Garuda - Garba Rujukan Digital

Sentiment Analysis of Beauty Product Applications using the Naïve Bayes Method Rambe, Tiara Syavitri; Hasibuan, Mila Nirmala Sari; Dar, Muhammad Halmi
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12303

The number of beauty products that appear on the market makes every producer compete in attracting consumers. One of the facilities provided by manufacturers to make it easier for consumers to shop is an online shopping application that can be accessed via gadgets. Where the feature of the application is the availability of user review services User reviews are often used as a recommendation for the product to be purchased. The more positive the reviews that appear, the greater the consumer's confidence to buy the product; conversely, the more negative the reviews that appear, the more reluctant consumers are to buy. This study aims to find out how much accuracy the Naïve Bayes algorithm has in conducting sentiment analysis on user reviews of beauty product applications with different combinations of training and test data. Furthermore, it is also important to know the frequency of words that often appear in the review. The sentiment class used is divided into three, namely, positive, negative, and neutral. This research method includes a number of stages, namely: data collection, data labeling, text pre-processing, data visualization, TF-IDF, sentiment analysis, etc., until the results are obtained. This research has produced the highest accuracy rate of 90.08% in the Naïve Bayes algorithm, with a composition of 90% training data and 10% test data. While the word that often appears in user reviews is "application," with a frequency of 446 occurrences, it is followed by the word "product," 444 times, and the word "price," 312 times. The greater the amount of training data used, the higher the level of accuracy resulting from the Naïve Bayes algorithm. Meanwhile, the greater the amount of test data used, the lower the resulting accuracy value.

Implementation of the Naïve Bayes Method to determine the Level of Consumer Satisfaction Hasibuan, Fitri Febriyani; Dar, Muhammad Halmi; Yanris, Gomal Juni
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12349

Satisfaction is a feeling of pleasure at something you like, you get it from goods and services. Satisfaction becomes an important assessment when someone sells goods or services. This is because satisfaction will be an assessment of the goods purchased by consumers or services that will be received by consumers. Therefore the authors make research about the level of consumer satisfaction in shopping. This research was made using the Naïve Bayes method and used consumer data as sample data which used 49 consumer data. By using the Naïve Bayes method, this study aims to see the level of consumer shopping satisfaction, it is made to see the results of a consumer's satisfaction, sometimes there are some consumers who are dissatisfied with the reason the product is not good and some are satisfied with the reason the product is still new and good. Therefore this research was made. This research was conducted using the naïve Bayes method with the first stage being data analysis, then data preprocessing, then naïve Bayes algorithm and finally system testing. After system testing is carried out, classification results will be obtained using the naïve Bayes method. Classification results stated that as many as 47 consumers were satisfied shopping and as many as 2 consumers were not satisfied shopping. The conclusion is that a lot of consumers are satisfied with shopping, meaning that the place is very good and liked by many consumers.

Analysis of Public Purchase Interest in Yamaha Motorcycles Using the K-Nearest Neighbor Method Triani, Diana Juni; Dar, Muhammad Halmi; Yanris, Gomal Juni
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12433

This data mining will carry out a classification of people who are interested and not interested in buying Yamaha motorcycles. In the data mining process, a method is needed that can provide goals to the data mining process. That's because there are many data mining methods that can be used. In this study the method that will be used by the author is the K-Nearest Neighbor (kNN) method. This method will be used to classify people's buying interest in Yamaha motorbikes. This research was conducted because there are some people who say that Yamaha motorbikes are not good, use of wasteful fuel. Therefore this research was conducted to prove this statement. So a research was made about people's buying interest in Yamaha motorbikes. Classification results obtained from 100 community data. From the classification process that has been carried out, the results show that 41 community data (41% representation) are interested in buying Yamaha motorcycles and 59 community data (59% representation) are not interested in buying Yamaha motorbikes. The results obtained state that there are still many people who are interested in Yamaha motorbikes. But it can be used as a reference that people are interested in motorbikes that have a good appearance, use economical fuel and are affordable. These results were obtained from the community's answers in the questionnaire, they were interested in motorbikes that use little fuel, have good designs and are affordable.

Implementation of the Naïve Bayes Method to Determine Student Interest in Gaming Laptops Nasution, Rico Fadly; Dar, Muhammad Halmi; Nasution, Fitri Aini
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12562

The development of the times resulted in the development of technology to date. With the existence of technology, many people have used technology to help their daily activities. In this study, the author will discuss the technology that is often used by students to help them with their assignments, namely laptops. Laptop is a technology that has been widely used by students, teachers and the public. Having a laptop can make things easier. Until now, each laptop brand continues to develop their laptop production laptops with good specifications. Until now, almost all laptop brands have made gaming laptops that are actually intended for people-people who play games. But with good specifications, gaming laptops can also be used for daily activities. With an attractive design and good specifications, of course you can attract student and public interest in gaming laptops. Therefore the authors made a study of student interest in gaming laptops. With good design and specifications on gaming laptops, the author aims to classify the number of students who are interested and not interested in gaming laptops. The classification will be carried out using the Naïve Bayes method with the number of sample data used as many as 100 student data in data mining. The classification results obtained were 55 students (55% representation) interested in gaming laptops and 45 students (45% representation) had no interest in gaming laptops. The results show that not all students are interested in gaming laptops, even though they have laptops design and great specs.

