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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,127 Documents
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Meta-Analysis: Inquiry-Based Learning Model in Improving Student Academic Achievement Fitri Rahmadani, Ade; Syafrijon; Jalinus, Nizwardi; Ridwan; Rijal Abdullah; Nurhasan Syah
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3934

Abstract

The purpose of this study is to re-analyze the application of inquiry learning models to improve student academic achievement. Meta-analysis is the type of research in this article. The research stage begins with formulating research problems, the next stage is continued by analyzing research data in accordance with the inquiry learning model. In the process of data collection apply non-test techniques wheresearching for articles contained in electronic journals using the Google Scholar site. 25 scientific articles were obtained from various articles both national and international found based on the inquiry model. In accordance with the results of data analysis, it was obtained that in applying the inquiry learning model in the learning process, there was an increase in student academic achievement. This is evidenced by the lowest value data obtained with a percentage of 3.05% to the highest value with a percentage of 50.99% so that an average of 17.66% is obtained. Then based on the calculation of the effect size of 25 articles used as references, the average effect size value of 7.33% was obtained. From this effect size value, it can be seen that the influence of the inquiry learning model has a very high influence on increasing student academic achievement.
An Effectiveness of Using Inquiry-Based Learning Models on Student Learning Outcomes: Meta Analysis Putri, Yuzia Eka
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3935

Abstract

This research analyzes the effectiveness of using an inquiry-based learning model on student learning outcomes. The inquiry learning model has five important principles that must be considered in the learning process, namely oriented towards intellectual development, the principle of interaction, the principle of asking, the principle of learning to think and the principle of openness. The data in this research consists of 21 articles. Data obtained from research results that have been published in national and international journals sourced from Google Schoolar, and SINTA with a publication period of 2018-2023. The requirements for selecting articles are 1) the article has research data 2) the research must be experimental or quasi-experimental 3) the article has supporting data to calculate the effect size. Data analysis using the JASP application. The results of data analysis show that the average effect size value is in the high category, namely 1.60. This shows that the inquiry learning model is effective in improving student learning outcomes
Sistem Informasi Harga Bahan Pokok Dinas Perdagangan dan Perindustrian Kota Palu Nursalim, Moh. Agung; Chairunnisa Ar Lamasitudju; Miftah; Wirdayanti; Mohammad Yazdi Pusadan; Rahmah Laila
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3937

Abstract

Pasar tradisional Indonesia sangat penting bagi perekonomian, terutama bagi pedagang kecil dan komunitas yang bergantung pada perdagangan sebagai sumber pendapatan mereka. Namun, masalah seperti pergeseran demografi, kemajuan teknologi, dan kurangnya transparansi harga telah mengganggu stabilitas pasar tradisional. Artikel ini menunjukkan betapa pentingnya sistem informasi harga bahan pokok untuk mengelola harga dan mencegah inflasi. Studi ini bertujuan untuk membangun sistem informasi yang disebut GadeMart yang akan melacak perubahan harga di dua pasar tradisional terbesar Kota Palu: Pasar Inpres Manonda dan Pasar Masomba. Diharapkan bahwa penelitian ini akan menawarkan solusi untuk meningkatkan stabilitas ekonomi dan transparansi harga di pasar tradisional.
A META ANALISIS : EFEKTIVITS METODE PEMBELAJARAN BLANDED LEARNING TERHADAP CAPAIAN KOGNITIF SISWA DI ERA DIGITALISASI Firmansyah Putra
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3938

Abstract

This research aims to discuss the effectiveness of the Blended Learning learning method on student learning outcomes. This research is a meta-analysis research using secondary data. The data obtained is in the form of post test results for the experimental class and control class from articles that apply blender learning. The number of articles used in this meta analysis was 15 articles. The data that has been successfully filtered is then calculated using the effect size (ES) formula. The calculation results show that learning using the blended learning method can also improve student learning outcomes. It can be concluded that learning using the blended learning method has a high level of effectiveness and is appropriate for student learning outcomes.
Migration Success Strategy and Implementation of Enterprise System: A Case Study on PT XYZ Biller Message Switching and Aggregator Service Merger Work From Home Oristania Wahyu Nabasya
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3939

Abstract

Purpose – The purpose of the research is to determine the strategy for the successful implementation of Biller Message Switching and Aggregator carried out by organizations with multicultural employees during work from home conditions. Methodology – The method used in this research was a summative evaluation with the research subjects of the merger of Bank X, Bank Y, and Bank Z. Research subjects were chosen because of the success of the development team in integrating enterprise systems to support the merger process carried out during the pandemic. Results – The results of the research concluded that the ES implementation strategy during the pandemic required consistency, actively documenting each process, over-communicating, and using the appropriate SDLC method. Originality – This research conducted a thematic analysis on the process of integrating and migrating ES companies that merged during the pandemic. Contribution – This research contributes to organizations that want to integrate and migrate ES during the pandemic. For academics, research can serve as a foundation for future research in developing theories of ES implementation in virtual or pandemic environments.
The Performance Analysis of Graph Neural Network (GNN) and Convolutional Neural Network (CNN) Algorithms for Cyberbullying Detection in Twitter Comments Muhammad Rizki Nurfiqri; Fitriyani
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3940

