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Optimizing Investment: Combining Deep Learning for Price Prediction and Moving Average for Return-Risk Analysis Hastomo, Widi; Karno, Adhitio Satyo Bayangkari; Masriyanda, Masriyanda; Sestri, Ellya; Kardian, Aqwam Rosadi; Azis, Nur; Dewanto, Ignatius Joko; Rasyiddin, Ahmad; Sundoro, Aries; Kamilia, Nada
Jurnal Teknik Elektro Vol 14, No 2 (2022): Jurnal Teknik Elektro
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jte.v14i2.45002

Abstract

The ability to analyze predictions marks something going up or down, as well as the level of possible risk taken into account by much-needed stock investors. In a study, this analysis of risk and correlation between shares was calculated using the method of moving averages (MA). Besides that, a dataset of 4 stocks (Apple, Google, Microsoft, and Amazon) also performed prediction mark stock in period time next (future) with the use of the neural network method (deep learning) Long Short-Term Memory (LSTM) model. The result of programming in the Python language is several visualizations for easy graph-reading information. This article presents new research that aims to fill the gap in understanding investment analysis for beginners by visualizing risk and return analysis on shares. The results reveal that changes in stock sales volume did not occur significantly, although the short and long-term MA charts for the four stocks tended to fluctuate, offering new insights into investment analysis and providing a basis for future development. The best accuracy results were on MSFT shares, with an achievement of 0.9532 and a loss value of 0.0014. Thus, MSFT shares can be used as a priority for investment. Therefore, this research adds a new dimension to the literature and paves the way for further investigations in risk and return analysis and stock prediction using deep learning.
Pemanfaatan RinfoForm Sebagai Media Pengumpulan Data Kinerja Dosen Handayani, Indri; Dewanto, Ignatius Joko; Andriani, Dina
Technomedia Journal Vol 2 No 2 Februari (2018): Technomedia Journal
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.287 KB) | DOI: 10.33050/tmj.v2i2.321

