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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 1,170 Documents
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Investigating of Signal Propagation Characteristics in a Realistic Rural Scenario using Verified Tools: A Case of South Chunya-Tanzania Yamakili, Pascal; Nicholaus, Mrindoko
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3853

Abstract

Effective radio network planning requires understanding an area's radio propagation characteristics. This investigation uses dependable techniques to examine the movement of wireless signals in Tanzania's rural locations. Propagation characteristics in selected rural Tanzanian communities (South Chunya) are examined as a case study, and recommendations are made based on the findings, particularly for wireless service providers or researchers looking to improve wireless connectivity in rural communities. Important radio parameters such as Pathloss, Signal to Noise ratio, Bandwidth throughput, Spectral efficiency and Spectral band were examined. This was done after simulating signal transmission from the Base station transmitter to the Base station receiver and observing power and attenuation. Their corresponding results are discussed and evaluated. The general observation of the pass loss results for both operating frequencies 800MHz and 2000MHz have shown that only few areas are experiencing strong signal after initial signal power transmission, large areas served by these macro sites are experiencing huge path loss. This is evidently affected by the terrain of an area and the carrier frequency of operators.
A Meta-Analysis of the Problem-Based Learning Model to Enhance Students' Creative Thinking Skills Elsa Sabrina; Maksum, Hasan; Waskito
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3854

Abstract

This study aims to investigate the influence of the Problem Based Learning (PBL) model on enhancing students' creative thinking skills. Meta-analysis method was employed to collect and analyze data from 17 relevant articles published in online journals between 2018 and 2023. The analysis results indicate that the implementation of the PBL model has a significant impact on enhancing students' creative thinking skills, with an effect size value of 0.40 categorized as a moderate effect. The implications of these findings underscore the importance of integrating the PBL model into educational approaches to facilitate the development of students' creative thinking skills in various educational contexts.
Evaluasi Manajemen Data Warehouse & Business Intelligence Menggunakan CMMI Pada E-Commerce XYZ Stella Gabriella Apriliani
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3856

Abstract

PT. XYZ, perusahaan e-commerce Indonesia, mengalami tantangan dalam mengintegrasikan data dari berbagai sumber ke dalam data warehouse, termasuk masalah duplikasi data yang menghabiskan banyak waktu dan usaha untuk mencapai data berkualitas. Hal ini berdampak pada lama waktu penyajian laporan ke Dewan Direksi yang bisa mencapai satu bulan tanpa hambatan berarti. Penelitian ini bertujuan untuk meningkatkan manajemen data warehouse dan business intelligence (DW-BI) dengan harapan menciptakan single source of truth yang efektif untuk kebutuhan manajemen pada tahun 2022. Menggunakan metode Capability Maturity Model Integration (CMMI) dan rekomendasi berbasis DAMA-DMBOK, penelitian ini berambisi mengangkat maturity level DW-BI e-commerce XYZ ke level 3. Hasilnya, tiga sub-aktivitas berada pada level 2 sementara empat lainnya telah mencapai level 3. Dengan rekomendasi yang ditargetkan pada sub-aktivitas level 2, penelitian ini berusaha mengatasi permasalahan integrasi data, mengoptimalkan manajemen DW-BI di PT. XYZ.
Unveiling the Benefits and Challenges of Test-Driven Development in Agile: A Systematic Literature Review Tampubolon, Sabar Maruba; Raharjo, Teguh
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3857

Abstract

The adoption of Test-Driven Development (TDD) in Agile software development prompts extensive discussion. Advocates highlight its benefits, while skeptics question empirical evidence. This study investigates TDD in Agile settings, examining its merits and challenges. Conducting a systematic literature review, it synthesizes insights from scholarly and industry sources. Results indicate TDD aids development, aligns with Agile practices, and enhances product delivery. Yet, challenges include procedural complexity and skill requirements. Proficiency in Agile practices like refactoring and unit testing is essential. TDD's impact on productivity is moderate and can be counterproductive. This research contributes new perspectives on TDD and Agile development, benefiting academia and informing practitioners for informed decision-making.
A Review of Bitcoin Price Prediction Based on Deep Learning Algorithms Tayib, Hanaa; M. Abdulazeez, Adnan
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3858

Abstract

This study provides a comprehensive analysis of the existing body of work on predicting the price of Bitcoin using deep learning techniques. It discusses the fundamental concepts behind deep learning and Bitcoin, including recurrent neural networks, convolutional neural networks, and long short-term memory networks. The study also examines the data sources used in training these models, including historical Blockchain transaction data, social media sentiments, and Bitcoin prices. The report also highlights the importance of metrics like mean absolute error, mean squared error, and root mean squared error for evaluating the effectiveness of various models. It also discusses future research topics, such as incorporating external factors into prediction models. The article offers valuable insights for academics, practitioners, and policymakers interested in cryptocurrency prediction.
Analisis Dinamika Tren Otoritas Keagamaan: Studi Kasus di Twitter Indonesia Tahun 2009-2019 Naila Nabiha Qonita; Taufik Edy Sutanto; Nur Inayah
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3862

