Hasil Pencarian  ::  Simpan CSV :: Kembali

"ABSTRACTPlagiarism is an act of taking or stealing ideas of others, whether intentionally or not. This plagiarism can happen anywhere, by anyone, and in various forms of writing. This plagiarism is referred to as academic crime, so it must be avoided by all parties. This article will examine ways to prevent plagiarism. The scope of this study is in the Indonesian online tutorial at Universitas Terbuka. This article is written based on observations and practices in tutorial activities. In the context of this discussion, plagiarism means writing the same answers from several students during the learning activities. The similarity of answers may be obtained from similar sources. The similariries occur because there is no attempt to write with the correct citation, or paraphrase it. Therefore, it demands creativity and innovation from the tutor in conducting the learning or tutorial, both during discussion time and tutorial task. Creativity is applied in selecting and designing the problem form in discussion activities. This creativity is also related to the skills of the tutor in higher order thinking skills to the students. The concept of innovation is applied in the dynamics of the problem in the tutorial task. Dynamic tutorial will be an indicator of professional educator in performing his duties as tutor. Through the creativity and innovation of tutors, students are indirectly required to answer honestly, thoroughly, and comprehensively. Besides, students are also required to always open the material and questions, because the tutor creates the tutorial class to be dynamic, not static. In this way, the tutorial activities will be a medium and place oflearning for students and tutors."

"Penelitian yang dilakukan adalah pengembangan program pendeteksi plagiarisme otomatis dwibahasa dengan waktu pelaksanaan yang singkat. Penggunaan MySQL sebagai sistem basis data menyebabkan program membutuhkan waktu yang lama untuk menyelesaikan eksekusinya, sehingga pada penelitian ini sistem basis data diganti pada program. Sistem database yang dipilih adalah Redis karena Redis menyimpan data dalam memori, sehingga diharapkan pengambilan data dapat dilakukan dengan lebih cepat. Pada akhir penelitian, berdasarkan perbandingan program yang menggunakan database Redis dengan program yang menggunakan database MySQL didapatkan bahwa penggunaan database Redis membuat eksekusi program lebih cepat sekitar 2999.335% hingga 3050.966% dibandingkan program yang digunakan. database MySQL. Pada penelitian ini juga dibuat sistem antarmuka pengguna grafis untuk program deteksi plagiarisme. Hal ini bertujuan agar pengguna lebih mudah dalam menggunakan program dan pengguna dapat langsung mengunggah makalah yang ingin diuji tingkat plagiarismenya. Pengujian pada sistem antarmuka program dilakukan dengan menanyakan penilaian terhadap 30 pengguna yang telah menggunakan program. Hasil pengujian pada antarmuka ini mendapatkan nilai akhir sebesar 87.93% di evaluasi alat ukur oleh pengguna sehingga termasuk dalam kategori Sangat Baik. Sedangkan pada pengukuran skala usability sistem, desain antarmuka program deteksi plagiarisme memperoleh skor akhir 79,16 dan termasuk dalam kategori Baik.

---

The research conducted is the development of a bilingual automatic plagiarism detection program with a short implementation time. The use of MySQL as a database system causes the program to take a long time to complete its execution, so that in this study the database system was replaced in the program. The database system chosen is Redis because Redis stores data in memory, so it is hoped that data retrieval can be done more quickly. At the end of the study, based on a comparison of programs using the Redis database and the programs using the MySQL database, it was found that the use of the Redis database made program execution faster by around 2999.335% to 3050.966% compared to the programs used. MySQL database. In this research, a graphical user interface system for the plagiarism detection program was also developed. This aims to make it easier for users to use the program and users can directly upload the paper they want to test for plagiarism level. Testing on the program interface system is carried out by asking for an assessment of 30 users who have used the program. The test results on this interface get a final score of 87.93% in the evaluation of the measuring instrument by the user so that it is included in the Very Good category. Whereas in the measurement of the system usability scale, the plagiarism detection program interface design obtained a final score of 79.16 and was included in the Good category."

"Education field is one of area have to be paid attention from plagiarism activity. The students are common part related to this criminal activity. They usually get involved in copying the programming assignments, for example source code duplication...."

