAPPING Maksum Ro’is Adin Saf; Dini Hidayatul Qudsi; Istianah Muslim
Jurnal Teknologi Informasi dan Terapan Vol 4 No 2 (2017)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v4i2.66

Abstract

Arabic is one of the most popular languages in Indonesia which is Muslim population being majority. Ability to recognize the types of sentence in Arabic Language is one of basic topic in Arabic language studying. The type of sentence in Arabic is known from the first word in the sentence, but often the first word of a sentence is not the original words, so it can not be found directly in the dictionary. In this reseach, the Arabic Stemming algorithm was modified to find the type of the word using affixes include to the word, this method refers to the rules in Sharf science, therefore this method is named as Affix Mapping Algorithm. The algorithm that has been prepared is tested using Cyclomatic Complexity method and the result shows that the independent path obtained is 5, from the result it can be concluded that the algorithm is structured well, very easy to test, and last long.
Analisis Sentimen pada Data Saran Mahasiswa Terhadap Kinerja Departemen di Perguruan Tinggi Menggunakan Convolutional Neural Network Yuliska Yuliska; Dini Hidayatul Qudsi; Juanda Hakim Lubis; Khairul Umum Syaliman; Nina Fadilah Najwa
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 5: Oktober 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021854842

Abstract

Review atau saran dari customer dapat menjadi sangat penting bagi penyedia layanan, begitu pula saran dari mahasiswa mengenai layanan sebuah unit kerja di perguruan tinggi. Review menjadi penting karena dapat menjadi indikator kinerja penyedia layanan. Pengolahan review juga sangat penting karena dapat menjadi referensi untuk pengambilan keputusan dan peningkatan layanan yang lebih baik ke depannya. Penelitian ini menerapkan analisis sentimen pada data saran atau review mahasiswa terhadap kinerja unit kerja atau departemen di perguruan tinggi, yaitu Politeknik Caltex Riau. Analisis sentimen dilakukan dengan menggunakan Convolutional Neural Network (CNN) dan word embedding Word2vec sebagai representasi kata. CNN merupakan metode yang memiliki performa yang baik dalam mengklasifikasi teks, yaitu dengan teknik convolutional yang menggabungkan beberapa window kata pada kalimat dan mengambil window yang paling representative. Word2Vec digunakan sebagai representasi data saran dan inputan awal pada CNN, dimana Word2Vec merupakan dense vectors yang dapat merepresentasikan hubungan antar kata pada data saran dengan baik. Saran mahasiswa dapat mengandung kalimat yang sangat panjang, karena itu perpaduan Word2Vec sebagai representasi kata dan CNN dengan teknik convolutional, dapat menghasilkan representasi yang representative dari kalimat panjang tersebut. Penelitian ini menggunakan dua arsitektur CNN, yaitu Simple CNN dan DoubleMax CNN untuk mengidentifikasi pengaruh kompleksitas arsitektur terhadap hasil klasifikasi sentimen.  Berdasarkan hasil pengujian, DoubleMax CNN dapat mengklasifikasi sentimen pada saran mahasiswa dengan sangat baik, yaitu mencapai Akurasi tertinggi sebesar 98%, Recall 97%, Precision 98% dan F1-Score 98%. AbstractStudent’s reviews about department performance can be essential for a college for it can be used to evaluate the department performance and to take an immediate action to improve its performance. This research applies sentiment analysis in the student’s reviews of college department in Politeknik Caltex Riau. Convolutional Neural Network and Word2Vec are employed to analyze the sentiment. CNN is known for its good performance in text classification by applying a convolutional technique to the input sentences. Word2Vec is used as word representation and as an input to the CNN. Word2Vec are dense vectors which can represent the relationship between words excellently. Student’s reviews can be a long sentence; hence the combination of Word2Vec as word representation and CNN with convolutional technique can produce a representative fiture from that long sentence. This research utilizes two CNN architectures, which are Simple CNN dan DoubleMax CNN to identify the effect of the complexity of CNN architecture to final result. Our experiments show that DoubleMax CNN has a great performance in classifying sentiment in the student’s reviews with the best Accuracy value of 98%, Recall 97%, Precision 98% and F1-Score value of 98%.
THE ALGORITHM OF GIVING AUTOMATIC HARAKAT ON ARABIC SCRIPT Dini Hidayatul Qudsi; Maksum Ro’is Adin Saf
Jurnal Ilmiah Kursor Vol 9 No 2 (2017)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v9i2.145

