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All Journal Coding: Jurnal Komputer dan Aplikasi Jurnal TIMES CESS (Journal of Computer Engineering, System and Science) JURNAL MEDIA INFORMATIKA BUDIDARMA Jusikom : Jurnal Sistem Komputer Musirawas JMM (Jurnal Masyarakat Mandiri) IRJE (Indonesian Research Journal in Education) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JURNAL PENDIDIKAN TAMBUSAI JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH JUSIM (Jurnal Sistem Informasi Musirawas) Building of Informatics, Technology and Science Journal of English Education and Teaching (JEET) JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL MAHAJANA INFORMASI Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat International Journal of Advances in Data and Information Systems Journal Zetroem Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Bulletin of Computer Science Research Instal : Jurnal Komputer Bulletin of Information Technology (BIT) Jurnal Minfo Polgan (JMP) Jurnal Nasional Teknologi Komputer PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Sistem Pendukung Keputusan dengan Aplikasi Jurnal Sistim Informasi dan Teknologi Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) International Conference on Sciences Development and Technology Al-Manaj International Journal of Information System & Innovative Technology Innovative: Journal Of Social Science Research JURNAL PENDIDIKAN DAN KEGURUAN Jurnal Manajemen Sistem Informasi Communication and Information Journal Jurnal Pendidikan dan Ilmu Sosial Journal Of Informatics And Busisnes Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Kendali Teknik dan Sains JRIIN :Jurnal Riset Informatika dan Inovasi Jurnal Penelitian Teknologi Informasi dan Sains Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi International Journal of Language and Ubiquitous Learning Jurnal Testing dan Implementasi Sistem Informasi Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Ignite: Journal Islamic Global Network for Information Technology and Entrepreneurship Jurnal Ilmiah Informatika dan Komputer International Journal of Information System and Innovative Technology Journal of Computer Science Artificial Intelligence and Communications Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Pengabdian Masyarakat Berdampak Journal of Electrical Engineering Research Router : Jurnal Teknik Informatika dan Terapan Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik Dan Multi-disiplin Ilmu Jurnal Pendidikan Agama Islam
Supiyandi Supiyandi
Universitas Pembangunan Panca Budi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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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.
Data Analysis Utilization of Land Use Land Cover Investigates Spatiotemporal Trends and Their Effects on Ecosystems Supiyandi, Supiyandi; Binti Mailok, Ramlah
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.v1.13

Abstract

Land use and land cover (LULC) have become a principal catalyst of ecological transformation, significantly affecting biodiversity, ecosystem services, and climate systems. Since 1960, anthropogenic activities such as urbanization, deforestation, and agricultural expansion have transformed more than 32% of the Earth’s surface, threatening ecological stability. In Batubara District, North Sumatra Province, Indonesia, rapid land-use transformations have raised concerns about environmental sustainability. This study aims to analyze the spatiotemporal patterns of LULC and evaluate their impacts on ecosystems in Batubara District, providing insights for sustainable land management and policy formulation. A quantitative approach was employed, utilizing remote sensing data from Landsat and Sentinel satellites, and integrated with GIS tools. Regression and sensitivity analyses were conducted to identify drivers of land use change and assess potential policy scenarios. A stratified random sample ensured representation across various land use types. The findings reveal significant land conversion driven by population growth and resource extraction, resulting in habitat fragmentation, reduced carbon sequestration capacity, and disruption of hydrological cycles. Urban expansion and deforestation were identified as major contributors to declining ecological connectivity and biodiversity loss. Sensitivity analysis further highlighted that inconsistent land management policies and climate variability hinder effective environmental planning and predictive modeling. This study highlights the pressing necessity for integration and adaptive land-use planning that incorporates spatiotemporal data and policy frameworks. The results provide actionable knowledge to support biodiversity conservation, enhance climate resilience, and promote sustainable development in rapidly transforming landscapes, such as Batubara District.
The Role of Brand Trust and Social Media Engagement in Driving Purchase Intention among Indonesian SMEs Amin, Muhammad; Hasanuddin, Muhammad; Supiyandi
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.v1.18