"Tugas Akhir ini membahas tentang bagaimana fenomena plagiarisme banyak terjadi dalam pembuatan konten didalam media social Youtube, baik melakukan copy sebagian maupun seluruhnya, rata-rata content creator jangan memberikan apresiasi kepada pemilik asli konten yang bersangkutan . Tugas akhir ini  adalah hasil penelitian kualitatif dengan penjelasan deskriptif disertai dengan pemaparan beberapa kasus yang terjadi di masyarakat serta tertulis dalam artikel . Hasil tugas akhir ini menyarankan bahwa peranan orang-orang di dalam Industri Youtube dan peran serta sebuah regulasi tertulis memang sangat sesuai untuk mengurangi dampak plagiarisme didalam pembuatan konten. Selain itu dengan tidak diberikannya apresiasi monetize atau suspend sementara maupun teguran dari pihak Youtube langsung merupakan salah satu bentuk pengurangan pelanggaran Hak Cipta yang baik yang telah dilakukan dan perlu terus mendapatkan pengembangan sesuai dengan kebutuhan pasar

---

This Final Project discusses how a lot of the phenomena of plagiarism occur inmaking content in social media Youtube, either copying part or all of it, on average the content creator should not give appreciation to the original owner of the content in question. This final project is the result of qualitative research with a descriptive explanation accompanied by exposure to several cases that occurred in the community and written in the article. The results of this final project suggest that the role of people in the Youtube Industry and the role of a written regulation are indeed very appropriate to reduce the impact of plagiarism in content creation. Besides that, by not giving monetize appreciation or temporary suspend or reprimand from YouTube directly, it is one of the forms of reducing copyright infringement that has been done and needs to continue to get development in accordance with market needs.

Keyword               : Plagiarism, Copyright , Content Creator

 

---

This Final Project discusses how a lot of the phenomena of plagiarism occur inmaking content in social media Youtube, either copying part or all of it, on average the content creator should not give appreciation to the original owner of the content in question. This final project is the result of qualitative research with a descriptive explanation accompanied by exposure to several cases that occurred in the community and written in the article. The results of this final project suggest that the role of people in the Youtube Industry and the role of a written regulation are indeed very appropriate to reduce the impact of plagiarism in content creation. Besides that, by not giving monetize appreciation or temporary suspend or reprimand from YouTube directly, it is one of the forms of reducing copyright infringement that has been done and needs to continue to get development in accordance with market needs.

Keyword               : Plagiarism, Copyright , Content Creator 

"

"Pada skripsi ini dibuat rancangan sistem deteksi plagiarisme pada karya tulis digital dua bahasa Indonesia - Inggris . Bahasa Indonesia digunakan sebagai karya tulis yang akan diuji dan bahasa Inggris sebagai karya tulis referensinya. Sistem ini menerapkan algoritma winnowing yang dilengkapi dengan metode penerjemah bahasa dan synonym recognition. Metode synonym recognition ini mampu mendeteksi sinonim dari tiap kata, mampu melakukan perubahan kata secara otomatis ketika diperlukan, dan mampu meningkatkan akurasi pada sistem deteksi plagiarisme dua bahasa yang sedang dikembangkan. Hasil penelitian ini menunjukkan bahwa penggunaan parameter winnowing yang tepat serta dilengkapi synonym recognition didapatkan peningkatan akurasi sistem dari 0.03 hingga 13.04.

---

In this thesis, the design of plagiarism detection system on bilingual digital essay Indonesian English . Indonesian used as a document to be tested and English as a reference document. The system applies winnowing algorithms that are equipped with language translator methods, and synonym recognition.

This synonym recognition method is able to detect synonyms of each word, capable of automatically changing words as needed, and capable of improving accuracy in the bilingual plagiarism detection system being developed.

The results of this study indicate that the use of appropriate winnowing parameters and by applying synonym recognition obtained improved system accuracy from 0.03 to 13.04."

