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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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Desain dan Pengembangan Lengan Robot SCARA 5-DOF untuk Pendidikan Robotika di Laboratorium STEM Febrianto, Rokhmat
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4373

Abstract

The development of a 5-degree-of-freedom (DOF) SCARA robot arm was successfully achieved for educational use within the CSL Laboratory at the School of Applied STEM, Universitas Prasetiya Mulya. The design utilizes cost-effective, locally sourced materials and an open-source control system based on Processing Java and Arduino C. These features make the SCARA robot arm an accessible tool for students to learn robotics, particularly in the areas of kinematics, control, and programming. Extensive testing of the robot’s inverse kinematics algorithm showed promising results, with average error rates of 1.20% for the Inner Arm, 4.21% for the Outer Arm, and 3.39% for the Z-axis. These low error rates highlight the robot’s precision in movement. This research not only met its objective of creating an accessible platform for teaching robotics but also demonstrated potential for future development in robotics education and industrial applications.
Contact Stress Analysis of Spur Gears and Performance Evaluation in Oat flake Rolling Machine Ko Ko, Chit; Win, Htay Htay; Swe, War War Min; Soe, Aung Kyaw
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.v13i4.4375

Abstract

        This paper focuses on examining the structural integrity of spur gears within an oat flaking machine. This machine functions by compressing oat grains situated between a pair of horizontally aligned rollers. These rollers, set to revolve at a speed of 400 rpm and a gap of 0.45 mm, process the grains into flakes. The rotation of the rollers is facilitated by spur gears, which are propelled by a belt drive connected to an electric motor. Following a fractional rotation, the processed oats are ejected as flakes. The power transmission between gears occurs through the interaction of meshing teeth. The contact stress on the spur gear is determined using Hertz's theory, and the analysis of contact stress across two meshing spur gear teeth is executed with varying number of gear teeth via ANSYS software. The findings are delineated, and the results from finite element analysis simulations are juxtaposed with theoretical calculations. The theoretical values for effective stress and strain in contact stress analysis are 60.75 MPa and 0.51309×10⁻⁴, respectively, while simulation values are 61.78 MPa and 6.1846×10⁻⁴. Theoretical and simulation results are nearly the same. Therefore, the design is safe for oat flake rolling machine. The machine's performance was tested with 0.45 mm and 0.6 mm flakes over three days. For 0.45 mm flakes, the average capacity was 28.99 kg/hr with 99.46% efficiency, while for 0.6 mm flakes, it was 48.14 kg/hr with 99.73% efficiency. These results confirm that the machine operates reliably and efficiently at both settings.
Enhancing Inspection Tasks: A Dataset for Corrosion Defects in Pipelines Aljalaud, Faten; Yousef Alohali
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4380

Abstract

Inspection plays a crucial role in ensuring the longevity, security, and dependability of critical public infrastructure for both governments and businesses. However, traditional inspection processes are often labor-intensive and pose various risks. Consequently, there is a growing need for automation in such tasks. This research paper presents a comprehensive dataset that can be utilized to develop algorithms and systems for automating the inspection process, a critical area in the field of computer vision. The dataset encompasses a diverse range of inspection scenarios and serves as a valuable resource for advancing automation technology specifically for the inspection of steel pipes to detect corrosion defects. Real-life pipe maps have been used to derive scenarios that represent varying levels of corrosion. By leveraging this dataset, researchers and practitioners can contribute to the development of more efficient and accurate automated inspection systems, thus greatly improving the overall efficiency and long-term safety of infrastructure inspection.
Perbandingan Algoritma Regresi Linear dengan Algoritma Backpropagation dalam Estimasi Timbulan Sampah di Sulawesi Utara Martina Lorensa; Rorimpandey, Gladly C.; Santa, Kristofel
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4093

