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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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Implementation of Density-Based Spatial Clustering of Applications with Noise and Fuzzy C – Means for Clustering Car Sales Auliani, Sephia Nazwa; Mustakim; Novita, Rice; Afdal, M
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.v13i4.4135

Abstract

This study compares the performance of two clustering algorithms, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM), in clustering car sales data at PT. XYZ. The dataset, comprising sales transactions from 2020 to 2023, includes information about vehicles, customers, and transactions. Preprocessing methods such as data transformation and normalization were applied to prepare the data. The results indicate that DBSCAN produces clusters with better validity, measured using the Silhouette Score, compared to FCM. Specifically, DBSCAN achieves the highest Silhouette Score of 0.7874 in cluster 2, while FCM reaches a maximum score of 0.3666 in cluster 3. Thus, DBSCAN proves to be more optimal for clustering car sales data at PT. XYZ, highlighting its superior performance in terms of cluster validity.
Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes: Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes Yeni Safitri; Rakhmat Kurniawan; Suhardi
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.v13i4.4136

Abstract

The emergence of the issue of childfree has become a trending topic on Twitter since the beginning of 2020 until now, which has given rise to many positive and negative opinions from various groups, especially on Twitter social media. This sentiment analysis research aims to determine the responses given regarding childfree in the form of positive, neutral or negative opinions by collecting Twitter data. The number of datasets used is 700 data, divided into 630 training data and 70 test data. This research uses the Naïve Bayes algorithm classification and confusion matrix as a performance evaluation of the system being built. The test results show an accuracy value of 64.29%, precision of 68.25%, recall of 64.29% and fi-score of 55.69%.
Design Web-based Portal to Management a Pilgrim Office in Kurdistan Region Sabri, Shaimaa Q.; Arif, Jahwar Y.; Taqa, Ghada Abd Alrhman; Çinar, Ahmet
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.v13i3.4141

Abstract

In the era of globalization, the region of Kurdistan, is participation in several ongoing projects where IT-enable systems are intended to be implemented in various sectors as part of the national IT policy. However, because of the establish system complex structure and the outdated system poor design, implementing IT enable systems locally is a significant issue. Particularly in the section dedicated to Hajj services, where files are still manually stored overcrowding happens ate registration offices since pilgrims cannot get any fresh instruction or announcements at the time they must got to the office or call them and insufficient security and safety measure for pilgrims’ data. The purpose of developing this file filing system was to facilitate and ease the management of current files by staff. As part of the research process, issues with Haji file management were identified and information was gathered via literature research, interview and observation. Laravel (PHP), Bootstrap and HTML5 are programming language used in system development, along MySQL, Xampp. System Usability Scale (SUS) approach was used to test the system, and 10 participations sign up for it. The highest overall satisfaction rate, at roughly 80.1%
Klasifikasi Ticket Service Desk Perusahaan Asuransi Jiwa Berbasis Machine Learning Imbenay, Joash Lorenzo; Indra Budi
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.v13i4.4142

Abstract

This study focuses on developing a ticket classification model for the Service Desk at an insurance company to enhance operational efficiency. Manual ticket classification is time-consuming and prone to errors, so the research aims to compare the performance of various classification algorithms to determine the best model. The methodology involves text mining and machine learning techniques using four main algorithms: Random Forest, Decision Tree, Support Vector Machine (SVM), and Naïve Bayes. The data comes from Service Desk tickets processed through text preprocessing stages. Findings indicate that the Random Forest model with a combination of TF-IDF Unigram features in the Access context performs best in classifying IT Support tickets, with a Precision of 0.76%, Recall of 0.66%, F-Score of 0.70%, and Accuracy of 0.54%. Implementing this model is expected to improve operational efficiency and user satisfaction with IT services, speeding up ticket handling, reducing administrative workload, and enhancing user satisfaction with IT services.
Evaluasi Kapabilitas dan Perancangan Tata Kelola TI Menggunakan COBIT 2019: Sekretariat Kabinet Ontoreza, Afrianda Gaza; Wirani, Yekti; Sucahyo, Yudho Giri
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.v13i4.4145

Abstract

E-government is the utilization of ICT applications to provide government services that enhance service delivery to be transparent, efficient, and effective. In Indonesia, the policy for managing e-government is regulated through Presidential Regulation No. 95 of 2018 concerning the Electronic-Based Government System (SPBE). This study was conducted in the Cabinet Secretariat (Setkab) with an SPBE evaluation results index that can still be optimized, particularly for the governance domain, which achieved a score of 2.90. Organizationally, Setkab does not yet have an information technology governance document. The research aims to conduct an evaluation of the capability level and formulate IT governance recommendations using COBIT 2019 framework. Assessment and design are carried out in accordance with Setkab's objectives, 13 processes are identified that are still below organizational expectations or below maturity level 3. IT governance recommendations are formulated to support the organization's strategic plan and increase the SPBE achievement index at Setkab.
Analisis Kesiapan Karir Mahasiswa Diploma Tata Busana Dalam Persaingan Bisnis Era Digital Novit, Sri Zulfia Novrita
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.v13i4.4148