Abstract

Cyberbullying incidents have surged due to the expansion of social media network and advancements in internet technology, presenting a substantial challenge in online communities. Previous studies employing Support Vector Machine (SVM) techniques have exhibited promising outcomes, achieving a superior accuracy of 71.25%. However, recognizing the dynamic nature of cyberbullying behaviors and the necessity for more robust detection methodologies, this research explores cyberbullying detection on Twitter utilizing Convolutional Neural Network (CNN) and Graph Neural Network (GNN). The selection of CNN and GNN is motivated by the deficiencies observed in prior SVM-based approaches and the capacity of neural network to capture intricate patterns in textual and network data. The GNN consistently outperforms CNN in terms of F1 score, accuracy, precision, and recall. With only 20 epochs, GNN achieves an accuracy of 80.25%, surpassing CNN's 68.43%. Through GNN optimization, its accuracy reaches 89.04% after 100 epochs, underscoring its efficacy in Twitter cyberbullying detection.
Deep Learning based Channel Estimation and Hybrid Beamforming for 5G Massive MIMO Wireless Communications Tun, Thwe Zin; Lwin, Zin Mar; Hla, Tin Tin
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3941

Abstract

Hybrid beamforming (BF), which divides beamforming operation into radio frequency (RF) and baseband (BB) domains, will play a critical role in MIMO communication at millimeter-wave(mmWave) frequencies. This paper also introduce offline training and prediction schemes for channel estimation and hybrid beamforming. The aim of this paper is that to increase spectral efficiency over more data streams by leveraging the deep learning based LSTM network. The LSTM network is used to train the numeric values from sequence data and predict on new sequence data. The performance is evaluated under different parameters including number of data streams (1, 2, 3 and 4) with different signal-to-noise ratio (SNR) for different carrier frequencies (28GHz, 38GHz, 60GHz and 73GHz) through computer simulation using MATLAB. The simulation results verified that the proposed method can achieve higher spectral efficiency when the number of data streams increases and the value of SNR-Test increases too.
PERBANDINGAN AKURASI LINEAR REGRESSION DAN SUPPORT VECTOR REGRESSION DALAM PREDIKSI SUHU RATA-RATA Lesnusa, Gideon Namlea; Dwi Shinta Angreni; Ardiansyah, Rizka
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3944

Abstract

The weather in Indonesia varies significantly and is influenced by geographical location, topography, and regional climate. Weather patterns differ between the western and eastern parts of Indonesia. This study explores time series models to predict weather data in Palu City, a region that is complex due to various weather factors. The focus is on the unique weather patterns reflected by the geography and topography of Palu City. Evaluation was conducted on time series models, including Linear Regression and Support Vector Regression (SVR), to estimate weather conditions in Palu City. The evaluation results show that the SVR model has an RMSE of 0.6302, while linear regression has an RMSE of 0.6328. This research has the potential to improve early warning and decision-making regarding extreme weather
Fake News in Social Network: A Comprehensive Review Omar, Mohamed Rasheed; Abdulazeez, Adnan
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3945

Abstract

Fake news has become a significant challenge in the digital age, evolving from its historical roots in traditional media to becoming a pervasive issue on social media platforms. This paper presents a comprehensive review of the scope and mechanisms of fake news propagation in the digital era, focusing specifically on social media. It examines the historical development of fake news and assesses the effectiveness of current detection methods. Various aspects of fake news, including its spread and the associated challenges, are explored through a detailed methodological approach that integrates both technological and sociological strategies. The goal is to enhance the accuracy of detection methods and mitigate the impact of fake news. This review aims to synthesize existing paper, identify gaps in the current knowledge, and recommend directions for future paper, ultimately seeking to protect public discourse and maintain the integrity of information in the digital landscape.
A Meta Analisis Pengaruh Model PjBL terhadap Kemampuan Berpikir Kreatif Peserta Didik Widyastuti, Rini; Jalinus, Nizwardi; Ridwan; Abdullah, Rijal; Krismadinata
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3946

Abstract

The Project Based Learning (PjBL) model is a learning strategy where students work on projects that help solve community/environmental problems. The ability to think at a higher level is a life skill that students must develop to face the challenges of life in the 21st century. One of the abilities at a high level is the ability to think creatively. The aim of this research is to analyze the effect of project-based learning on creative thinking skills. This research method is meta-analysis using a sample of 16 articles from various article sources. The research was conducted using quantitative methods using the OpenMEE application as a measure of effect size. The results of the meta-analysis show that the application of the PjBL model significantly influences students' creative thinking abilities as seen from various subjects and levels of education, from elementary school to college. The average effect size results are in the very high category, which means that the application of the PjBL model in learning influences creative thinking abilities

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