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Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Published by CV. Raskha Media Group
ISSN : -     EISSN : 31232507     DOI : https://doi.org/10.64803/cessmuds
Core Subject : Religion, Science, Education, Engineering,
Religion Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering
The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies (CESSMUDS) with ISSN No. 3123-2507 (online) is one of the activities organized by Raskha Media Group Publisher. The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies (CESSMUDS) is held to encourage Lecturers, Students, and Researchers to publish in the National Scientific Forum, hoping that society can widely feel its benefits. The lecturers, students, and researchers will be published as Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies (CESSMUDS). The proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies (CESSMUDS) are published by CV. Raskha Media Group is a Publisher managed by an editorial team experienced in their respective fields. Raskha Media Group Publisher accordance with the data in the Registration form stored in the Business Entity Administration System based on Deed Number 196 dated October 10, 2023, made by Notary ALWINE ROSDIANA PAKPAHAN, SH, located in the City of Medan, along with supporting documents received on October 11, 2023, regarding the registration of CV RASKHA MEDIA GROUP, abbreviated as RKMG, situated in the City of Medan, has been received and registered in the Business Entity Administration System.
Arjuna Subject : Umum - Umum
Articles 113 Documents
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Understanding Adolescent Online Sexual Patterns Through Big Data Analysis Yusman, Yanti; Mohd Noor, Noor Anida Zaria
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.2

Abstract

The rapid growth of digital technology and the increasing use of social media among adolescents in Indonesia, particularly in Padang, West Sumatra, have raised concerns about online sexual risk behaviors such as sexting, sharing explicit content, and unsafe interactions with strangers. Previous studies in Indonesia have largely relied on small- scale surveys, which are insufficient to capture the complex and dynamic nature of adolescents’ digital behaviors. This study aims to understand patterns of online sexual risk behaviors among adolescents in Padang through a big data analysis approach. Data were collected from popular social media platforms frequently used by teenagers and processed using text mining, natural language processing (NLP), and sentiment analysis. Clustering techniques and social network analysis were applied to identify behavioral patterns, interaction dynamics, and vulnerable groups. The findings reveal diverse patterns of behavior, ranging from curiosity-driven exploration to high-risk involvement influenced by peer pressure and exposure to sexual content online. Network analysis further indicates that digital communities play a significant role in shaping adolescents’ risky sexual behaviors in Padang. This study demonstrates that big data analytics provide a more comprehensive understanding compared to traditional survey methods, and highlights important implications for sexual health education, digital parenting strategies, and child protection policies at both local and national levels.
In Vitro Antifungal Activity of Eco-Enzyme Derived from Horticultural Organic Waste Against Candida albicans Lubis, Najla; Ate Tarigan, Ruth Riah; Hayati, Dwi
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.3

Abstract

This study aimed to evaluate the antifungal activity of eco-enzyme (EE) derived from various horticultural organic wastes against Candida albicans. Two formulations were prepared: Bioz1 (pineapple peel, orange, papaya, starfruit, kuini, and mango) and Bioz2 (pineapple, orange, banana corm, noni, and kuini). Both were fermented for 100 days. The antifungal activity was tested in vitro using the disc diffusion method at concentrations of 1:0, 1:10, 1:50, and 1:100 (EE: distilled water). Results indicated that Bioz1 at 1:50 exhibited the highest inhibition zone (7.38 mm, medium category), while Bioz2 at 1:0 showed the strongest activity (8.16 mm, medium category). Dilution at 1:10 in Bioz2 was the most effective concentration for inhibiting fungal growth. These findings highlight the potential use of eco-enzyme as an environmentally friendly natural disinfectant against pathogenic fungi
A Theory-Informed Conceptual Framework for Sustainable Intangible Cultural Heritage Preservation in the Digital Era through Immersive Information Systems Perwitasari, Ika Devi; Ariffin, Shamsul Arrieya; Jodi Hendrawan
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.4

Abstract

The preservation of Intangible Cultural Heritage (ICH) faces significant challenges in the digital age, particularly regarding authentic representation, technology acceptance, and sustainability. This research aims to develop a theory-informed conceptual framework to support ICH preservation through immersive information systems. The approach used was conceptual, with a systematic literature review, theory synthesis, and framework development. The literature analyzed included cultural preservation theory, the Technology Acceptance Model (TAM), the User-Centered Design (UCD) approach, and the Culturally Appropriate Design Guidelines (CADG). The research results produced a framework consisting of three main dimensions: Cultural Appropriateness, Technological Acceptance, and Sustainability. These three dimensions lead to the development of Immersive Information Systems that incorporate VR, AR, and AI technologies as key enablers for the documentation, dissemination, and intergenerational transfer of cultural knowledge. The literature synthesis indicates that community engagement, user acceptance of technology, and social, technological, and economic sustainability strategies are key pillars of ICH preservation in the digital age. As an illustration, the case of the Toba Batak demonstrates how immersive technology can be used to document local cultural practices such as tortor, gondang sabangunan, and ulos. The study's conclusions emphasize that ICH preservation cannot be separated from the integration of preservation theory, technology adoption, and sustainable design. The resulting framework provides both theoretical contributions by broadening the horizons of cultural preservation studies and practical contributions as a guide for the ethical, inclusive, and sustainable implementation of immersive technology.
Enhancing the Hill Cipher with a Three-Pass Protocol Approach Siahaan, Andysah Putera Utama; Binti Saari, Erni Marlina; Hassan, Moustafa Hussein Ali; A. Khalid, Noor Aldeen; Pane, Muhammad Akbar Syahbana
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.5

