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Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Published by Asosiasi Riset Ilmu Matematika dan Sains Indonesia
ISSN : 30326249     EISSN : 30465419     DOI : 10.62383
Core Subject : Science,
Computer Science & IT
Jurnal ini adalah jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam yang bersifat peer-review dan terbuka. Bidang kajian dalam jurnal ini termasuk sub rumpun Ilmu Komputer, dan Ilmu Pengertahuan Alam.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 112 Documents
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Evaluasi Efektivitas Model Klasifikasi Sentimen untuk Analisis Opini Publik terhadap Kebijakan Lingkungan Berdasarkan Data Media Sosial Berbahasa Indonesia Dada Suhaida; Adisti Primi Wulan; Rosanti Rosanti; Dianna Dianna
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 2 No. 2 (2024): Maret: Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v2i2.951

Abstract

Background: Public opinion analysis has become increasingly important in the digital era, where social media platforms generate large-scale textual data reflecting public perceptions toward environmental policies. Advances in Natural language processing (NLP) and machine learning enable systematic sentiment classification to support data-driven decision-making. Objective: This study aims to evaluate the effectiveness of several sentiment classification models in analyzing Indonesian-language social media data related to environmental policies. Method: The research employed a text mining pipeline including data crawling, preprocessing (case folding, tokenization, stopword removal, and stemming), and vectorization using TF-IDF. Three classification models Logistic Regression, Support Vector Machine (SVM), and Long Short-Term Memory (LSTM) were trained and evaluated using accuracy and F1-score metrics. Results: Experimental findings indicate that LSTM achieved the highest performance with 91.7% accuracy and 91.2% F1-score, outperforming SVM (88.5%) and Logistic Regression (84.2%). Sentiment distribution analysis shows that public opinion is dominated by positive sentiment (47.5%), followed by neutral (32.0%) and negative (20.5%). Overall: The results demonstrate that deep learning-based models provide more robust contextual understanding and more reliable sentiment mapping for environmental policy analysis.
Sistem Pendukung Keputusan Seleksi Penerimaan Karyawan Baru di Winmart Menggunakan Metode Seleksi Berbasis Web Herlina Baro Lolu; Andreas Ariyanto Rangga; Paulus Mikku Ate
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 2 (2026): Maret: Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i2.955

Abstract

The selection process for accepting new employees is one of the important stages in a company to ensure that the candidates accepted have qualifications that suit the company's needs. At WINMART, the selection process is still carried out manually, so it is less efficient and prone to errors. Therefore, a system is needed that can assist in more objective and efficient decision making. This Decision Support System (DSS) is designed to assist the selection process for recruiting new employees using the Simple Additive Weighting (SAW) method, which can assess several relevant criteria, such as work experience, education, skills and competency tests. This system was built on a web basis, so it can be easily accessed by parties involved in the selection process, such as HRD and managers. The SAW method was chosen because of its ability to convert various subjective criteria into more objective numerical scores, so that selection results can be more transparent and accountable. By using this system, it is hoped that it can increase efficiency, accuracy and transparency in the new employee selection process at WINMART, as well as facilitate decision making in selecting candidates who best suit the desired criteria.
Penerapan Algoritma Dijkstra dalam Optimasi Rute Terpendek dari Stasiun Kereta Api Medan ke Universitas Negeri Medan Nazwa Salsyabilla Ramadhani; Juliana Gloria Br. Sipayung; Maria Winarni Br Silitonga; Mika Monika Fransiska Simanullang
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 3 (2026): Mei : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i3.961

Abstract

The increasing complexity of urban transportation systems demands intelligent and measurable navigation methods. Medan City, the capital of North Sumatra Province, has a dense road network with multiple route options that often confuse road users. Dijkstra's Algorithm, developed by Edsger Wybe Dijkstra in 1959, is a greedy-based computational approach proven effective for solving the shortest path problem on non-negative weighted graphs. This study applies Dijkstra's Algorithm to determine the shortest route from Medan Railway Station to Universitas Negeri Medan (UNIMED). The road network was modeled as an undirected weighted graph with 15 nodes and 16 edges, where edge weights represent actual road distances measured via Google Maps. The graph has a density of 0.152, confirming its sparse graph characteristic. Three alternative routes were identified and analyzed. The algorithm was implemented in Python 3 using the heapq module as a priority queue. Results show that the optimal route is A → B → C → E → F → M → N → O via Jl. M.T. Haryono, Jl. Aipda KS Tubun, Jl. Madong Lubis, and Jl. Prof. H.M. Yamin, with a total distance of 6.64 km. This achieves 99.1% accuracy compared to Google Maps, with a deviation of only 0.06 km. The optimal route is 6.25% more efficient than Alternative Route 1 (7.30 km) and 11.9% more efficient than Alternative Route 2 (7.54 km). The algorithm executes in under 1 millisecond with time complexity O((V+E) log V). These findings confirm Dijkstra's Algorithm as highly effective for medium-scale urban road network optimization.
Reconceptualizing Student Agency in AI-Supported STEM Learning: A Qualitative Study of Autonomy, Regulation, and Dependency Nofamataro Zebua
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 2 (2026): Maret: Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i2.962