Abstract

This study aims to measure the career readiness of Diploma in Couture students at the Faculty of Tourism and Hospitality, Padang State University in facing digital business challenges. This research uses a survey method by collecting data from 172 of the total population of students who are academically active in 2024. The sample technique used was purposive sampling. The indicators measured include digital literacy readiness, technology adaptability readiness, practical experience readiness, and modern business skills readiness. The results showed that students' digital literacy readiness was categorized as very low with a score of 46%, technological adaptability readiness was 60%, readiness due to practical experience was 64%, and readiness for a very low understanding of modern business skills was 43%. These findings indicate a significant gap between academic training and current industry requirements, which hinders students from adapting quickly to new technologies and managing fashion businesses effectively in the digital age. This study aims to measure the career readiness of Diploma in Couture students at the Faculty of Tourism and Hospitality, Padang State University in facing digital business challenges. This research uses a survey method by collecting data from 172 of the total population of students who are academically active in 2024. The sample technique used was purposive sampling. The indicators measured include digital literacy readiness, technology adaptability readiness, practical experience readiness, and modern business skills readiness. The results showed that students' digital literacy readiness was categorized as very low with a score of 46%, technological adaptability readiness was 60%, readiness due to practical experience was 64%, and readiness for a very low understanding of modern business skills was 43%. These findings indicate a significant gap between academic training and current industry requirements, which hinders students from adapting quickly to new technologies and managing fashion businesses effectively in the digital age.
Digital Image Noise Reduction Based on Proposed Smoothing and Sharpening Filters M. Weli, Mohammed; M. Abdullah, Omar
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.v13i4.4151

Abstract

In order to reduce noise in digital photographs, this paper provides a thorough analysis of sophisticated sharpness enhancement and image smoothing approaches. The research compares and contrasts different approaches, including well-known filters like Gaussian filter, Mean filter, Weighted Averaging filter, Laplacian filters, and Unsharp mask, with suggested strategies aimed at achieving optimal efficiency. The performance of these techniques is evaluated in several circumstances with speckle noise and Gaussian noise corrupted images. The results show how well the suggested strategy performs in terms of reducing noise, preserving image features, and improving overall image quality. The comparative advantage of the suggested technique over conventional filters is highlighted by comparative analysis. The study's conclusion offers information on the possible uses and future developments of these methods in practical image processing situations.  
Data Mining Techniques Against Cyber Threats: A Review Sami, Jalal; Abdulazeez, Adnan Muhsin
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.v13i3.4153

Abstract

Abstract Data mining is a technique used to extract useful data from existing databases. Those datasets are now being shared globally. Secure communication and confidentiality are required because data from multiple sources must be collected and stored in one central location. Data mining technology involves methods that rapidly and efficiently convert vast quantities of data into relevant insights adapted to the user's requirements. Unfortunately, the utilization of data mining expertise to acquire sensitive personal information poses a threat to individuals' privacy rights. This paper provides a review of the current techniques for preventing cyber risks and safeguarding privacy through the application of data mining. Data mining is used to examine, analyze, and figure out the structure and behavior of data mining organizations. Implementing data mining with optimal outcomes is a challenging task. In the past decade, academics have extensively studied many elements of data extraction. Therefore, it is crucial to provide published research evidence pertaining to this field. For this study, a thorough evaluation was carried out of more than thirty research papers sourced from reputable literature databases. The objective was to extract significant information regarding the field of data mining. The collected data was then used to address various study inquiries about cutting-edge extraction methodologies, data mining mechanisms in cyber dangers, data extraction procedures, algorithms, and evaluation techniques. This paper discusses various research areas and issues in data mining, serving as a valuable reference for researchers in this domain.
Implementasi Kecerdasan Buatan dalam Manajemen Proyek Agile dalam Mengatasi Tantangan dan Memaksimalkan Dampak Lumbanraja, Harry Leonardo; Raharjo, Teguh; Fitriani, Anita Nur
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.v13i4.4155

Abstract

The Agile methodology, with an 80% adoption rate, often faces challenges leading to project failures. This study investigates using artificial intelligence (AI) to overcome these challenges through a systematic literature review of 44 papers. It examines AI's impact on key Agile phases: envision, speculate, explore, adapt, and close. Findings highlight AI's critical role in improving project outcomes by addressing implementation challenges. AI tools aid in risk assessment and project selection during planning, enhance effort estimation and task allocation in speculation, improve team communication and technical issue resolution in exploration, optimize systems in adaptation, and provide valuable insights in closure. The paper offers guidance on effective AI integration to enhance Agile Project Management success.
Embracing Freedom in Learning: The Impact of Kurikulum Merdeka on Engineering Students of Universitas Negeri Medan Hasan, Hanapi; Maksum, Hasan; Waskito; Tansa Trisna Astono Putri
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.v13i4.4156

Abstract

In 2020, Indonesia's Ministry of Education, Culture, Research, and Technology introduced the Merdeka Belajar-Kampus Merdeka (MBKM) curriculum for higher education to better prepare students for the modern job market. This study contrasts the MBKM curriculum with the non-MBKM curriculum, focusing on their impacts on students' career exploration and professional maturity. Using a quantitative, correlational approach, the study sampled 187 engineering students from a Medan university. Instruments included the Career Exploration Survey (CES) and the Career Development Inventory (CDI). Results showed that both curricula positively influence career exploration and professional maturity, with no significant differences between the two. The MBKM curriculum's emphasis on real-world experience and career preparation was highlighted as a key factor in fostering career readiness. The study concludes that both curricula effectively support career development, but the MBKM curriculum offers a more practical, hands-on approach to preparing students for the workforce.

Page 66 of 113 | Total Record : 1127

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