Analisa Sentiment Untuk Opini Alumni Perguruan Tinggi

dharmendra, komang; Saputra, Komang Oka; Pramaita, I Nyoman

doi:10.24843/mite.2019.v18i02.p11

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Opini dari alumni dikumpulkan saat mahasiswa telah menyelesaikan masa studi dan dinyatakan lulus, dan opini yang disampaikan dari mahasiswa tersebut adalah hal yang mereka alami selama menempuh Pendidikan. Untuk mendapatkan informasi dari opini yang disampaikan oleh alumni dilakukan analisa sentimen, untuk mengeluarkan informasi apakah opini yang disampaikan oleh alumni tersebut bernilai positif, negative, atau netral [1].…”

Section: Pendahuluanunclassified

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping

Dharmendra¹,

Januhari²,

Ramayasa³

et al. 2022

JTIUST

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Dalam penyimpanan data, dokumen pengiriman disimpan tanpa pengamanan khusus. Untuk mengatasi masalah di atas, diperlukan cara yang cepat untuk melindungi data dari penyalahgunaan. Peneliti bertujuan untuk menggunakan teknik enkripsi deskriptif algoritma AES 128-bit pada sistem, karena memiliki tingkat ketahanan tertentu terhadap segala jenis serangan untuk menghindari kehilangan dan pencurian serta mengurangi risiko korupsi data/file. Proses enkripsi dan deskripsi file dokumen menggunakan algoritma AES 128-bit (Advanced.Encryption Standard ). Pada data/file, proses enkripsi plaintext (1 blok) terlebih dahulu diubah menjadi kode ASCII bilangan heksadesimal dan dibentuk menjadi matriks 4x4 byte yang disebut state . Proses enkripsi pada AES 128 adalah 10 loop iteratif transisi state . Data yang diproses pada setiap putaran adalah data biner . Setiap putaran AES membutuhkan pembangkitan kunci dan menggunakan 4 transformasi dasar, yaitu subbyte, shiftrows, mixcolumns, dan addroundkey. Dan proses dekripsi mengkonversi dalam urutan invshiftrows, invsubbytes, addroundkey, dan invmixcolumns. Pemrosesan enkripsi dan dekripsi dilakukan setiap 128 bit atau 16 karakter dalam file dokumen dengan lebih dari 16 karakter yang dikonfirmasi. Jadikan proses enkripsi dan dekripsi AES paralel. Untuk file teks dengan kurang dari 16 karakter, padding akan terjadi. Padding adalah penggunaan karakter ASCII kosong untuk mengisi sejumlah kecil karakter sehingga dapat diproses tanpa mempengaruhi hasil enkripsi atau dekripsi.

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Section: Pendahuluanunclassified

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping

Dharmendra¹,

Januhari²,

Ramayasa³

et al. 2022

JTIUST

View full text Add to dashboard Cite

show abstract

“…Terdapat beberapa penelitian sebelumnya terkait komplain layanan yang dilakukan oleh beberapa peneliti seperti, Analisa Sentiment Untuk Opini Alumni Pada Perguruan Tinggi (Dharmendra, Saputra, & Pramaita, 2019 (Basari, Hussin, Ananta, & Zeniarja, 2013). Penerapan principal component analysis dan genetic algorithm pada analisis sentimen review pengiriman barang menggunakan algoritma support vector machine (Rachmi, 2017).…”

Section: Jurnal Ilmu Pengetahuan Dan Teknologi Komputerunclassified

Algoritma Klasifikasi Naive Bayes Dan Support Vector Machine Dalam Layanan Komplain Mahasiswa

Hermanto

Mustopa²,

Kuntoro³

2020

jitk

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Service in the world of education is an important element for the creation of an academic atmosphere that is conducive to the implementation of a successful teaching and learning process. The process of service to students there is a tendency to be implemented not following the minimum service standards that must be provided to students so that students tend to complain about the services provided. Submission of criticism, complaints, input, or suggestions for dissatisfaction and problems that exist in the university environment is still very limited. Complaints can be constructive if submitted to the right place and party. In this research the data processing of email complaints from students conducted at the academic student body (students.bsi.ac.id). Student complaint data that will be processed is data in the form of * .xls complaint file. Before text data is analyzed using text mining methods, the pre-processing text needs to be done including tokenizing, case folding, stopwords, and stemming. After pre-processing, the classification method is then performed in classifying each complaint category and dividing the status into two parts, namely complaint and not complaint so that the status becomes a normal condition in text mining research. The purpose of this study is to obtain the most accurate algorithm in the classification of student complaints and can find out the results of the classification of the Naïve Bayes algorithm method and Support vector Machine used and compared. In this study, the results of testing by measuring the performance of these two algorithms using Cross-Validation, Confusion Matrix, and ROC Curves. The obtained Support vector Machine algorithm has the highest accuracy value compared to Naïve Bayes. AUC value = 0.922. for the Support vector machine method using the student academic data collection dataset (students.bsi.ac.id) has 84.45%, from the Naïve Bayes algorithm has an accuracy rate of about 69.75% and AUC value = 0.679.

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Gojek and Grab User Sentiment Analysis on Google Play Using Naive Bayes Algorithm And Support Vector Machine Based Smote Technique

Hermanto

Kuntoro²,

Asra

et al. 2020

J. Phys.: Conf. Ser.

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As the online Ojek services, people often talk about them by giving their opinions and opinions through various media, one of which is Google Play opinion given by the public to the services of online Ojek also diverse. Users provide review reviews or comments about the application, of course users will choose an app that has a good review. But monitoring the reviews of the general public is not easy, because the amount is very much to be processed so that researchers want to know the extent of the user review analysis of Gojek and Grab applications based on the review of user comments using the classification technique is using the NB algorithm and SVM based technique Smote. The results of the test with the highest accuracy result 81.09% and AUC value = 0.922 is the application Gojek while for application test results grab accuracy value of 73.20% and AUC value = 0.848. To that end, the implementation of the Support Vector Machine based Smote technique in this study has higher accuracy so that it can be used to provide solution to the sentiment analysis problems in the review user comments online Ojek application

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Analisa Sentiment Untuk Opini Alumni Perguruan Tinggi

Cited by 3 publications

References 6 publications

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping

Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping

Algoritma Klasifikasi Naive Bayes Dan Support Vector Machine Dalam Layanan Komplain Mahasiswa

Gojek and Grab User Sentiment Analysis on Google Play Using Naive Bayes Algorithm And Support Vector Machine Based Smote Technique

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