Abstract

The majority of Arabic reference books in Arabic writing without a vowel/harakat causestudents to have difficulty in learning Arabic. Reading Arabic Script without harakatrequires an understanding of the science of Nahwu-Sharf (Arabic Grammar) to be able tounderstand its contents. Therefore, in this study the basic rules of Nahwu-Sharf Sciencehave been translated into an algorithm that can be used to provide an automatic harakaton Arabic script (without harakat). Based on the interview results with the expert, sixexamples of sentences that represented the types(conditions) of basic sentences in theArabic language have been used as scenarios to examine the generated algorithm. Theallowed sentence is limited to one sentence only and cannot be in the form of poetry orsatire. Additionally, Cyclomatic Complexity Testing is used to examine scenarios in a testcase. All the steps of the Cyclomatic Complexity have been performed, which are creatingthe flowgraph, calculating the independent path, and testing scenario. The scenarios wereexamined in a test case through 13-path test case examination and result match withexpected output. In addition, 24 examples which represented the six conditions have beenutilized to examine for more detailed analysis and also results accuracy 100% inaccordance with the basic rules of Nahwu-Sharf science.
Predictive Analytics Data Mining in Imbalanced Medical Dataset Dini Hidayatul Qudsi
Jurnal Komputer Terapan  Vol. 2 No. 2 (2016): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

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Abstract

Predictive Analytics Data Mining in Imbalanced Medical Dataset
Pengembangan Sistem Business Intelligence untuk Analisa Pola Tindak Pidana di Pengadilan Negeri Pekanbaru dea pricillia mulyani; ardianto wibowo; Dini Hidayatul Qudsi
Jurnal Komputer Terapan  Vol. 4 No. 2 (2018): Jurnal Komputer Terapan November 2018
Publisher : Politeknik Caltex Riau

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Abstract

The District Court is an agency that handles criminal offenses in Pekanbaru. Based on the results of an interview with the Registrar's Office of Law, it is known that the Pekanbaru District Court reported and analyzed cases regarding the criminal acts of the Police and Prosecuting Office, where it was required to report criminal acts. Therefore, a website-based Business Intelligence (BI) system is built to process criminal data that is visualized into dashboards to support the Legal Registrar in obtaining criminal patterns that occur in Pekanbaru, and allows evaluating the internal performance of the Pekanbaru District Court, using the CI framework and use the PHP programming language. Based on UAT testing the function on the system has been successfully built and running well, usability testing results with a questionnaire to the Registrar's Office of Law, showing that the system is 94% easy to use, 91% studied, 95% useful, and 88% satisfying. And system efficiency found that the measurement of performance levels on web pages based on certain aspects get a percentage of 67% and the time needed to load a web page is a percentage of 70%.
Pemodelan Data dengan Skema Galaksi pada Data Lulusan Dini Nurmalasari; Dini Hidayatul Qudsi; Mutia Sari Zulvi; Warnia Nengsih
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2020: SNTIKI 12
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Indikator kebijakan pada bagian akademik mengacu kepada Standar Nasional Pendidikan Tinggi (SN Dikti). Berdasarkan pasal 54 UU Dikti, SN Dikti merupakan satuan standar yang meliputi standar nasional pendidikan, ditambah dengan standar penelitian, dan standar pengabdian kepada masyarakat. Standar Pendidikan Tinggi yang ditetapkan oleh setiap Perguruan Tingg terdiri atas sejumlah standar dalam bidang akademik dan nonakademik. Indikator yang ada pada SN Dikti terdiri dari indikator yang bersifat kuantitatif dan kualitatif. Saat ini untuk menghasilkan data yang dibutuhkan untuk pelaporan Standar Mutu Perguruan Tinggi, masih dilakukan secara manual melalui penggabungan dari beberapa sistem informasi yang ada di Politeknik Caltex Riau (PCR). Hal ini mengakibatkan beberapa kendala diantarnya lamanya proses untuk mendapatkan data, data tidak konsisten, dan mengganggu kinerja sistem informasi transaksional yang ada. Pada penelitian ini dilakukan pemodelan data secara multidimensi, yang bertujuan untuk mengintegrasikan semua data yang dibutuhkan, sehingga dapat memberikan solusi terhadap permasalahan saat ini. Pemodelan dilakukan dengan pendekatan model skema galaksi (fact constallation schema) yang diharapkan dapat memaksimalkan waktu proses, sehingga dapat mempercepat kinerja dari data warehouse yang dibangun. Dari hasil penelitian yang telah dilakukan, kesederhanaan query skema galaksi berpengaruh pada kecepatan waktu query, akurasi dan konsistensi data.
Mining Student's Reviews to Obtain Their Perception toward College Department Performance Yuliska Yuliska; Dini Hidayatul Qudsi; Lya Anggraini; Juanda Hakim Lubis
International ABEC 2021: Proceeding International Applied Business and Engineering Conference 2021
Publisher : International ABEC

