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All Journal AMMA : Jurnal Pengabdian Masyarakat Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Ahya Mahfuzi
UNIVERSITAS PAMULANG
Humanities Chemistry Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Pengenalan Microsoft Word Pada Usia Dini Kepada Yayasan Roemah Tawon Muhammad Faisal; Ahya Mahfuzi; Nisan Yedidiya Sorayana Mendrofa; Azis Saputro; Muzakki Hafizh; Muhammad Ikhwal; Annis Syifa; Rizky Prasetyo; Muhammad Yusuf; Abdul Majid; Perani Rosyani
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 09 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Manage data and store information (data storage) practically and efficiently. In today's digital era, computer-based information and communication technology has influenced various aspects of life, including education, it is undeniable. This community service activity aims to provide assistance to participants of the ROEMAH TAWON Foundation in applying Microsoft Word. With this activity, it is hoped that it will make it easier for students to do word processing and make useful presentation media to facilitate the learning process. The method used in an effort to achieve the planned target or goal is the explanation of the material, practice (performance) and question and answer. The trainees are divided into groups. Each group was accompanied by one of the university students. To find out the success of the program activities that have been carried out, an evaluation is carried out. Evaluation is done by giving practical exams to determine the level of understanding of students regarding the material and training that has been provided. The conclusion of this activity is that community service has succeeded in increasing students' knowledge in the application of Microsoft Word. The students of the ROEMAH TAWON Foundation felt helped by the training that was carried out so that they could use computers or laptops in doing school assignments well, such as making papers to facilitate activities. Students gave a very positive response to the activities carried out and considered this activity very useful
Analisa Prediksi Harga Saham Bank BRI Berdasarkan Data Historis Menggunakan Algoritma Random Forest Ahya Mahfuzi; Munawaroh Munawaroh
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 6 No. 1 (2026): Maret : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v6i1.10865

Abstract

Abstract. Stock price fluctuations are complex and play a crucial role in investment decision-making. Bank Rakyat Indonesia (BRI) shares, as one of the largest banking institutions in Indonesia, often reflect national economic conditions. Conventional approaches such as fundamental and technical analysis have limitations in capturing the non-linear patterns inherent in time-series stock price data. Therefore, this study aims to analyze the capability of the Random Forest algorithm in modeling Bank BRI stock prices based on historical data and to evaluate the accuracy of the resulting prediction model. This research utilizes one year of historical Bank BRI stock price data, consisting of 301 observations, with variables including Open, High, Low, Close, Adjusted Close, and Volume. The model was developed using the Random Forest algorithm with 200 estimators and no maximum tree depth, implemented using the PHP programming language. The dataset was divided into 80% training data and 20% testing data. The experimental results indicate that the Random Forest algorithm is capable of effectively modeling Bank BRI stock price patterns and adequately following actual price trends. Model evaluation produced a Mean Absolute Error (MAE) of Rp 155.0986 and a Root Mean Square Error (RMSE) of Rp 193.1669, with an average prediction error of Rp 155.1005. Most predictions from the 60 testing data points exhibited an error rate below 2%, indicating satisfactory predictive accuracy. These findings demonstrate that the Random Forest algorithm can effectively represent fluctuations in Bank BRI stock prices based on historical data and serve as a foundation for future stock price forecasting reasearch.
Co-Authors Abdul Majid Annis Syifa Azis Saputro Muhammad Faisal Muhammad Ikhwal Muhammad Yusuf Munawaroh Munawaroh Muzakki Hafizh Nisan Yedidiya Sorayana Mendrofa Perani Rosyani Rizky Prasetyo