Abstract

The study investigates the influence of digital marketing strategies—social media engagement, online advertising, and brand trust—on consumer purchase intention in Indonesia’s SME sector. Using a quantitative design, data were collected from 150 SME consumers via structured online questionnaires and analyzed through multiple regression using SPSS 26.0. The model explained 65.7% of the variance in purchase intention, indicating a strong predictive capacity. Results revealed that all three independent variables significantly affect purchase intention, with brand trust emerging as the most influential predictor. The findings underscore that trust, transparency, and interactive engagement are essential in transforming digital exposure into purchasing behavior. Moreover, they highlight the necessity for SMEs to integrate ethical governance and culturally aligned digital communication to strengthen customer relationships and brand credibility. This research contributes to the literature by contextualizing digital marketing effectiveness within an emerging economy, offering theoretical insights and practical recommendations for designing trust-based digital strategies. The study’s implications encourage further exploration of mediating and moderating factors, such as consumer satisfaction and perceived risk, to deepen understanding of behavioral mechanisms in digital markets.
Analysis of User Interaction Association Patterns in E-Learning Systems Using the Apriori Algorithm Rizka; Berutu, Asro Hayati; Nabawy, Putri; Pratama, Haris; Supiyandi
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.v1.30

Abstract

The development of e-learning systems has generated a vast volume of user interaction data. Every activity—such as logging in, viewing materials, taking quizzes, and downloading assignments—contains valuable information that can be leveraged to enhance the effectiveness of online learning systems. This study aims to analyze user interaction association patterns in an e-learning system using the Apriori algorithm. A data mining approach was employed to identify relationships among features frequently accessed together, with a minimum support threshold of 0.4, minimum confidence of 0.6, and lift > 1.0. The dataset used consists of simulated (dummy) data representing seven user transactions and five main e-learning features. The analysis produced eight significant association rules with lift values above 1.0, indicating non-random relationships among features. Feature combinations such as {login} → {view_material} and {take_quiz} → {view_score} exhibited strong relationships, with confidence values reaching 0.75. These findings suggest the existence of dominant user interaction patterns that can be utilized to optimize navigation design, recommendation features, and overall user experience in e-learning systems. This research contributes to the application of the Apriori algorithm for exploring user access patterns in online education contexts, providing an analytical foundation for developing more adaptive and behavior-driven systems.
Sentiment Analysis of Reviews from Google Play: Azur Lane, Genshin Impact, Arknights Siregar, Kardandi Alfarizi; Cahyadi, Bhagaskara; Samosir, Legiman; Azhard, Alfani; Supiyandi
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.v1.33

Abstract

Sentiment analysis of user reviews for mobile games is essential for understanding player perceptions of a game. This study focuses on sentiment analysis of user reviews for three popular mobile games: Azur Lane, Genshin Impact, and Arknights, using the Support Vector Machine (SVM) algorithm. The objective of this research is to classify reviews into three sentiment categories: Positive, Negative, and Neutral. Data was collected through web scraping from the Google Play Store, with a total of 6,000 reviews analyzed. The data preprocessing steps included cleaning, tokenization, stopword removal, and stemming, followed by TF-IDF feature extraction. The results show that the SVM model achieved an accuracy of 79.50%, with the best performance for Positive and Negative sentiments, but struggled with Neutral sentiment classification. The sentiment distribution revealed that Azur Lane had a higher proportion of Negative reviews compared to Genshin Impact and Arknights, which received predominantly Positive feedback. This study provides insights into the potential of using SVM for sentiment analysis in mobile games, and highlights areas for improvement, such as better handling of Neutral sentiment through more advanced models or balanced datasets.
Measuring IT-Business Strategic Alignment in Indonesian Digital Start-ups Fachri, Barany; Iqbal, Muhammad; Supiyandi; Hasanuddin, Muhammad
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.v1.34

Abstract

This study investigates the level of strategic alignment between Information Technology (IT) and business in digital start-ups across Java, Indonesia, using Luftman’s Strategic Alignment Maturity (SAM) model as the primary analytical framework. A mixed-methods approach was employed, combining quantitative data from structured questionnaires with qualitative insights from interviews involving supervisors from IT and business divisions. The findings indicate that digital start-ups have achieved a moderate level of alignment maturity, corresponding to the Established Focused Process stage, with an average score of 3.45. Partnership and technology scope emerged as the most mature domains, demonstrating effective collaboration and technological adaptability. In contrast, governance and competency measurement were identified as areas requiring significant improvement. The results highlight that alignment in these organizations is largely driven by informal relationships, entrepreneurial culture, and shared innovation values rather than by formal governance systems. Strengthening IT governance, implementing structured performance metrics, and promoting cross-functional skill development are recommended to advance alignment maturity. This research contributes to the broader understanding of IT-business integration in emerging digital economies and provides a practical framework for improving strategic coherence and organizational performance in start-up environments.  
Application of Machine Learning in Computer Hardware Failure Detection Systems Irwan, Irwan; Supiyandi, Supiyandi; Rizal, Chairul
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.v1.71

