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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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Machine Learning and Fuzzy C-Means Clustering for the Identification of Tomato Diseases Saleh, Amir; Ridwan, Achmad; Gibran, M Khalil
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3379

Abstract

Diseases in tomato plants can cause economic losses in the agricultural industry. Identification of tomato plant diseases is important to choosing the right action to control their spread. In this research, we propose an approach to identify tomato plant diseases using a machine learning algorithm and lab colour space-based image segmentation using the fuzzy c-means (FCM) clustering algorithm. The segmentation method aims to separate the infected area, leaf image, and background in the tomato plant image. In the first step, the tomato image is represented in the Lab colour space, which allows for combining information on brightness (L), red-green colour components (a), and yellow-blue colour components (b). Then, the FCM algorithm is applied to segment the image. The segmentation results are then evaluated through an identification process using machine learning techniques such as k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes (NB) to measure the level of accuracy. The dataset used in this research is tomato images, which include various plant diseases obtained from the Kaggle dataset. The performance results of the proposed method show that the segmentation approach based on Lab colour space with the FCM clustering algorithm is able to identify infected areas well. The accuracy value of each machine learning method used is kNN of 85.40%, RF of 88.87%, SVM of 80.73%, and NB of 74.60%. The proposed method shows success in accurately identifying types of tomato plant diseases and obtains improvements compared to without using segmentation.
Pengaruh Knowledge Sharing Factor Terhadap Keberlanjutan Penggunaan E-Learning Pasca Covid-19: The Influence of Knowledge Sharing Factors on the Continuity of Using E-Learning Post-Covid-19 Ariyanti, Putri; Ditha Tania, Ken; Wedhasmara, Ari; Meiriza, Allsela
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3382

Abstract

E-learning includes learning methods that use information technology and can be accessed via the internet, making it possible to learn remotely without face-to-face meetings. E-learning functions to implement knowledge management practices, especially in sharing knowledge. Studies on various knowledge-sharing factors influencing the adoption of e-learning in the post-pandemic context are still limited in the existing literature. Therefore, this study has the objective of developing an Expectation Confirmation Model by taking into account the factors of knowledge sharing (communication openness, personal trust, sharing motivation, use of technology, and perceptions of ease of use of technology) to test the viability of using e-learning, especially at Srivijaya University. This study uses the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to test the validity of the developed model. Study data was collected from active students at Sriwijaya University who used or are currently using e-learning in lectures. The results of this study show that knowledge sharing factors, including openness of communication, personal trust, motivation to share, usefulness of technology, and perceived ease of use of technology, are important factors in determining the continued use of e-learning services at Sriwijaya University.
Sentiment Analysis Performance Value Optimization Using Hyperparamater Tunning With Grid Search On Shopee App Reviews Muhammad Luthfi Al-Ghifari; Ken Ditha Tania
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3384

Abstract

The rapid development of technology today has provided convenience for us in today's civilization. One of these developments is the invention of the internet due to high internet penetration and rapid growth in mobile usage, online shopping has increased tremendously. This online shopping is now often referred to as e-commerce. E-commerce is one of the trade models that has been widened under the effect of extensive use of technology. Specifically, e-commerce refers to the usage of the Internet or other networks. Shopee is one of the popular marketplaces in Indonesia that has the highest number of visitors of 129 million per month and can be downloaded on the Google Play Store. Play Store itself has several features such as Reviews that can allow users to give opinions. All complaints and opinions from shopee users can be channeled into this feature. With this a research aims to optimize the performance value of sentiment analysis with the Term Frequency-Inverse Document Frequency (TF-IDF) method and Hyperparameter Tuning with Gridsearch for the Shopee application on the Google Play Store. Based on research the reviews resulting in 3000 data where 2015 user data is positive and 985 data is negative. Testing data was split by a ratio of 90:10 for 300 data test in each classification model to find the accuracy score. With hyperparameter tuning using gridsearch we can see the result of each accuracy score of KNN, DCT, RF, and LR is increasing from 0.73 to 0.77, 0.823 to 0.826, 0.856 to 0.87, and 0.856 to 0.866. This indicated that among the machine learning model that had been tuning using gridsearch, KNN is the one that highly increased.
Faktor Adopsi Microsoft Teams Sebagai Teknologi Kolaborasi Pada Perusahaan Dengan Modifikasi UTAUT2 Tanizar, Ade Lido; Gui, Anderes
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3386

