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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) ROUTERS: Jurnal Sistem dan Teknologi Informasi
Tyas, Putri Cahyaning
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science

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Dampak Berita Emas Palsu Terhadap Harga Saham PT Aneka Tambang TBK (ANTM): Analisis dan Prediksi) Ispaniyah, Ispaniyah; Tyas, Putri Cahyaning; Suseno, Akrim Teguh; Wulandari, Umi Meganinditya
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 1, Februari 2025
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i1.3969

Abstract

Fake news or hoaxes, have become a major problem around the world in recent years. This phenomenon not only affects public opinion but can also affect various aspects of socio-economic life, including financial markets. Currently, global stock prices continue to rise and have reached their highest level since 2012-2013. One of the leading mining companies in Indonesia, PT Aneka Tambang Tbk (ANTM), is not entirely dependent on its share price. The impact of fake news on stock prices has become a topic of growing interest in the academic literature. Various previous studies have attempted to identify the relationship between the spread of fake news and stock price fluctuations. Using the RapidMiner application, an analysis of PT ANTM's stock price prediction was conducted using Neural Network (NN) and Linear Regression (LR) algorithms. To assess the accuracy of the prediction, the analysis is performed using the Root Mean Square Error (RMSE) results. The comparative analysis conducted shows that the Neural Network algorithm has a lower error rate of 14,806 +/- 0.000 compared to the Linear Regression algorithm which has a value of 22,379 +/- 0.000. This shows that the Neural Network algorithm has higher accuracy in predicting the share price of PT ANTM. A smaller RMSE value indicates a more accurate prediction. In addition, this study also identified that the time span of the data used (December 19, 2023 - June 19, 2024) can affect the prediction results. Based on the conclusions, the researcher suggests that using a dataset with a longer time span and applying other Deep Learning algorithms to improve prediction accuracy can be used for future research.
Implementasi Firebase Cloud Messaging untuk Meningkatkan Efisiensi Pencatatan Keuangan pada Aplikasi Android SmartMoney Tyas, Putri Cahyaning; Anshori, Arif Iman; Naufal, Abdul Razak
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8560

Abstract

Personal money management is often overlooked by most people, irregular financial management often results in a mismatch between income and expenses, thus triggering uncontrolled spending. This study ims to improve the efficiency of user habits in recording finances by implementing a reminder (notification) feature using Firebase Cloud Messaging (FCM) on the SmartMoney application. The data collection method for this study uses questionnaires and research, based on an initial survey conducted by distributing questionnaires, as many as 73% of them rarely record transactions because they forget and feel the manual recording process is inefficient. The SmartMoney application development process uses the Incremental Development method, Meanwhile, functional testing was conducted using the Black Box Testing method to check the extent to which reminder messages were successfully received under various application usage conditions. Testing was carried out 10 times per device for a total of 30 trials. The test results showed that notification messages were successfully delivered 95% of the 30 trials, whether the application was running in the foreground, background, or had been completely closed. The implementation of FCM has proven effective in providing transaction information directly to users (Killed). Therefore, this study shows that the implementation of Firebase Cloud Messaging (FCM) is able to create effective and consistent push notification (Notification Reminder) feature for users so that it can increase the efficiency of more orderly financial recording.
Co-Authors Abdul Razak Naufal Anshori, Arif Iman Ispaniyah, Ispaniyah Suseno, Akrim Teguh Wulandari, Umi Meganinditya