Abstract

Teknologi informasi yang berkembang begitu pesat sehingga setiap Perguruan Tinggi senantiasa bersaing dalam kegiatan penelitian yang dilakukan oleh peneliti dan dosen. Salah satunya Perguruan Tinggi Raharja yang bergerak dibidang komputer. Perguruan Tinggi Raharja yang memiliki banyak inovasi untuk menciptakan media pengumpulan data kinerja dosen yang tidak konvensional. Untuk itu dibuatlah sebuah media informasi yang dijadikan sebagai media dalam pengumpulan data dosen yang ada di Perguruan Tinggi Raharja. Kinerja Penelitian dan Kinerja Pengabdian kepada Masyarakat yang merupakan sebagai bagian dari Tri Dharma Perguruan Tinggi Raharja yaitu pusat bagi Perguruan Tinggi dalam pengembangan Ilmu Pengetahuan , Teknologi, dan IPTEKS. Dalam implementasinya saat ini masih kurang efektif yaitu dalam pengumpulan data kinerja dosen. Hal ini masih terlihat pada saat ingin menginput data dosen, dosen harus datang ke ruangan Rahaja Enrichment Centre (REC). Maka dari itu pastinya saat ini mayoritas pasti memiliki email. Dikarenakan email merupakan salah satu media yang paling aman, dengan email mudah sekali dalam bertukar file atau dalam hal yang lainnya. Dan pastinya akan memanfaatkan fasilitas yang ada pada email. salah satunya yang terdapat pada gmail adalah Google Form. Google Form ini memiliki fungsi yaitu untuk membuat formulir pendaftaran dan untuk membuat daftar - daftar lain yang kemudian dengan cara meminta kepada seseorang untuk mengisi formulir yang telah dibuat sesuai dengan ketentuan yang ada. Akan tetapi pada Perguruan Tinggi Raharja ini lebih dikenal sebagai Rinfo Form. Dengan melalui Rinfo Form ini diketahui dapat menutupi kekurangan yang berpengaruh dalam pengumpulan data kinerja dosen tersebut. Dalam penelitian ini dilakukan dengan menggunakan metode pengumpulan data, diantaranya yaitu metode observasi dan metode studi pustaka. Peneliti berharap dengan pemanfaatan Rinfo Form memberikan pengaruh baik dalam pengumpulan data kinerja dosen di Perguruan Tinggi Raharja. Kata kunci : Teknologi informasi, Data, RinfoForms Information technology is growing very rapidly so that every university is always competing in research activities undertaken by researchers and lecturers. One of them is Perguruan Tinggi Raharja which is engaged in computer. Perguruan Tinggi Raharja has many innovations to create unconventional lecturer data performance data collection. For that made a media information that serve as a medium in the data collection of lecturers in Perguruan Tinggi Raharja. Performance Research and Performance Devotion to the Society which is a part of Tri Dharma Perguruan Tinggi Raharja is the center for Universities in the development of Science, Technology, and IPTEKS. In the current implementation is still less effective in the collection of lecturer performance data. It is still visible at the time to enter the data of lecturers, lecturers must come to the room Raharja Enrichment CentRE (REC). Therefore of course now majority must have mail. Because email is one of the most secure media, with very easy email in exchange files or in other things. And certainly will take advantage of existing facilities on mail. One of which is in gmail is Google Form. This Google Form has a function that is to create other lists later by asking someone to fill out form that has been created in accordance with the existing provisions. However, in Perguruan Tinggi Raharja is better known as Rinfo From. By through Rinfo Form is known to cover the inadequate deficiencies in the collection of lecturer performance data. In this research is done by using data collection method, such us observation method, and literature review. Researchers hope by utilizing Rinfo Form give good influence in data performance data at Perguruan Tinggi Raharja. Keywords : Information technology, Data, RinfoForms
Analysis of Covid 19 Data in Indonesia Using Supervised Emerging Patterns Rahardja, Untung; Dewanto, Ignatius Joko; Djajadi, Arko; Candra, Ariya Panndhitthana; Hardini, Marviola
APTISI Transactions on Management (ATM) Vol 6 No 1 (2022): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v6i1.1768

Abstract

This research method uses CRISP-DM with emerging pattern supervision modeling and EPM Algorithm. The contribution of the research is to assist the Government in overcoming the problem of the spread of the COVID-19 cluster in several regions in Indonesia. The research aims to implement information on the COVID-19 data mining pattern in the DKI Jakarta area. The problems faced are the difficulty of identifying the pattern of COVID-19 data in one area, it is difficult to dig up data on the http://corona.jakarta.go.id website. It is not easy to decide on the handling of COVID-19. The output of the research results in a cluster of information on COVID-19 in the DKI Jakarta area based on Significance level depends on the Covid Map In terms of Region, Status, Gender, & age And Signification can be the basis for determining covid OTG, DTG, and Positive. The theoretical and practical implications can be stated as follows: The use of supervised emerging pattern methods can affect the processing of COVID-19 data. For 5 Regions in DKI Jakarta and distribution to determine covid OTG, DTG, and Positive. The result of the development of this data mining system is to produce pattern reports to produce Supervised Emerging Patterns technology for decision making at the COVID-19 Task Force in DKI Jakarta.
Model Penilaiann Kinerja Karyawan dengan Personal Balanced Scorecard: (Studi Kasus Universitas Tangerang Raya) Nur Aziz; Dewanto, Ignatius Joko
MAMEN: Jurnal Manajemen Vol. 1 No. 2 (2022): April 2022
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (354.828 KB) | DOI: 10.55123/mamen.v1i2.218

Abstract

Employee performance is assessed through superiors, subordinates and co-workers. Work performance or employee performance can later be used to determine employee policies in improving their performance in the future. The Personal Balanced Scorecard (PBSC) describes employees in four areas, namely: internal, external, skills and learning, and finance. By applying this method can help the managerial for the purposes of assessing its employees objectively.