Abstract

Beberapa perusahaan di Indonesia telah melakukan adopsi Microsoft Teams untuk mendukung kegiatan berkolaborasi di perusahaan. Adopsi ini dilakukan sebagai langkah adaptasi selama masa pandemi Covid-19, serta selanjutnya mendukung skema hybrid-working arrangement yang diadopsi beberapa perusahaan pasca berakhirnya masa pandemi. Studi ini melakukan identifikasi atas faktor yang mempengaruhi adopsi teknologi kolaborasi yang digunakan di perusahaan, dengan pendekatan UTAUT2 yang diadopsi dengan melakukan modifikasi dengan menambahkan konstruk perceived value. Hasil yang didapatkan pada penelitian ini menunjukkan sebagian besar konstruk UTAUT2 dapat menjelaskan penerimaan adopsi teknologi kolaborasi, termasuk perceived value. Pada penelitian ini, Effort Expectancy ditemukan tidak berpengaruh signifikan pada adopsi Microsoft Teams di perusahaan.
Automatic Generation of Unit Test Data for Dynamically Typed Languages Hayatou Oumarou; El Mansour, Faouzi
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3396

Abstract

Testing is the major means of verifying and validating software. It is a repetitive and time-consuming activity. Testing is neglected because of its high cost and the fact that it does not add functionality to the system. As a result, many programmers don't write tests. To remedy this, some researcher proposed automatic test generation. Test generation is a solution that reduces workload and increases productivity. In this paper, we propose a test data generation approach for unit tests in dynamically typed languages. Our approach is based on the analysis and decomposition of the AST (Abstract Syntax Tree) obtained when compiling the source code of the method under test. We validate this approach in Pharo a real system. The results on three systems show the effectiveness of the approach.
IT Project Management Control and The Control Objectives for IT and Related Technology COBIT 2019 Framework Jaya, Ruddy Kusuma; Melissa Indah Fianty
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3397

Abstract

The development of information technology has been leveraged by state-owned enterprises (BUMN) operating in the fields of Maintenance, Repair, and Overhaul, as well as industrial services in Indonesia. Among the company's 21 priority projects, three projects have been identified as experiencing delays in the planning phase related to the delivery of business requirements. The measurement of IT governance capability was conducted using the process rating of COBIT 2019. The selected process objectives were APO02, APO03, and APO05. The results of the capability level measurement indicate that APO02, APO03, and APO05 have reached level 2. Based on the measurement results, findings have been identified that require improvement, especially in APO03, such as providing understanding to key stakeholders about enterprise architecture and enterprise architecture design. As a recommendation for improvement, it is expected that the company can engage in Enterprise Architecture design to align strategic program priorities with architectural objectives.
Penerapan Metode Design Thinking Terhadap Perancangan User Interface Marketplace BuildID Untuk User Putra, Pacu; Irfa, Nyayu Nhasywa Perialah; Sazaki, Yoppy; Hardiyanti, Dinna Yunika; Novianti, Hardini
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3398

Abstract

Marketplace Build Id merupakan marketplace berbasis mobile yang dikembangkan oleh PT. Semen Baturaja. Marketplace ini berguna untuk meningkatkan penjualanan, promosi serta pemasaran. Build Id sendiri telah tersedia dalam bentuk website dan sedang mengembangkan versi android atau mobile. Penelitian ini bertujuan membantu perancangan user interface Build Id milik PT. Semen Baturaja agar lebih terarah pada fitur-fitur yang akan diimplementasikan sehingga hasilnya dapat sesuai dengan kebutuhan pengguna. Sedangkan metode perancangan yang dipakai yakni Design Thinking akan diimplementasikan melalui prototype aplikasi Build Id dan dilakukan pengujian black-box testing berguna untuk mengetahui fungsionalitas sistem dari aplikasi Build Id. Hasil dari pengujian menunjukkan bahwa marketplace Build Id berjalan dengan baik serta sesuai yang diharapkan.
Framework for Project Sustainability for Power Installations Using Business Intelligence Approach: A Systematic Literature Review Esiefarienrhe, Bukohwo Michael; Maine, Itumeleng Michael
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3402