Abstract

The rapid advancement of computer systems has increased the complexity and performance demands of computer hardware, leading to higher risks of hardware failure. Early detection of hardware faults is crucial to ensure system reliability, reduce downtime, and minimize maintenance costs. This proceeding discusses the application of Machine Learning (ML) techniques in computer hardware failure detection systems as an intelligent and adaptive solution. Machine Learning enables automated analysis of large volumes of hardware monitoring data, such as temperature, voltage, power consumption, and error logs, to identify patterns that indicate potential failures. Various ML approaches, including supervised learning, unsupervised learning, and anomaly detection methods, can be utilized to predict hardware malfunctions before critical failures occur. Compared to traditional rule based monitoring systems, ML based detection systems offer higher accuracy, scalability, and the ability to adapt to dynamic hardware environments. Furthermore, the integration of Machine Learning with hardware sensors and monitoring tools enhances real time fault detection and supports predictive maintenance strategies. This paper highlights the role, advantages, and challenges of applying Machine Learning in computer hardware failure detection systems, including issues related to data quality, model interpretability, and computational overhead. Overall, the application of Machine Learning provides a promising approach to improving the reliability and efficiency of modern computer hardware systems.
Co-Authors AA Sudharmawan, AA Abdul Karim Abdul Kholik Abil Alwi Prayoga Adisty Maysandra Agus Priawan Aidil Halim Lubis Aidil Halim Lubis Aisyah, Adinda Putri Akhiryani, Atna Aldri Frinaldi Almanna Hussein Amelia, Nanda Aminuddin Indra Permana Andhika Fisryansah Ahlief Putra Andriana, Melly Andriani Sitorus Andry Wiranda Hakiki Andysah Putera Utama Siahaan Anggi Jelita Sitepu Anita Yulistia Aprilia, Anggita Arizka Anggraini Armasari, Selly Arrahma, Syahrani Asih, Munjiat Setiani Atika Rizki, Cindy Awaluddin Nasution Ayu Nafis Azhard, Alfani Azzahra, Shafa Marwah bagus dwi nugraha Barany Fachri Basyir, Muhammad Khalidin Batubara, Raihan Syafawi Benni Ichsanda Rahman Hz Berutu, Asro Hayati Berutu, Nurhalijah Binti Mailok, Ramlah Buyung Solihin Hasugian Cahyadi, Bhagaskara Chairul rizal Chairul Rizal Chairul Rizal Chatarina Umbul Wahyuni Cindy Atika Rizki Cindy Atika Rizki Cindya Putri Hidayat Siregar Dafa Ikhwanu Shafa Dafa Ikhwanu Shafa Damanik, M. Zidan Damayanti, Fera Darbin Silaban Darmansyah, Dandi Darmawan Napitupulu Dedek Juliani Ritonga Deni Apriadi Dian Kurnia Dinah Makhroza Silalahi Donny Dwi Putra Dwi Citra Tarcilia Br Berutu Dwi Prapita Sari Eka Putra Eka, Muhammad Eka, Muhammad Eko Hariyanto Ermaliza Evra Tiara Syahputri Fachri, Barany Fadhil, Muhammad Syaban Fahmi Zahary Fahraini, Fakhita Fahrizal, Deni Fajar Ryanda Fasya, Muhammad Rezeki Fatwa Aulia Fauzi Bima Ramadhan Fauzi Kurniawan Febrian, Alvin Fikri Aditiya Sitorus Firda Mei Amandaa Firtiani, Ade Irda Gehan Hasibuan Ginting, Giovany Ginting, Risdawati Gita Aulia Grase Latifah Sibuea Gultom, Imeldawaty Hafizh Sallam Hakim Gilangkara Hamdi Handoko, Divi Harahap, Ardhansyah Putra Harun