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All Journal Jurnal Manajemen dan Bisnis Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer
Rizki Adi Saputra
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Computer Science & IT Economics, Econometrics & Finance Social Sciences Other

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Hubungan Kausalitas Antara Nilai Tukar dengan Harga Saham dan Inflasi di Indonesia Rizki Adi Saputra; D. Agus Harjito
Jurnal Manajemen dan Bisnis Indonesia Vol 3 No 1 (2015): Jurnal Manajemen Bisnis Indonesia - Edisi Oktober 2015
Publisher : Forum Manajemen Indonesia (FMI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31843/jmbi.v3i1.70

Abstract

Penelitian ini bertujuan untuk menganalisis hubungan kausalitas dan kointegrasi antara nilai tukar rupiah terhadap dollar Amerika dengan IHSG dan nilai tukar tersebut dengan inflasi. Penelitian ini menggunakan data bulanan periode Januari 2003-Desember 2013, data diperoleh dari Bank Indonesia (BI) dan Badan Pusat Statistik (BPS). Alat analisis menggunakan uji kausalitas Engel-Granger untuk mengetahui hubungan sebab akibat (kausalitas) dan uji kointegrasi untuk mengetahui hubungan keseimbangan jangka panjang. Hasil penelitian menggunakan uji kausalitas Granger menunjukkan bahwa nilai tukar memiliki hubungan kausalitas dengan indeks harga saham gabungan (IHSG), sedangkan Uji kointegrasi menunjukkan adanya hubungan jangka panjang antara nilai tukar dan harga saham untuk periode Januari 2003 sampai Desember 2013. Hasil penelitian lain dari uji kausalitas Granger menunjukkan bahwa terjadi hubungan kausalitas antara nilai tukar dengan inflasi, dan dari uji kointegrasi menunjukkan adanya hubungan jangka panjang untuk periode Januari 2003 - Desember 2013. Kata kunci: Nilai Tukar , IHSG, Inflasi, Kausalitas Granger
Analisis Sentimen Aplikasi Tokocrypto Berdasarkan Ulasan Pada Google Play Store Menggunakan Metode Naïve Bayes Rizki Adi Saputra; Dion Parisda Ray; Faldy Irwiensyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1707

Abstract

The advancement of increasingly sophisticated technology has brought numerous changes and conveniences for humans in all aspects, including the financial sector. Cryptocurrency has emerged as an innovation in the financial world. A cryptocurrency exchange is an electronic platform that enables sellers and buyers to conduct cryptocurrency trading transactions through a website or mobile application. Currently, many cryptocurrency exchange applications suffer from poor service, unreliable security, lengthy withdrawal processes, high administrative fees, and other issues. As a result, many people in Indonesia rely on reviews on the Google Play Store to check user feedback before deciding to use these cryptocurrency exchange applications. Many Indonesians seek information on cryptocurrency exchange applications that provide the best services for buying and selling cryptocurrency. One such application, according to reviews on the Google Play Store, is Tokocrypto. This study aims to understand the sentiment towards user reviews of the Tokocrypto application using the Naïve Bayes algorithm for data classification. The data obtained consists of 2,000 reviews from the Google Play Store in February 2024, collected using Google Colaboratory. The research stages include data scraping using web scraping techniques, data labeling, preprocessing, TF-IDF weighting, implementing the Naïve Bayes algorithm, and evaluation. The cleaned data resulted in 1,000 reviews, with 396 positive sentiments and 604 negative sentiments. The results of sentiment analysis research using the Naïve Bayes algorithm method show 74.22% for accuracy, 63.25% for precision, and 81.40% for recall.
Analisis Sentimen Ulasan Aplikasi Samsat Digital Nasional Pada Google Playstore Menggunakan Algoritma Naïve Bayes Deni Wijaya; Rizki Adi Saputra; Faldy Irwiensyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1738

Abstract

Digital transformation has become a major factor of change in various aspects of modern life, including business, education, and government. In the current era of digital transformation, the government is trying to improve efficiency and services to the community through the implementation of various technological innovations. The application of digital technology in public services is increasingly widespread, including in the administrative service sector such as the National Digital Samsat (SIGNAL) which allows people to make online vehicle tax payments through the SIGNAL application. User evaluations of this application can provide important insights for service providers. This research aims to analyze the sentiment of user reviews of the National Digital Samsat application on the Google Playstore platform using the Naïve Bayes algorithm. This method is used to classify user reviews into positive and negative sentiment categories. From 2000 reviews taken, 1,665 reviews were categorized as positive and 335 reviews as negative after manual labeling. Data preprocessing using RapidMiner includes cleaning, transform cases, tokenizing, stopword filter, token by length filter, and stemming. TF-IDF weighting is used to give weight to each word in the document. Evaluation of the Naïve Bayes model resulted in an accuracy of 63.61%, with 307 True Positives, 74 True Negatives, 26 False Positives, and 192 False Negatives. Precision was 92.19% and recall was 61.52%. The overall analysis shows that user reviews tend to be more positive towards the SIGNAL app, although there are some negative reviews. This conclusion gives an idea of users' positive perception of the app
Analisis Sentimen Pada Ulasan Pengguna Aplikasi Streaming Vidio Menggunakan Metode Naïve Bayes Muhammad Yusuf Siregar; Ade Davy Wiranata; Rizki Adi Saputra
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 5 (2024): April 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i5.1787

Abstract

The The development of information technology innovation has a positive impact on the media and entertainment industry, especially in the significant use of online streaming services. Vidio is one of the most popular streaming applications, providing interesting features such as watching, uploading, and sharing videos in mobile format for smartphones, tablets, and smart TVs. Vidio's strength is its ability to show live television from various channels in Indonesia. Although the Vidio app offers interesting features and ease of use, not all users are guaranteed to be satisfied. Each app has its own advantages and disadvantages, so users' experiences and views may vary. This can be seen from the user reviews available on the Google Play Store. This research aims to analyze the sentiment of user reviews of the Vidio application using the Naïve Bayes algorithm. The data used in this research are 1500 reviews collected in February 2024. After going through the data cleaning stage, the number was reduced to 1475 review data. From the available dataset, there are 165 positive reviews and 1310 negative reviews. The research process includes data retrieval using web scraping technique, data labeling, preprocessing, and TF-IDF weighting before the classification stage. For classification, cross validation technique and Naïve Bayes method were used. The results showed that the accuracy achieved by the Naïve Bayes algorithm was 80.28%, precision 24.18%, and recall 35.76%.
Co-Authors Ade Davy Wiranata D. Agus Harjito Arif Singapurwoko Deni Wijaya Dion Parisda Ray Faldy Irwiensyah Muhammad Yusuf Siregar