Penerapan Natural Language Processing dalam Pembuatan Aplikasi Penerjemah Bahasa Melayu Dialek Panai – Bahasa Indonesia Dar, Muhammad Halmi; Hasibuan, Mila Nirmala Sari; Nasution, Fitri Aini
Jurnal Informatika Vol 11, No 3 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i3.5887

The Panai dialect of Malay is the mother tongue used by the speaking community in four sub-districts in Labuhanbatu Regency. The reduced number of native speakers who are skilled in the Panai Malay dialect can threaten the sustainability of this language. Efforts to preserve the Panai Malay dialect must be made to avoid extinction. One way that can be done is to document vocabulary in the form of a translator application. This study aims to create an application translator for the Panai-Indonesian dialect of Malay by applying natural language processing. As for the potential users of this application, they are the people of Labuhanbatu in general, especially those in the four sub-districts previously described. The stages of the research method used were: requirement analysis, design, implementation, testing, and maintenance. This research focuses on technology for improving information and communication technology content in the context of local wisdom (culture and language) in Indonesia. The focus of this research is in line with the Strategic Plan (RENSTRA) of Labuhanbatu University, which covers the fields of information and communication technology and cultural arts. From the results of this study, it is hoped that local wisdom in Labuhanbatu Regency will be maintained as social capital for the resilience of the Indonesian nation.

Analisis Sentimen Ulasan Pengguna Aplikasi pada Google Play Store Menggunakan Algoritma Support Vector Machine Lubis, Sanny Khairani; Dar, Muhammad Halmi; Nasution, Fitri Aini
Jurnal Informatika Vol 11, No 2 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i2.5860

One of the most popular e-commerce sites in Indonesia is Shopee. As the largest marketplace application in Indonesia, Shopee provides product and service review features to users on the Google Play Store. The review feature is very helpful to find out whether user reviews are positive or negative. Having user reviews will help Shopee improve its services. To identify a very large number of user reviews, it is not possible to do it manually by reading them one by one. This process will take a very long time and is not effective. Therefore, we need a method that is able to identify reviews from users more effectively and efficiently. This research aims to conduct sentiment analysis of user reviews of the Shopee application on the Google Play Store by applying the Support Vector Machine algorithm. The research stages carried out started with dataset collection, dataset labeling, preprocessing, TF-IDF weighting, classification, and evaluation. From the research results, accuracy was 70.88%, precision was 49.49%, recall was 52.55%, and F1-score was 49.84%. From these results, it can be concluded that the performance of the support vector machine algorithm in classifying the sentiment of user reviews of the Shopee application on the Google Play Store is quite good.

Implementasi Artificial Intelligence pada Charity Box Masjid dan Musholla sebagai Sistem Keamanan Berbasis RFID Pratiwi, Nurul; Munthe, Ibnu Rasyid; Dar, Muhammad Halmi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 1 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i1.1278

Tingginya angka kriminalitas di Indonesia telah berdampak buruk dan merugikan masyarakat, sehingga berbagai upaya telah dilakukan untuk meningkatkan kesadaran dan keamanan di masyarakat. Pencurian kotak amal adalah target kejahatan bagi penjahat. Untuk itu perlu diambil langkah tegas dalam hal kewaspadaan dan keamanan agar tindak pidana pencurian kotak amal dapat dihindari. Salah satu langkah untuk meningkatkan kesadaran dan keamanan adalah dengan menerapkan konsep keamanan pada kotak amal. Dengan memanfaatkan beberapa sensor pendukung dan komponen pendukung pada kotak zakat maka sistem keamanan akan bekerja secara otomatis, sehingga jika terjadi pencurian kotak zakat maka sistem akan memberikan notifikasi notifikasi SMS kepada pihak pengelola masjid. Penelitian ini difokuskan pada masalah fasilitas keamanan dan pengawasan kotak amal di masjid atau mushalla. Menggunakan sistem ini akan mengurangi resiko pencurian kotak amal di masjid dan mushalla, karena selain dilengkapi dengan alarm dan SMS gateway, sistem ini juga dilengkapi dengan RFID sehingga akses membuka kotak amal bisa lebih aman. Bentuk sistem ini bekerja jika kotak amal diangkat atau dibongkar secara paksa, sistem akan memberikan notifikasi berupa alarm dan SMS, sehingga tindak pidana pencurian kotak amal dapat lebih diwaspadai.