Abstract

This paper presents the design and implementation of a cryptographic scheme that combines the Hill Cipher algorithm with the Three-Pass Protocol (TPP) using mod-256 arithmetic. The objective is to provide a secure communication mechanism without direct key exchange while adapting a classical cipher to modern digital contexts. The system employs a 2×2 key matrix where plaintext characters are mapped to their ASCII values, grouped into vectors, and transformed through matrix multiplication followed by modulo reduction. The TPP structure allows both sender and receiver to apply their private keys independently, producing layered ciphertexts before the final recovery of the plaintext. A prototype application was developed using Microsoft Visual Studio 2010 (Visual Basic) to validate the approach. The program includes input fields for plaintext, ciphertext at each stage, key matrices, and a log box that records the detailed matrix operations for transparency. Experimental results demonstrate that the original plaintext can be accurately restored after multiple encryption and decryption phases, while the intermediate ciphertexts remain random and unintelligible. The findings confirm that integrating Hill Cipher with the Three-Pass Protocol strengthens confidentiality and eliminates the need for key distribution. Beyond its security benefits, the prototype also serves as an educational tool, helping students and practitioners understand both matrix-based encryption and keyless secure communication protocols.
Blockchain-Based Credentialing for Teachers: A Systematic Literature Review on Transparency and Trust in Educational Management Marnita, Marnita; Safarati, Nanda; Bensaadi, Iswadi; Taufiq, M.
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.6

Abstract

This study presents a systematic literature review (SLR) of blockchain applications in educational credentialing, with a particular emphasis on teacher professional development and governance. While most existing research focuses on higher education credentials, this review highlights the limited exploration of blockchain in teacher credentialing, despite its significant potential to address persistent challenges such as credential fraud, data fragmentation, and slow verification processes. Guided by the PRISMA 2020 framework, the review synthesizes 27 peer-reviewed studies published between 2019 and 2025. The findings reveal that blockchain’s core features —immutability, verifiability, and decentralization —can transform credential governance from a “trust-by-institution” model to a “trust-by-design” system. This paradigm shift enables tamper-resistant records, cross-institutional verification, and transparent audit trails, thereby enhancing accountability. The study makes three key contributions. Theoretically, it extends the literature by systematically consolidating knowledge on the role of blockchain in teacher credentialing, offering a novel perspective on its governance implications. Practically, it provides concrete recommendations for policymakers, institutions, teachers, and technology developers, with relevance for developing countries. In the Indonesian context, blockchain integration with systems such as SIMPKB, SISTER, and PDDikti is proposed as a pathway toward more transparent, accountable, and competency-based teacher management. Finally, the review identifies future research directions, including empirical pilot studies, cross-country comparisons, ethical frameworks for data privacy, and cost-benefit analyses of adoption in resource-constrained settings. Overall, this study highlights blockchain not only as a technological innovation but also as a governance strategy that can strengthen trust, accountability, and transparency in teacher credentialing systems.
The Role of the Media in Revealing Corruption Cases Rahmayanti, Rahmayanti; Pohan, Masitah
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.7

Abstract

The mass media plays a strategic role in overseeing government operations and informing the public, particularly in the context of uncovering corruption cases. This study aims to analyze the media's role in uncovering and shaping public opinion regarding corruption cases in Indonesia. Through a qualitative approach using case studies of several media reports related to major corruption cases, it was found that the media acts as a social watchdog, a driver of public opinion, and a catalyst for law enforcement action. However, the media also faces challenges such as interference from political interests and limited access to information. The study's findings indicate that the existence of free and independent media is crucial for strengthening transparency and public accountability. Therefore, strengthening journalistic professionalism and ethics is key to increasing the effectiveness of the media's role in eradicating corruption.
Analysis of Technical and Allocative Efficiency Models for Shallot Farming to Increase Production in Karo Regency Hakim, Tharmizi; Supriana, Tavi; Wibowo, Rulianda P.; Hasanah, Yaya
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.8

