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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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Tata Kelola TI Strategis: Memanfaatkan Kerangka COBIT 2019 untuk Mengurangi Kegagalan Pencadangan Data dalam Operasi Industri Melissa Indah Fianty
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.v13i3.3918

Abstract

The development of information technology today has had a significant impact on various aspects of human life, including in the industrial sector. One example is the integration of information technology in company operations to use it as a supporting tool for sending data and information which is the main reference for organizational management in decision making. To measure the level of capability of the IT system used, companies can use the COBIT 2019 framework, which not only helps in assessing the suitability of IT systems, but also provides recommendations for solutions to problems faced by the company. For example, research results show that problems related to data backup failures have been identified in Domain DSS01, with recommended solutions such as implementing policies related to information security from outsourced employees, establishing internal management processes, setting up timely incident tickets, and implementing recommendations to overcome non-compliance.
Optimization of Fortune Cooking Oil Distribution Routes Using Ant Colony Optimization Method Yuniar Nur Latifah; Donoriyanto, Dwi Sukma; Nur Rahmawati
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.v13i2.3920

Abstract

In Indonesia, cooking oil is very important as a food ingredient. Where the production volume of a product can affect distribution system decisions. An efficient distribution process can provide a competitive advantage in terms of cost and service. Distribution at PT ABC is currently still done manually, besides that the company has not optimized the transport capacity of vehicles so that it results in swelling distribution costs, as well as distribution bridges. This research is aimed at finding the most optimal distribution route for cooking oil products at PT A using the Ant Colony Optimization method. After processing the data using the Ant Colony Optimization method, the optimal fortune cooking oil distribution route was obtained by dividing it into 4 subroutes with a total mileage of 2371 KM with a total distribution cost of Rp. 1,612,960. and the total mileage of the initial route was 2693 KM with a total distribution cost of Rp. 1,831,240. So we get a total savings in mileage of 322 KM and savings in total distribution costs of Rp. 218,960. Therefore, the results obtained using the Ant Colony Optimization method will be selected as the proposed method.
A Review on Heart Disease Detection Classification Based on Deep Learning Algorithm Jalal, Dimen; Abdulazeez, Adnan Mohsin
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.v13i2.3921

Abstract

Heart disease it is one of the main causes of death in the globe. Heart illness encompasses a spectrum of disorders that impact the heart, its blood arteries, and its overall functionality. Also referred to as cardiovascular disease. This paper investigates the potential benefits of deep learning (DL) architectures for improving diagnostic accuracy addressing the critical need for improved diagnosis of cardiac disease, and the difficulties associated with applying DL methods for heart disease identification. This survey study highlights the important role that DL plays in cardiovascular diagnostics from a number of tasks like as diagnosing, predicting, and classifying heart diseases. Convolutional Neural Networks (CNNs), a type of deep learning, are being used in the context of heart illness with the primary goal of creating accurate and dependable models for the identification, diagnosis, and prognosis of various heart-related disorders.
A Review of Heart Disease Classification Base on Machine Learning Algorithms Hasan, Mayaf; Abdulazeez, Adnan Mohsin
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.v13i2.3923

Abstract

Heart disease is currently the leading cause of death. This problem is acute in developing countries. Predicting heart disease helps patients avoid it in its early stages and can also help medical practitioners find out the main causes. Machine learning has proven over time to play an important role in decision making and forecasting through massive data sets created by the healthcare sector. This review provides an overview of heart disease prediction using applied machine learning algorithms such as Naïve Bayes, Random Forest, Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression, and K-Nearest Neighbour (KNN). And these differences in the techniques are a reflection of many strategies for predicting heart disease. We present a synopsis of classification techniques that are primarily used in the predicted of heart disease. Additionally, we review several previous studies that conducted over the past four years, that used machine learning algorithms to predict cardiovascular.
Bioinformatics in Action : A Comprehensive Review of Bioinformatics Applications in Varied Disciplines Dewi, Adhe; Setyo Adhi, Canggih Gelar
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.v13i3.3924

Abstract

Studies have been carried out related to the application of bioinformatics which includes genomics, proteomics and metabolomics in everyday life, such as in the fields of health, agriculture, environment, renewable energy and food. Evaluation of the quality of the papers used is based on papers available in each journal on platforms such as Scopus, Google Scholar, as well as articles published by Elsivier, Springer Nature, etc. The stages carried out in this research include journal data collection, journal renewal, journal grouping, and journal comparison. Based on this application, it has been proven that bioinformatics has achieved success in understanding various biological aspects. Thus, it is hoped that this research can provide deeper insight regarding the use of bioinformatics in various other fields.
Regulation of Network Condensation Based on Fitness Ordered Access Strategy Xu, Dongpeng
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.v13i2.3926