Abstract

Pada penelitian ini dilakukan perbandingan dua algoritma untuk estimasi timbulan sampah yaitu algoritma regresi linear dengan algoritma backpropagation. Tujuan dari penelitian ini yaitu untuk mengetahui model algoritma dengan performa terbaik yang dihasilkan dari kedua algoritma tersebut yang mana algoritma dengan kinerja terbaik akan digunakan dalam pembuatan sistem estimasi timbulan sampah. Hasil penelitian menunjukkan bahwa berdasarkan hasil evaluasi model untuk kedua algoritma menggunakan data uji didapatkan bahwa model regresi linear sederhana memiliki kinerja yang lebih baik dari pada model backpropagation. Untuk nilai error pengujian data uji dengan metrik evaluasi MSE dan MAE pada model algoritma regresi linear yaitu sebesar 0,034382 dan 0,13332 dibandingkan dengan backpropagation didapatkan nilai MSE dan MAE sebesar 0,03457 dan 0.13974. Dan pada penelitian ini telah dibuat sistem estimasi timbulan sampah menggunakan algoritma regresi linear sederhana dengan pengujian algoritma memiliki nilai error MAPE kurang dari 10% yang mana masuk dalam kategori sangat akurat.
Aplikasi Android Untuk Reservasi Lapangan Futsal Menggunakan Metode First In First Out (FIFO) Laala, Jonathan Zebina; Lamasitudju, Chairunnisa Ar.; Azhar, Ryfial; Laila, Rahmah; Wirdayanti; Miftah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4104

Abstract

Technology facilitates the process of futsal field rental, such as payment queueing and real-time monitoring. An Android application has been developed to manage payment queueing and futsal field rental at Novega Futsal Court, addressing inefficiencies of traditional methods that decrease customer satisfaction. Utilizing Rapid Application Development (RAD) and First In First Out (FIFO) method, this application designed expedite and enhance the queueing process. Data was collected through direct interaction with respondents and on-site observation, while its development involved the use of React Native and Node.js. Testing results indicate the application functions as expected, enabling users to easily rent and pay, and assisting managers in efficiently organizing queues. This application enhances service efficiency and customer satisfaction, making a positive contribution to technology-based futsal management.
Kebijakan Link and Match Di Pendidikan Teknologi dan Kejuruan (PTK) dalam Persepsi Managemen Kurikulum di Indonesia Oriza, Wike
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4114

Abstract

Prambule Undang-undang Dasar 1945 menegaskan peningkatan tingkat pendidikan sebagai tujuan utama pemerintah Republik Indonesia, mengarah pada pendidikan berkualitas tanpa diskriminasi dan berakar pada nilai-nilai Pancasila. Upaya mencapai pembangunan manusia komprehensif mencakup program pendidikan kejuruan, yang bertujuan mempersiapkan individu untuk bidang kerja baik formal maupun informal. Pendidikan kejuruan awalnya berbasis esensialisme, memisahkan kejuruan dan akademik, tetapi terdapat ketidakselarasan dengan dunia kerja. Tujuan pendidikan kejuruan kini lebih fokus pada persiapan siswa untuk bidang tertentu, meski tantangan muncul akibat dinamika kepentingan yang tidak selalu sejajar. Kualitas pendidikan berperan krusial dalam kemajuan bangsa, menciptakan lingkungan pembelajaran untuk mengembangkan potensi siswa. Dalam era kemajuan ilmu pengetahuan dan teknologi, persaingan sumber daya manusia berkualitas memerlukan kebijakan Link and Match antara sekolah dan dunia kerja. Hal ini sangat memegang peranan penting di era revolusi industri 4.0, dimana upaya transformasi menuju perbaikan dengan mengintegrasikan dunia online dan lini produksi di industri, semua proses produksi berjalan dengan internet sebagai penopang utama. Implementasi kebijakan ini diharapkan dapat mengurangi pengangguran, mengoptimalkan kesiapan kerja lulusan pendidikan teknologi dan kejuruan, serta mencapai tujuan pembangunan pendidikan yang berkelanjutan. Link and match juga merupakan program vokasi pemerintah yang menghubungkan SMK dengan industri dalam kerangka Kerjasama termasuk meliputi penyelarasan kurikulum, pelatihan guru, prakerind siswa, penguatan TEFA yang didukung evaluasi program berkelanjutan
Implementasi Kurikulum Berbasis Local Wisdom pada Pembelajaran Seni Kuliner : Studi Kasus Program Studi S1 Pendidikan Vokasional Seni Kuliner Wiwik Gusnita; Nizwardi Jalinus; Rijal Abdullah; Ridwan
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4115