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Abstract

Student’s perception toward department performance can be crucial, therefore, it can be used to evaluate the department outcome and take an immediate action to improve its management. This study applies sentiment analysis and topic modeling to the student’s reviews of college department at Politeknik Caltex Riau in order to mine student’s perception for seven college departments performance. Sentiment analysis with Support Vector Machine (SVM) is employed to obtain student’s sentiment. There are 3 types of sentiments to be analyzed; positive, negative and neutral. Topic modeling with Latent Dirichlet Allocation (LDA) is also carried out to get some important keywords in the student’s reviews. Our experiments show that Positive is the most prominent sentiment in the student’s reviews while LDA reveals some important topics toward preferences.
Pelatihan Penggunaan Open Journal System (OJS) Bagi Dosen Politeknik Caltex Riau Dini Hidayatul Qudsi; Khairul Umam Syaliman; Ibnu Surya; Mona Elviyenti
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 1 No. 1 (2023): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (320.687 KB) | DOI: 10.35143/jiterpm.v1i1.5909

Abstract

Jurnal ilmiah merupakan salah satu indikator penting dalam perkembangan keilmuan. Aktifitas penelitian atau kegiatan ilmiah seacara umum, biasanya menuntut publikasi sebagai salah satu bentuk laporan dan presentasi hasil penelitian. Hal ini tentunya sejalan dengan Tri Dharma Perguruan Tinggi, yaitu Pengajaran, Penelitian, dan Pengabdian Kepada Masyarakat. Rata-rata perguruan tinggi telah menggunakan Open Journal System (OJS) dalam pengelolaan jurnal. Penggunaan tools ini dapat mempermudah pengelolaan jurnal-jurnal yang ada. Pemanfaatan OJS dilingkungan Politeknik Caltex Riau belum termaksimalkan, hal ini di sebabkan oleh segi sumber daya pengelolaan, yaitu dosen di lingkungan Politeknik Caltex Riau yang masih kesulitan dalam menggunakan OJS dan kurang memahami alur proses publikasi menggunakan OJS. Maka pelatihan penggunaan OJS bagi dosen-dosen di lingkungan Politeknik Caltex Riau penting untuk diselenggarakan.
IMPLEMENTASI ALGORITMA FP-GROWTH DALAM PENENTUAN POLA HUBUNGAN KECELAKAAN LALU LINTAS Rizky Fitria; Warnia Nengsih; Dini Hidayatul Qudsi
Jurnal Sistem Informasi Vol. 13 No. 2 (2017): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.361 KB) | DOI: 10.21609/jsi.v13i2.551

Abstract

Tingginya jumlah kecelakaan yang terjadi menjadi alasan penting bagi pihak Satuan Lalu Lintas, salah satunya Polresta Pekanbaru untuk mengetahui hubungan antara factor-faktor penyebab kecelakaan. Hubungan tersebut dipelajari dengan menggunakan teknik data mining. Teknik ini bertujuan untuk menemukan informasi berupa pola yang dapat menjadi acuan dalam pengambilan kebijakan di Satuan Lalu Lintas Polresta Pekanbaru. Teknik data mining yang digunakan yaitu teknik association rule dengan Algoritma Fp-growth. Algoritma ini menerapkan struktur data tree untuk mengetahui pola kecelakaan lalu lintas. Pola tersebut ditentukan oleh dua parameter, yaitu support (nilai penunjang) dan confidence (nilai kepastian). Sistem dibuat berbasis desktop dengan bahasa pemograman Visual Basic.Net. Sistem ini menghasilkan pola kecelakaan yang sering terjadi. Berdasarkan pengujian lift ratio, didapatkan pola kecelakaan yang paling sering terjadi, yaitu faktor kecelakaan dengan jenis_luka adalah luka ringan, jenis_jalan adalah jalan arteri, waktu adalah padat kendaraan, dan jenis_kelamin adalah perempuan dengan nilai lift ratio 1.20%. Sedangkan hasil pengujian skala Likert didapatkan bahwa 88.09% pengguna merasa dimudahkan dengan sistem ini dan dapat membantu mereka dalam mengetahui pola kecelakaan yang sering terjadi.
Co-Authors Ardianto Wibowo dea pricillia mulyani Ibnu Surya Istianah Muslim Juanda Hakim Lubis Juanda Hakim Lubis Khairul Umam Syaliman Khairul Umam Syaliman Lya Anggraini Maksum Ro’is Adin Saf Maksum Ro’is Adin Saf Mona Elviyenti mutia sari zulvi Najwa, Nina Fadilah Nurmalasari, Dini Rizky Fitria Saf, Maksum Ro’is Adin Vandi Rahman Warnia Nengsih Warnia Nengsih Yuliska Yuliska