Abstract

The growing concerns about environmental sustainability and energy conservation have led to increased interest in optimizing electricity consumption and billing processes in various projects. This research article presents a comprehensive study on the development and application of Business Intelligence (BI) frameworks for enhancing project sustainability through data-driven energy management. Through the integration of BI tools and techniques, this research investigates the analysis of electricity consumption patterns, billing accuracy, and cost-effectiveness in diverse project contexts. The article emphasizes the significance of data preprocessing, statistical analysis, and predictive modelling in uncovering valuable insights to support informed decision-making. Additionally, the review examines the concept of project sustaibility, emphasizing its significance in achieving desired outcomes, meeting stakeholder expectations, and ensuring the project’s viability in an ever-changing environment. Traditional project management approaches often fail to adequately address sustainability concerns, leading to project failures or limited long-term impact. Hence, the review highlights the growing importance of leveraging BI-driven frameworks to enhance project sustainability in various sectors, including in Information and Communication Technology (ICT) domain. The Systematic literature review (SLR) method was used involving the scooping of 230 articles from over 8 global academic databases. With the use of exclusion criteria, only 61 articles were used in the study. The analysis of the articles shows that 57% were journal articles, 39% were conference proceedings, 2% were thesis/dissertations and 2% were generic. Within the scope of this literature review, key terms and keywords were identified to provide insights into the development of a novel BI-driven framework for project sustainability. Consequently, future research directions are identified to further explore the integration of renewable energy sources, AI and machine learning applications, and behaviour-based energy management strategies within BI frameworks for sustainable project outcomes. This review lays the foundation for future research endeavours in developing innovative BI-driven frameworks that foster sustainable practices and contribute to a greener and more resilient future across diverse industries and projects.
Analisis Pengaruh User Satisfaction Terhadap Niat Penggunaan Sistem Informasi Kearsipan Dinamis Terintegrasi (SRIKANDI) pada Pemerintahan Kota Palembang : Analysis of the Influence of User Satisfaction on Intention to Use Integrated Dynamic Archival Information Systems in Palembang City Government Zhafira Zafitri; Putra, Apriansyah
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3403

Abstract

Transformasi digital berperan penting di Pemerintahan Indonesia dengan SRIKANDI (Sistem Informasi Kearsipan Dinamis Terintegrasi) yang diluncurkan oleh Kementerian PANRB pada 2020. Pada Februari 2023, SRIKANDI mulai diterapkan di Pemerintah Kota Palembang. Namun, fakta yang ada menunjukkan bahwa banyaknya aplikasi pemerintah yang tidak digunakan dan dinilai tidak efisien. Salah satu penyebab permasalahan tersebut terjadi dikarenakan rendahnya tingkat kepuasan pengguna. Oleh karena itu, perlu dilakukan analisis pengaruh user satisfaction terhadap niat penggunaan SRIKANDI di Pemerintahan Kota Palembang, terutama dari perspektif Aparatur Sipil Negara (ASN) sebagai pengguna SRIKANDI. Penelitian ini menggunakan teori Delone & McLean IS Success Model untuk mengukur faktor-faktor tiap dimensi kualitas, user satisfaction, intention to use, dan menambah faktor privacy concerns. Data dikumpulkan melalui kuisioner yang diberikan kepada 250 ASN di Kota Palembang. Data yang diperoleh dianalisis menggunakan aplikasi SmartPLS 4 dan teknik PLS-SEM. Hasil penelitian menunjukkan bahwa User Satisfaction berpengaruh positif pada Intention to Use. Sementara itu, User Satisfaction dipengaruhi positif secara signifikan oleh Completeness, Pleasure, dan Assurance. Availability dan Privacy Concerns tidak memiliki pengaruh signifikan terhadap User Satisfaction.
Sentiment Analysis of Hotel Reviews Using Support Vector Machine Simarmata, Alexander Romian; Muhammad Zakariyah
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): 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.v12i5.3405

Abstract

With technology nowadays, everyone can leave their review about a hotel on the internet. This creates a new issue for the hotel itself because the reviews can come in in thousands amount. This will consume a lot of time to handle these reviews manually. In this study, a sentiment analysis model will be made to overcome the issue. The data in this study is collected from Kaggle website. This data contains 20,491 reviews about a hotel. The data will then be preprocessed and given a label for each data point. Then, the model is trained using the clean data. The model will use Naïve-Bayes, Logistic Regression, and Support Vector Machine algorithm. From the result performed, it's concluded that Support Vector Machine performed more accurately with 94% rate.

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