Abstract

The existence of this local wisdom-based curriculum can increase the younger generation's awareness of social and cultural identity which is currently starting to be abandoned and turned to the western world. This research aims to identify forms of local wisdom and describe in more detail the implementation of a local wisdom-based curriculum. This research method is descriptive qualitative by adding the VOSviewer application to obtain relevant data. This study refers to the application of a local wisdom-based curriculum to the FPP-UNP Culinary Arts Vocational Education Study Program. The research results show that graduates of the culinary arts vocational study program also have competence in processing randang and traditional Minangkabau food to develop entrepreneurship and support tourism in West Sumatra. The implementation of a local wisdom-based curriculum in the Culinary Arts Vocational Education undergraduate study program adapts to three national higher education standards, namely content standards, process standards and assessment standards.
Multi Stage Analisis Sentimen Berbasis Aspek Pada Ulasan Pengguna Aplikasi Dompet Digital Menggunakan Metode Multinomial Naïve Bayes Hikmatul Maulidia Putri
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4197

Abstract

Digital wallet is one of the financial technology that is currently popularly used by Indonesians as a non-cash transaction tool. The more users of digital wallet applications, the number of reviews, comments, and opinions also increases and varies. User reviews are considered very helpful as well as a forum for information because they can assess certain aspects. This study proposes research related to Aspect-based Sentiment Analysis using Multinomial Naïve Bayes to analyze user sentiment towards an aspect, namely service, cost, and security on digital wallet applications and determine the evaluation of system performance using the Multinomial Naïve Bayes algorithm. The data in this study was taken using scraping techniques with keywords from the Google Play Store platform as many as 500 in each aspect. The results of this study show that the 70:30 data division is better than other data division ratios, namely the 80:20, and 90:10 data division ratios, with performance evaluation using accuracy, precision, recall, and f1-score respectively 0.841, 0.844, 0.841, and 0.841.
Optimasi Pemilihan Fitur untuk Prediksi Penyakit Jantung Menggunakan Algoritma Genetika dan Random Forest Gori, Takhamo; Hestiningtyas, Annisa
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4214

Abstract

Penyakit jantung merupakan salah satu penyebab utama kematian di seluruh dunia, menekankan urgensi prediksi dini dan manajemen risiko yang efektif. Dalam upaya meningkatkan akurasi prediksi penyakit jantung, penelitian ini mengusulkan pendekatan metode GridSearchCV (GS) dan Genetic Algorithm Feature Selection (GA-FS) pada model Random Forest (RF). Setelah proses seleksi fitur dengan GA-FS, dari sebelas atribut awal dimasukkan, delapan atribut terpilih, yakni Sex, ChestPainType, RestingBP, Cholesterol, FastingBS, RestingECG, ExerciseAngina, dan ST_Slope, sementara atribut Age, MaxHR, dan Oldpeak dieliminasi. Hasil penelitian menunjukkan bahwa model RF yang dioptimalkan dengan GS dan GA-FS (RF-GS-GAFS) mencapai akurasi 91.85%, presisi 95.10%, recall 90.65%, dan F1-Score 92.82%, mengungguli model RF dengan optimasi GS (89.67%) dan RF tanpa optimalisasi (88.04%). Temuan ini memberikan kontribusi positif yang signifikan dalam meningkatkan kinerja model prediksi penyakit jantung melalui optimalisasi parameter dan pemilihan fitur menggunakan algoritma genetik.
Designing an Effective Job Recommender System based on Embedded Machine Learning Models Ayodele, Abiola Olaide; Gbadebo, Adedeji
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4232

Abstract

The need to automate employment offers to qualify job searchers has gain attentions. For an automated recommendation systems to be used more frequently, a better user-friendly filtering techniques are required. This paper designs an automated process, referred to as “the job recommender”, which focuses on user-centric design and personalization for recommending and matching applicants with appropriate jobs. We use the bottom-up approach that uses dataset based on filtering algorithms to predict and make recommendations for job seekers. The algorithm helps the recruiters to produce the list of the résumé that best meets the job descriptions. In this context, the random forest (RF) and support vector machines (SVM) are adopted to train the data. They are supplied personalized information (qualifications, result of aptitude test, age, and work experience) reported on the résumés of individual candidates from the pool of submissions, and the system train data to learn the evolution of job selection by candidates based on these machine learning tools. The algorithm used would help the recruiters to produce the list of the résumé that best meets the job descriptions. The algorithms are designed to recommend personalized items tailored to each user's interests. Under the minimum hardware and software requirements, the job recommender system was implemented in streamlit - a python template, for designing the frontend.

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