"Pengembangan sistem pendeteksi plagiarisme dibuat untuk mengatasi masalah plagiarisme yang kerap terjadi pada dunia akademis. Pada skripsi ini dibuat sistem pendeteksi plagiarisme otomatis pada karya tulis digital dwi bahasa Indonesia-Inggris dengan Bahasa Indonesia digunakan sebagai karya tulis yang akan diuji dan Bahasa Inggris sebagai karya tulis referensinya. Sistem menerapkan algoritma winnowing yang dilengkapi dengan metode penerjemah bahasa Googletrans API dan similar words. Algoritma winnowing merupakan algoritma yang dapat mendeteksi kesamaan antar teks dengan menggunakan fingerprint yang didapat dari proses hashing karakter teks. Penelitian dilakukan untuk meningkatkan akurasi sistem dan mengetahui metode penilai kesamaan teks yang akurat. Dari hasil penelitian, didapatkan bahwa parameter terbaik algoritma winnowing secara umum terdapat saat nilai k-window = 5 dan nilai basis bilangan prima bernilai 3. Parameter n-gram bernilai kecil akan lebih akurat pada teks yang memiliki jumlah kata lebih sedikit dan/atau tingkat plagiarisme tinggi dan sebaliknya. Tingkat akurasi sistem pendeteksi plagiarisme otomatis dwi bahasa yang dikembangkan berkisar antara 75.02 hingga 99.51. Metode Cosine Similarity menjadi metode penilai kesamaan teks terbaik dari hasil penelitian ini. Selain itu, metode penerjemahan Googletrans API juga memberikan kelebihan dalam hal akurasi dan kelengkapan data kamus dibandingkan dengan metode kamus terjemahan database.

---

The development of plagiarism detection system is made to overcome the problem of plagiarism that often occurs in the academic world. In this thesis, an automatic plagiarism detection system on bilingual digital paper Indonesian English is created with Indonesian is used as the tested paper and English as the reference paper. The system implements the winnowing algorithm that comes with the Googletrans API language translator method and similar words. Winnowing algorithm is an algorithm that can detect similarity between text by using fingerprint obtained from hashing process of text character. The study was conducted to improve system accuracy and to know accurate method of text equality assessment.

From the study result, it is found that the best parameter of winnowing algorithm is generally occured when the value of k window 5 and the base value of the prime number is 3. The smaller value of n gram parameter will be more accurate in text that has fewer word counts and or high plagiarism levels and vice versa. The accuracy level of the automatic plagiarism detection system in the developed language ranged from 75.02 to 99.51 .

The Cosine Similarity method is the best method of text equality assessment according to results of this study. In addition, the Googletrans API translation method also provides advantages in terms of accuracy and completeness of dictionary data as compared to database translation dictionary method."

"Penelitian yang dilakukan berupa pengembangan terhadap sistem pendeteksi plagiarisme otomatis sehingga dapat menerapkan jaringan saraf tiruan Self-Organizing Map SOM untuk melakukan klasifikasi terhadap hasil keluaran Latent Semantic Analysis. SOM dipilih untuk melakukan klasifikasi karena algoritma ini tidap perlu melakukan supervisi pada proses pembelajarannya sehingga dapat secara otomatis menentukan tingkat plagiarisme antar paragraf yang tidak mudah ditentukan secara langsung oleh manusia. Selain itu dilakukan perbandingan akurasi penentuan tingkat plagiarisme yang dimiliki oleh sistem apabila hanya menggunakan LSA saja, penggunaan LSA dengan SOM, dan penggunaan LSA dengan Learning Vector Quantization LVQ. Penggunaan SOM dan LVQ dilakukan untuk melakukan klasifikasi tingkat plagiarisme dari hasil keluaran LSA. Penentuan tingkat plagiarisme sudah cukup dilakukan apabila hanya menggunakan LSA saja, dimana sudah dapat menghasilkan tingkat akurasi paling tinggi yaitu 86,24. Namun, penggunaan SOM dengan jumlah kelas sebanyak 2 dengan 3 parameter memberikan rata-rata tingkat akurasi yang sedikit lebih rendah, yaitu sebesar 82,00. Sedangkan penggunaan LVQ dengan jumlah kelas sebanyak 2 dengan 3 parameter juga memberikan rata-rata tingkat akurasi yang sedikit lebih tinggi dibandingkan, yaitu sebesar 82,10.

---

This research has concern on deployment of neural network algorithm Self Organizing Map SOM in automatic plagiarism detector so it could be used to classify the output from Latent Semantic Analysis. SOM is chosen because it is an unsupervised neural network algorithm. With unsupervised neural network, it could determine the plagiarism level between paragraf automatically, which hard for human to determine it. Other than deployment of SOM, this research also focusses on the comparison of accuracy of the system if the system only deploys pure LSA, combination of LSA and SOM, and combination of LSA and Learning Vector Quantization LVQ.

SOM and LVQ are used to do classification for the output from LSA. Plagiarism level could be determined by the result of LSA only. It has 86,24 as the highest accuracy level. But, the usage of SOM with 2 classes and 3 parameters gives lower average of accuracy, which is 82,00 . Therefore, usage of LVQ with 2 classes and 3 parameters gives slight better accuracy than SOM, which is 82,10."