Abstract

This study explores student agency in Artificial Intelligence (AI)-supported STEM learning environments, addressing a critical gap in existing literature that predominantly focuses on learning outcomes rather than learner-centered processes. Drawing on an interpretive qualitative approach, this research investigates how students experience autonomy, self-regulation, and decision-making when interacting with AI technologies in STEM education. Data were collected from 15 participants engaged in AI-supported learning through in-depth semi-structured interviews, supported by observations and document analysis. The data were analyzed using thematic analysis to identify recurring patterns and meanings related to student agency. The findings reveal that student agency is a dynamic and multidimensional construct shaped by the interplay between technological affordances and learner engagement. Four major themes emerged: enhanced autonomy, development of self-regulated learning, negotiated decision-making, and ambivalent dependency on AI. While AI technologies provide adaptive support that empowers students to take control of their learning, they also introduce the risk of over-reliance, which may reduce cognitive engagement. This study contributes to the theoretical advancement of student agency by conceptualizing it as a spectrum rather than a fixed attribute, highlighting the dual role of AI as both an enabler and a constraint. The findings offer important pedagogical implications for designing AI-supported STEM learning environments that promote active, reflective, and responsible learning. Future research is recommended to explore this phenomenon across diverse contexts and through longitudinal designs.
Navigasi Privasi di Era Digital: Peran Kesadaran Pengguna dalam Mitigasi Kebocoran Informasi di Media Sosial Zahra Azkiya; Evy Nurmiati
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 3 (2026): Mei : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i3.968

Abstract

The rapid digitalization in Indonesia, reaching 180 million active social media users, has not been accompanied by adequate security system resilience, thereby triggering massive data breach risks. This study aims to analyze the privacy navigation mechanisms of the digital society as an instrument for mitigating information leaks. The method used is descriptive qualitative with a literature study (library research) approach, which examines primary and secondary literature related to regulations, digital behavior, and user psychological factors. The research findings indicate that privacy navigation in the digital era has not operated optimally due to the dominance of social existence needs, which triggers the privacy paradox phenomenon. Although users possess knowledge regarding cyber risks, the desire for social validation through self-disclosure often overrides technical protection logic. The practice of using secondary accounts (second accounts) was found to be a form of manual navigation, yet its effectiveness remains dependent on individual digital literacy. The implications of this research emphasize that mitigating information leaks requires the integration of critical user awareness, platform governance transparency, and consistent law enforcement through the PDP Law. Digital awareness must transform into reflexive protective behavior to maintain informational sovereignty in cyberspace.  
Rancang Bangun Sistem Pendeteksi Kebocoran Gas Elpiji Berbasis Internet Of Things Menggunakan Esp32 Rudi Hermawan; Mudjianto Mudjianto
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 3 (2026): Mei : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i3.1033

Abstract

Liquefied Petroleum Gas (LPG) is one of the most widely used energy sources in households and small industries. However, gas leakage often becomes a major cause of fires and explosions due to delayed detection. Therefore, an early warning system capable of detecting LPG leaks in real time is required. This research aims to design and implement an Internet of Things (IoT)-based LPG gas leak detection system using the ESP32 microcontroller. The system utilizes the MQ-2 gas sensor to detect LPG concentration in the surrounding environment. When the detected gas concentration exceeds the specified threshold, the system activates a buzzer alarm, displays warning information on an Android smartphone, and sends monitoring data through the internet. The research method employed is the Waterfall model, consisting of requirements analysis, system design, implementation, testing, and maintenance. System testing was carried out using the Black Box Testing method to verify the functionality of each component. The results indicate that the developed system successfully detects LPG gas leakage, provides early warning notifications, and performs real-time monitoring through smartphone devices. This system is expected to improve household safety and minimize fire hazards caused by LPG gas leaks.
Kajian Perkembangan Sistem Saraf Pusat pada Mus musculus Yafitriani Loi; Nailla Ramadani; Cinta Serlina; Bunga Deli Anjani; Jodion Siburian; Afreni Hamidah; Desfaur Natalia
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 4 (2026): Juli : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i4.992