Al Rasyid Havni Virul Hendry Hendry Hermansyah Hermansyah Hermansyah Hidayah, Adinda Fita Hotmaidah Harahap Ibnu Faisal Icha Miranti Irzan Ilka Zufria Inneke Putri Irfan Azhar Gurning, Muhammad Irfan Sarif, Muhammad Irwan Irwan Gunawan Irwan Irwan Ismahani , Siti J. Prayoga Jiddan, Jayyid Jonhuneddi, Ridho Defvin Ananda Julyanda, Rizki Jundi Haqqoni Khairul Azis Khairuniza, Nabila Khalidy, Furqan Kiki Widya Pratiwi Latifa Khoirani Latifa Khoirani Leni Marlina Lia Kristina , Manalu Lili Wilandari LINDA WAHYUNI Lingga, Cindy Valentina Lisa Amelia Putri Lubis, Najla Luthfiah Azzahra Irhanda Luthfie Budie M Khori Pratama Mailok, Ramlah Binti Malau, Sebastian Veron Manalu Lia Kristina Martiman Suazisiwa Sarumaha Mesran, Mesran Mhd Murini Ramadhani Mochammad Imron Awalludin Mohammad Yusup Mohammad Yusup Mona Donaon Muhammad Abdul Mujib Muhammad Alfariz Rasyid Muhammad Alfariz Rasyid Muhammad Alfariz Rasyid Muhammad Amin Muhammad Eka Muhammad Eka Muhammad Eka Muhammad Eka Muhammad Eka Muhammad Eka Muhammad Evan Jinanda Muhammad Fajrotu Syahri Dalimunthe Muhammad Farhan Muhammad Habib Muhammad Hasanuddin Muhammad Hasanuddin Muhammad Hasanuddin, Muhammad Muhammad Ikhsan Muhammad Iqbal Muhammad Iqbal Muhammad Irfan Sarif Muhammad Israr Fathoni Muhammad Noor Hasan Siregar Muhammad Siddik Hasibuan Muhammad Syahuda Hasibuan Muhammad Yusuf Azmi Muhammad Zen Muhammad Zen, Muhammad Munadi Munadi Nabawy, Putri Nabila Intan Zahrani Nasution, Yusuf Ramadhan Nasution, Yusuf Ramadhan Natria Selina Nazwa Aliya Muthmainnah Hsb Nazwa Alya Faradita Nuranisah Nuranisah Nurjannah Hasibuan Nurul Fitriah Nuzul Ramadhan Paranindra Ardhana Biroe Aurori Pasaribu, Saddam Husen Romadon Pasi, Ramadhana Pramudya, Farhan Amar Pratama, Haris Pratama, M. Khoiri Putra, Donny Dwi Putra, Randi Rian Putri Andini, Putri Putri, Dinda Wijaya Rafif Rasendriya Rahim, Fitra Rahmadani Rahmadani Rahmadani Rahmadani Rahmat Abdillah Rasendriya, Rafif Rebecca Evelyn Laiya Ricky Ramadhan Harahap Rino Ariansyah Rino Ariansyah Risma Hidayati Rismayanti Rismayanti Rizal, Chairul Rizka Rizki, Cindy Atika Rizky Vita Losi Rondi Sahputra Darmono Rosa Prahasti Rusmin Saragih, Rusmin Ruth Riah Ate Tarigan Safrizal Barus Saidi Ramadan Siregar Salsa Nabila Iskandar Salsabila Nasution Salsabila Yusra Samosir, Legiman Samsul Maarif Aceh Sanjaya, Dian Saprina Putri Utama Ritonga Sari, Anggy Permata Sari, Dwi Prapita Sarip, Mohammad Sepriana Nurliani Sidik, Jafar Silalahi, Dinah Makhroza Siregar, Ina Namora Putri Siregar, Kardandi Alfarizi Sitha, Nur Syifa'u Siti Dian Siti Khodijah Siti Khodijah Siti Sundari Sri Putri Balqis Sri Ratna Dewi suci ramadhani Surbakti, Ferdiyansyah Suryanda, Daniel Suyitno Suyitno Syahada Mawarda Hutagalung Syahada Mawarda Hutagalung Syahada Mawarda Hutagalung Syahida, Silmi Syahputra, Zulfahmi Syamsul Arifin Syawaliah Putri Rangkuti Tanjung, Agung Hafizh Tegar Ardiansyah Triguna, Aalhafis Aden Trisatin Panggabean Try Widyawanti Vera Meikana Sitorus Wahyu Eka Judistira Wahyudi, Farhan Rizky Waldana, Fadhil Warda Hamidah Wasito, Muhammad Wicaksono, Aldi William Lutfi Rahman Harjo Yessi Fitri Annisah Lubis Yusril Burhani Batubara Yusuf Ramadhan Nasutiion Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Yusup, Mohammad Zul fiqr Zulfahmi Syahputra Zulham Zulham