Abstract

The shallot commodity has a strategic role in national food security, but its production still experiences fluctuations, especially in Karo Regency. The primary challenge faced by farmers is the low level of productivity and efficiency in their production. This study aims to analyze the efficiency model of shallot farms in Karo Regency and identify the factors influencing it, including the complex interaction between external factors (climate change), farmers' adaptive responses, and existing socioeconomic structures. The methods employed are a combination of qualitative and quantitative approaches, including surveys and in-depth interviews. Data analysis will use the Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), and Tobit regression models. The expected results can provide a comprehensive understanding of the sustainability of shallot farming and offer integrated policy recommendations for local governments, extension workers, and farmers.
Urban Area Design in the Arrangement of Smart Drainage Systems with IoT Technology (IoT) to Overcome Flooding in Urban Areas Tarigan, Ruth Riah Ate; Supiyandi, Supiyandi; Lubis, Najla; Hasanuddin, Muhammad; Khodijah, Siti; Atika Rizki, Cindy
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.9

Abstract

Flooding is a major problem that frequently occurs in Medan City due to high rainfall, dense settlements, and limited drainage system capacity. Conventional drainage planning still faces obstacles in real-time monitoring of channel conditions, resulting in less than optimal flood management responses. This study aims to examine the use of Internet of Things (IoT) technology in planning a smart drainage system as a flood mitigation effort in Medan City. The research method was carried out through literature review, conceptual modeling, and analysis of IoT infrastructure needs, including water level sensors, data communication devices, and integration with geographic information systems (GIS). The results of the study indicate that the implementation of an IoT-based drainage system can improve the effectiveness of water flow monitoring, support rapid decision-making in flood control, and provide accurate spatial data for urban spatial planning. In conclusion, the use of IoT has great potential to support the development of a smart drainage system in Medan City, thereby reducing flood risk and increasing the resilience of urban infrastructure in a sustainable manner.
Implementation Of Loose Parts of Media In Literacy Learning in Early Childhood Education Rozana, Salma; Widya, Rika; Ependi, Rustam; Yanti, Nursaida
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.10

Abstract

Literacy education at an early age is crucial in laying the foundation for children's reading and writing skills. However, conventional learning methods are often less attractive and do not align with the characteristics of early childhood development. Loose parts, which are open-ended materials that can be manipulated freely, offer an innovative approach that allows children to explore literacy in a creative way. This study aims to explore the effectiveness of using loose media parts in improving early childhood literacy skills, as well as identify challenges in their implementation. This study employs a qualitative approach, utilizing a case study method, which was conducted in three Pendidikan Anak Usia Dini (PAUD) that have implemented loose parts-based learning. Data were collected through participatory observation, in-depth interviews with five early childhood education teachers, and analysis of children's artefacts. Thematic analysis techniques are employed to identify the primary patterns in the utilization of loose parts in literacy learning. This study concludes that loose parts effectively enhance children's involvement and creativity in literacy learning during early childhood education, particularly in the stage of letter and word recognition. However, for the optimization of implementation, further support is needed in the aspects of planning, teacher training, and parent involvement. The primary recommendations of this study are the development of guidelines for implementing loose parts in early childhood literacy, enhancing teacher training, and strengthening the role of parents in supporting the exploration of loose parts within the home environment.
Fundamental Models of Digital Stimulus on Consumer Purchasing Decisions: Implications For AI-Based Marketing Strategies and The Digital Economy Nasution, Umar Hamdan; Zahri, Cut; Rahman, M. Arif
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.11

Abstract

This research aims to develop a fundamental model that links digital stimulus to consumer purchasing decisions, with AI-based marketing strategies as a moderator variable. The development of digital technology has revolutionized consumer behavior in the purchase decision-making process. Digital stimuli, such as personalized advertising, artificial intelligence-based interactions (including chatbots and virtual assistants), automated product recommendations, and interactive UI/UX designs, are increasingly influencing consumer preferences. However, research that comprehensively examines the relationship between digital stimulus, AI-based marketing strategies, and purchasing decisions is still limited, especially in Indonesia. The novelty of this research lies in the integration of consumer behavior analysis with machine learning approaches to validate prediction models of purchase decisions. The method employed was a survey of 420 active digital consumers, followed by Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis and algorithmic validation using Random Forest and Gradient Boosting. The results show that personalized advertising and UI/UX design have a significant positive effect on purchase intent, which is further the primary determinant of purchase decisions. Machine learning-based pricing strategies have been demonstrated to enhance the effectiveness of personalized advertising. At the same time, AI interactions, product recommendations, sentiment analysis, and customer engagement moderation are not significant. Algorithmic validation confirms a very high prediction accuracy (96.9%–98.3%), indicating that the model reliably maps the behavior patterns of digital consumers. Theoretically, this study enriches the literature on digital consumer behavior while providing practical recommendations for e-commerce to optimize ad personalization, enhance UI/UX design, and leverage AI-based pricing strategies. The implications of this research are also relevant for regulators in strengthening ethical policies and developing the national digital economy ecosystem

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