Abstract

The condensation in complex networks disclose the underlying mechanism of the monopoly in socioeconomic system, which can help us to design and access the anti-monopoly policy based on the study on network condensation. Inspired by the consideration, We introduce a set of rearrangement mechanism into the fitness model to regulate the order of nodes with different fitness to enter the network, and study the influence of this regulation strategy on network condensation. By extensive Monte Carlo simulations and finite size scaling analysis, we obtain the critical rearrangement index under a typical fitness distribution, establish the relationship between the index and the condensation intensity, and finally construct the condensation phase diagram. These results show that there exists an interval of the critical rearrangement index, outside which the condensation of the fitness model will be effectively suppressed. We carry out a theoretical analysis on some key results to understand their underlying origin, and discuss their instructive significance on the anti-monopoly market management.
Fluctuation behavior of the degree growth dynamics in complex networks Chang, Hanyun; Qian, Jiang-Hai
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.v13i2.3927

Abstract

The standard network theory predicts the fluctuation of the degree growth rate is interval-independent, whereas the evidence witnessed in Internet shows an inconsistent result, which raises the concern of many existing relevant studies that apply just single observation interval. To check whether such inconsistency occurs in more systems, we study empirically the degree growth fluctuations in two social networks. We find both their fluctuation exponents decrease logarithmically with the observation interval, presenting clear interval dependency that differs from those observed in Internet in the specific manner but is still consistent in the tendency. By applying a progressive shuffling procedure, we find an asynchronous response of the fluctuation exponent and deduce the decline of the exponent might be related to the development of the internal correlation. These results indicate the general existence of the interval dependency in the degree growth fluctuation and suggest its close connection with the correlation evolution, which could provide new insight to the related dynamics in complex networks.
Perancangan Sistem Donasi Kepada Penulis Ilmiah Dengan Blockchain Ethereum Berbasis Ekstensi Browser Laurenso, Justin; Yohannis, Alfa Ryano
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.v13i3.3928

Abstract

This research highlights the challenges faced by scientific authors, especially regarding the lack of recognition, financial support, and appreciation. An innovative solution is proposed through the application of blockchain technology, specifically Ethereum, to improve transparency and security in the donation flow. Using such an approach, this research aims to provide a solution to the problem as well as open up wider collaboration opportunities within the research community. This research involves steps such as literature study, system analysis, system development, and report generation. In system development, the SDLC (Software Development Life Cycle) methodology with a structured waterfall model is used and is suitable for designing a donation system with blockchain technology. This research successfully developed a donation system integrated with the ethereum blockchain based on browser extensions. The unit testing results show that the functions used run well. It is hoped that this research can make a significant contribution in supporting scientific writers, strengthening transparency in the flow of donations, and becoming a foundation for further research in this field.
Finite Element Analysis of Spur Gear Set in Noodles-making Machine Using Different Materials and Face Widths Thin, Po Po; Win, Htay Htay; Soe, Aung Kyaw; Latt, Aung Ko
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.v13i2.3929

Abstract

This paper focuses on the design and structural analysis of a spur gear set for a noodles-making machine by changing three different materials (ASTM A 536, ASTM A 220, and AISI 1020) and gear face widths. Gear corrosion occurs at contact points as a result of bending stress and contact stress. This is the major source of the gear failure of the noodles-making machine. Pitch diameters of 50mm and modules of 5mm spur gears are selected in the design of the roller gear set. In theoretical analysis, the AGMA contact stress equation was used based on the Hertzian theory. The minimum von Mises stress and effective strain are found on AISI 1020 carbon steel by using ANSYS 17.0 software. In this paper, von Mises stress and effective strain are analyzed by changing the face widths of spur gear set to 8mm, 10mm, 12mm, 14 mm, and 16mm and using finite element analysis (FEA). Although all face widths are safe for this design, 12mm is chosen in this paper due to power consumption and strength points of view.
A Qualitative Study on the Influencing Factors of E-Government Adoption to Improve Public Trust in Local Government: Case Study of Rokan Hulu Municipality Fadrial, Rudy; Sujianto; Simanjuntak, Harapan Tua Ricky Freddy; Wirman, Welly
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.v13i3.3931

Abstract

Amidst global public trust challenges, e-government emerges as a promising solution to bolster trust. In Indonesia, rural areas face obstacles hindering effective e-government implementation. This paper explores Rokan Hulu Municipality's initiatives, aiming to understand e-government's impact on public trust at the rural/district level, bridging critical knowledge gaps. This study employs a qualitative approach to investigate the factors influencing e-government adoption. Primary data is gathered through interviews with key stakeholders, supplemented by secondary data from organizational documents. Employing open and axial coding, this study organizes findings to the Technology-Organization-Environment framework. Within the technological dimension, obstacles such as infrastructure; integration and interoperability; data security and confidentiality; and service providers, third parties, or vendors emerge as significant barriers. In the organization dimension, culture, organizational capability, budget constraints, human resource quality, perceptions, bureaucracy, and strategy become challenges, with organizational capability and strategy showing mixed impacts due to incomplete initiatives and limited inter-agency coordination. In environment dimension, digital divide, regulatory availability, and public participation become inhibiting factors, while political intervention becomes the driving factor.

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