Abstract

Religious authority refers to individuals vested with governance over religious matters, such as kiai, ulama, and ustaz within the context of Islamic faith. In the age of social media, where freedom of expression prevails, anyone can initiate discussions on various topics, including religion. However, this freedom often raises doubts about truthfulness or validity of opinions concerning religious topics because not all information originates from credible religious authorities. This study analyzes trend dynamics of religious authority in discussions about Islam on Twitter between 2009 and 2019, using Katz centrality and Laplacian centrality. According to both methods, the findings indicate that dominance in religious conversations tends not to be held by religious authorities, with the average percentage of religious authority appearances only 14.24% in Katz centrality and 12.42% in Laplacian centrality. Results of this study are intended to serve as reference for government policy-making related to religious moderation education to public.
The Effect of Blended Learning on Students' Creative Thinking Ability: A Meta-Analysis Sisrayanti; Ambiyar; Wulansari, Rizky Ema; Sabrina, Elsa
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3866

Abstract

This study aims to investigate the influence of technology-based learning, particularly blended learning, on students' creative thinking abilities. Through quantitative analysis, data comprising sample size, mean, and standard deviation extracted from Google Scholar indexed journals were examined. Employing a group contrast analysis design with a random effects model, effect sizes were corrected using JASP software. The analysis revealed a summary effect of 6.74 with a confidence interval ranging from 4.68 to 8.80, indicating a significant difference between groups utilizing blended learning and those employing conventional methods. Notably, students engaged in blended learning exhibited superior creative thinking skills compared to their counterparts. These findings underscore the pressing need to integrate blended learning methodologies to enhance the learning process effectively.
Enhancing Problem-Solving Learning Models: A Review from the Lens of Independent Learning in the Post-Pandemic Era Elsa Sabrina; Ambiyar; Wulansari, Rizky Ema
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3868

Abstract

This research aims to explore the optimization of the problem-solving learning model within the context of independent learning in the post-pandemic era. Utilizing a systematic literature review method and the PRISMA model, the study identifies 25 pertinent articles concerning the implementation of the problem-solving learning model in independent learning. The analysis indicates that applying this model positively impacts students' critical thinking abilities, enhances creativity, and reinforces communication and collaboration skills. From an independent learning standpoint, the problem-solving learning model grants students the autonomy to cultivate creative thinking patterns and fosters heightened engagement in the learning process. The study also highlights adapting the model to online learning, with teachers as facilitators. In conclusion, these findings underscore the effectiveness of the problem-solving learning model in independent learning, especially in the post-pandemic era. They also offer valuable insights for educators and policymakers to develop adaptive learning strategies suited to the current educational environment.
Developing a Gantry Robot with Pre-calculated pure S-curve Motion Profiles for Delicate Egg Handling: Utilizing ESP32, FreeRTOS, and AS5600 Encoders Ju Ju Naing; Swe, War War Min; Win, Htay Htay
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3869

Abstract

The poultry industry faces challenges due to egg breakage during transfer. This paper describes a gantry robot specifically designed for delicate egg handling. The robot utilizes pre-calculated pure S-curve motion profiles to achieve smooth and precise movements, minimizing stress on the eggs. This approach leverages the computational efficiency of pre-calculation, making it suitable for low-power microcontrollers like the ESP32. FreeRTOS(Free Real-Time Operating System) ensures real-time task management for profile execution and data collection every 4 milliseconds from the AS5600 encoders. These encoders provide high-resolution angular position feedback, allowing for comparison with the planned S-curve profile after each movement step. This system offers advantages such as reduced egg breakage, improved transfer efficiency, and a simpler design compared to real-time control. However, limitations include limited adaptability to significant environmental changes and disturbances. Future work may investigate incorporating real-time feedback control for enhanced robustness.
Explainable Sentiment Analysis pada Ulasan Aplikasi Shopee Menggunakan Local Interpretable Model-agnostic Explanations Ninda Rizky Nuraeda; Muhaza Liebenlito; Taufik Edy Sutanto
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.3870

Abstract

Seiring dengan perkembangan teknologi, pertumbuhan e-commerce mengalami peningkatan secara signifikan. Hadirnya aplikasi Shopee sebagai salah satu platform e-commerce terkemuka telah mendorong pengguna untuk melakukan transaksi belanja secara online. Dalam konteks ini, perhatian terhadap peningkatan kualitas aplikasi menjadi penting, khususnya melalui evaluasi ulasan pengguna dengan menggunakan analisis sentimen. Analisis sentimen umumnya mengadopsi pendekatan machine learning, meskipun transparansi dalam proses analisis menjadi tantangan utama. Penelitian ini mencoba mengatasi tantangan tersebut dengan menerapkan aspek baru dari Artificial Intelligence (AI), yang dikenal sebagai eXplainable Artificial Intelligence (XAI), khususnya pada analisis sentimen yang disebut Explainable Sentiment Analysis. Metode Local Interpretable Model-agnostic Explanations (LIME) digunakan untuk menjelaskan faktor-faktor yang mempengaruhi prediksi model machine learning. Model yang dievaluasi yaitu Logistic Regression, Random Forest, Support Vector Machine, dan Naïve Bayes. Hasil penelitian memberikan wawasan yang berharga tentang alasan di balik prediksi sentimen pada ulasan, sehingga diharapkan dapat meningkatkan pemahaman tentang bagaimana model machine learning membuat prediksi pada data tertentu.

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