Abstract

The development of the central nervous system in Mus musculus is a complex biological process that occurs through several stages, including neurulation, neuronal proliferation, neuronal migration, neuronal differentiation, neurogenesis, and synaptogenesis. This study aimed to explore the stages of central nervous system development in Mus musculus and the factors influencing them through a literature review approach. The method used was descriptive qualitative analysis based on scientific journals and books published between 20162026. The results showed that neurulation plays a role in forming the basic structure of the brain and spinal cord, while the stages of proliferation, migration, differentiation, and synaptogenesis contribute to the formation of neural networks and nervous system function. This process is influenced by genetic and environmental factors, including nutrition, hormones, stress, and exposure to chemical substances. The use of Mus musculus as an animal model has significantly contributed to the development of neurobiology and neurological health research.
Analisis Kualitas Butir Soal Materi Perubahan Wujud Zat Kelas IV SD Niken Ariyana Putri; Fina Fakhriyah; Eka Zuliana
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 4 (2026): Juli : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i4.1003

Abstract

The quality of test items is essential for producing accurate and reliable learning assessments. High-quality instruments not only measure students’ learning achievement but also provide valuable information for improving instructional practices. This study aimed to analyze the quality of essay test items on the topic of Changes in the States of Matter for fourth-grade elementary school students based on validity, reliability, difficulty level, and discrimination power. A quantitative descriptive method with an item analysis approach was employed. The participants were 22 fourth-grade students from a public elementary school in Pati Regency, Central Java. The instrument consisted of 20 essay questions administered during the second semester of the 2025/2026 academic year. Data were analyzed using Microsoft Excel to calculate validity coefficients, reliability coefficients, difficulty indices, and discrimination indices. The findings showed that 70% of the test items met the validity criteria, while 30% required revision. The reliability coefficient of 0.83 indicated high consistency of the instrument. Difficulty level analysis revealed that 80% of the items were easy, 10% were moderate, and 10% were difficult. The discrimination power analysis showed that 35% of the items were poor, 20% satisfactory, 30% good, and 15% excellent. Overall, the test items demonstrated adequate quality for classroom assessment. The findings suggest that revising items with low validity and discrimination power can improve the quality of assessment instruments, enabling teachers to evaluate students’ learning outcomes more accurately, objectively, and fairly.
Sistem Pendukung Keputusan Pemilihan Motor Bekas menggunakan Metode Weighted Product pada PT Sukses Motor Munajar Munajar; Khusnul Khotimah; Hanasa Shelviani; Imam Himawan; Aminah Aminah
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 3 (2026): Mei : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i3.1030

Abstract

This study presents the development of a decision support system to recommend the best used motorcycles for prospective buyers at PT. Sukses Motor. The system aims to provide faster, more accurate, and objective recommendations while improving customer service. The Weighted Product (WP) method was applied to evaluate motorcycle alternatives based on multiple criteria, including price, condition, production year, mileage, and buyer preferences. System development included requirements analysis, UML-based design, implementation using PHP and MySQL, and functional testing. Data were collected through interviews with sales staff and company records. The results show that the system successfully generates recommendation rankings that match buyer needs and preferences. In addition to identifying the most suitable motorcycle, the system provides several alternative recommendations, enabling buyers to compare available options before making a purchasing decision. The proposed system improves the efficiency and objectivity of the recommendation process and can serve as a reference for developing decision support systems in other multi-criteria decision-making applications.
Analisis Pengaruh Kualitas Layanan SIJARU FISIP UI terhadap Kepuasan Pengguna: Menggunakan Metode Webqual 4.0 Firmansyah Ruspandi; Eva Rahmawati; Sri Diantika
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 4 (2026): Juli : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i4.1032

Abstract

The Room Reservation Information System (SIJARU) is a crucial facility in supporting academic operations at FISIP UI. However, the effectiveness and service quality of this system need periodic evaluation to ensure user satisfaction. This study aims to analyze the influence of SIJARU's service quality on user satisfaction using the WebQual 4.0 method, which includes dimensions of usability, information quality, and service interaction quality. This study employed a quantitative approach with a survey of 100 respondents consisting of students, lecturers, and educational staff at FISIP UI. Data were processed using multiple linear regression techniques, preceded by validity, reliability, and classical assumption tests. The results indicate that usability, information quality, and service interaction quality simultaneously have a significant positive influence on user satisfaction, with an Adjusted R Square value of 92.7%. The conclusion of this study is that the service quality of SIJARU has provided high satisfaction to users; however, continuous system maintenance and development are required to maintain and improve service quality in the future.

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