ImplementasiAlgoritma NaÃ¯ve Bayes Classifier (NBC) Untuk Analisis Sentimen Komentar Kebijakan Full Day School Dewi Utami, Yarma Agustya; Sihombing, Volvo; Dar, Muhammad Halmi
MEANS (Media Informasi Analisa dan Sistem) Volume 6 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Sentiment analysis is an important research topic and is currently being developed. Sentiment analysis is carried out to see the opinion or tendency of a person's opinion on a problem or object, whether it tends to have a negative or positive view. The main purpose of this research is to find out public sentiment towards the Full Day school policy comments from the Facebook Page of the Ministry of Education and Culture of the Republic of Indonesia and to determine the performance of the Na-Ã¯ve Bayes Classifier Algorithm. The results of this study indicate that the public's negative sentiment towards the Full Day School policy is higher than positive or neutral sentiment. The highest accuracy value is the NaÃ¯ve Bayes Classifier algorithm with the trigram feature selection of the 300 data training model with a value of 80%. This simulation has proven that the larger the training data and the selection of features used in the NBC Algorithm affect the accuracy of the results. Meanwhile, the simulation results from 10 test data with 5 different NBC and Lexicon algorithms also show that the Full Day School Policy proposed by the Indonesian Minister of Education and Culture has a higher negative sentiment than positive or neutral by most Facebook users who express opinions through comments. The highest accuracy value is the NaÃ¯ve Bayes Classifier algorithm with the trigram feature selection of the 300 data training model with a value of 80%. This simulation has proven that the larger the training data and the selection of features used in the NBC Algorithm affect the accuracy of the results. Meanwhile, the simulation results from 10 test data with 5 different NBC and Lexicon algorithms also show that the Full Day School Policy proposed by the Indonesian Minister of Education and Culture has a higher negative sentiment than positive or neutral by most users. Facebook that expresses opinions through comments. The highest accuracy value is the NaÃ¯ve Bayes Classifier algorithm with the tri-gram feature selection of the 300 data training model with a value of 80%. This simulation has proven that the larger the training data and the selection of features used in the NBC Algorithm affect the accuracy results.

Implementasi Artificial Intelligence pada Charity Box Masjid dan Musholla sebagai Sistem Keamanan Berbasis RFID Pratiwi, Nurul; Munthe, Ibnu Rasyid; Dar, Muhammad Halmi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 1 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Tingginya angka kriminalitas di Indonesia telah berdampak buruk dan merugikan masyarakat, sehingga berbagai upaya telah dilakukan untuk meningkatkan kesadaran dan keamanan di masyarakat. Pencurian kotak amal adalah target kejahatan bagi penjahat. Untuk itu perlu diambil langkah tegas dalam hal kewaspadaan dan keamanan agar tindak pidana pencurian kotak amal dapat dihindari. Salah satu langkah untuk meningkatkan kesadaran dan keamanan adalah dengan menerapkan konsep keamanan pada kotak amal. Dengan memanfaatkan beberapa sensor pendukung dan komponen pendukung pada kotak zakat maka sistem keamanan akan bekerja secara otomatis, sehingga jika terjadi pencurian kotak zakat maka sistem akan memberikan notifikasi notifikasi SMS kepada pihak pengelola masjid. Penelitian ini difokuskan pada masalah fasilitas keamanan dan pengawasan kotak amal di masjid atau mushalla. Menggunakan sistem ini akan mengurangi resiko pencurian kotak amal di masjid dan mushalla, karena selain dilengkapi dengan alarm dan SMS gateway, sistem ini juga dilengkapi dengan RFID sehingga akses membuka kotak amal bisa lebih aman. Bentuk sistem ini bekerja jika kotak amal diangkat atau dibongkar secara paksa, sistem akan memberikan notifikasi berupa alarm dan SMS, sehingga tindak pidana pencurian kotak amal dapat lebih diwaspadai.

Penerapan Data Mining untuk Prediksi Penjualan Produk Sepatu Terlaris Menggunakan Metode Regresi Linier Sederhana Pohan, Doli Alamsah; Dar, Muhammad Halmi; Irmayanti, Irmayanti
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.4795

Prediksi penjualan adalah perkiraan penjualan pada waktu yang akan datang dalam keadaan tertentu dan dibuat berdasarkan data yang telah terjadi. Prediksi ini dipengaruhi oleh penjualan produk di PT.Sepatu Bata. Regresi Linier Sederhana adalah hubungan linier antara satu variabel bebas dengan variabel terikat, analisis ini untuk mengetahui arah hubungan antara variabel bebas dengan variabel terikat apakah positif atau negatif dan untuk memprediksi nilai dari variabel terikat jika nilai variabel bebas mengalami kenaikan atau penurunan. Peneliti akan merancang sebuah sistem implementasi data mining untuk memprediksi penjualan produk sepatu laris agar lebih memanfaatkan data transaksi penjualan yang ada. Perancangan akan diimplementasikan dengan menggunakan bahasa pemrograman PHP dan database MySQL.

Title

Found 30 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 30 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 30 Documents
Search