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All Journal Publikasi Pendidikan Widyagogik : Jurnal Pendidikan dan Pembelajaran Sekolah Dasar Nusantara of Research : Jurnal Hasil-hasil penelitian Universitas Nusantara PGRI Kediri (e-journal) Jurnal Bimbingan dan Konseling Terapan Jurnal Penelitian Pendidikan IPA (JPPIPA) Mimbar Ilmu Psikologi Konseling: Jurnal Kajian Psikologi dan Konseling Bulletin of Counseling and Psychotherapy ProGCouns: Journal of Professionals in Guidance and Counseling Indonesian Journal of Counseling and Development International Journal of Applied Counseling and Social Sciences JPOL: Journal of Pedagogy and Online Learning Madani: Multidisciplinary Scientific Journal Mahir : Jurnal Ilmu Pendidikan dan Pembelajaran Indonesian Counseling and Psychology Algebra Router : Jurnal Teknik Informatika dan Terapan Router : Jurnal Teknik Informatika dan Terapan JITCoS : Journal of Information Technology and Computer System Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Nasution, Salsabila
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Physics Public Health Social Sciences Other

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Identifikasi Tingkat Kecenderungan Perilaku Adiktif Mahasiswa Generasi Z Erwita, Erwita Ika; Ginting, Rafael Lisinus; Aisyah, Fadinda; Nasution, Salsabila
PSIKOLOGI KONSELING Vol. 19 No. 2 (2025): Jurnal Psikologi Konseling
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In today's digital era, the tendency of addiction to technology, social media, and certain substances is increasing, which has the potential to harm the well-being of students. This study aims to identify the level of addictive behavior tendencies in students at Medan city, focusing on two main factors: individual predisposition and specific areas of addiction. Through a descriptive quantitative approach, data were collected from 491 students using a questionnaire that measured addictive tendencies based on various variables, including learning patterns, emotional regulation, impulsivity, and addictive behaviors related to technology, drugs, gambling, and pornography. The results showed that Internet & Technology was the domain with the highest addiction tendencies (M = 17.44), followed by emotional regulation (M = 15.86). Although addiction to Cigarettes, Alcohol, and Drugs showed the lowest mean value (M = 9.53), the high kurtosis value indicates the presence of a group of students with very high addiction. On the other hand, psychological factors such as Impulsivity and low Executive Function contribute to impulsive decision-making that exacerbates addictive behavior. This study recommends the development of more holistic prevention and intervention programs, including enhanced guidance and counseling services and effective coping skills training, to help college students overcome addictive behaviors and improve their psychological well-being.
Validity and Reliability of the Objective Measure of Ego Identity Status Adaptation: The Rasch Model Approach Umar, Nur Fadhilah; Syahril, M. Fiqri; Nasution, Salsabila; Ardis, Nurfaidah; azzahrah, Humairah; Rafli, Muhammad
Bulletin of Counseling and Psychotherapy Vol. 7 No. 3 (2025): Bulletin of Counseling and Psychotherapy
Publisher : Kuras Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51214/002025071583000

Abstract

Ego identity plays a crucial role in shaping an individual’s self-concept, career decisions, and social relationships. Accurately measuring ego identity status is essential for understanding identity formation and promoting healthy psychological development. This study examines the validity and reliability of the adapted Objective Measure of Ego Identity Status (OMEIS) using the Rasch Model, a contemporary psychometric approach that enhances measurement precision. A sample of 431 university students participated in this study, with data collected through an online questionnaire. Rasch analysis was employed to assess item fit, rating scale effectiveness, person reliability, and item difficulty levels. The results indicate that the adapted OMEIS demonstrates strong structural validity and high item reliability (0.99), although person reliability (0.63) requires improvement. The Wright Map analysis confirms the instrument’s ability to capture variations in ego identity, while item difficulty analysis highlights areas for potential refinement. Findings suggest that the Rasch Model provides a robust framework for validating psychological instruments, ensuring their applicability across diverse populations. This study contributes to the refinement of identity measurement tools and underscores the importance of advanced psychometric methodologies in psychological research
Penerapan Metode Segmentasi Warna HSV untuk Deteksi Objek Berbasis Warna pada Citra Digital Rizka Rizka; Nasution, Salsabila; Aulia, Fatwa; Supiyandi Supiyandi
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 4 (2025): Desember : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i4.706

Abstract

This study discusses the application of the HSV color segmentation method for color-based object detection in digital images. The data used consist of digital images in JPG, PNG, or WebP format containing various colored objects, including red tomatoes, yellow bananas, green apples, orange oranges, purple akebia, brown sapodilla, and blue blueberries. The research process involves converting images from BGR to HSV, determining HSV ranges for each color, creating masks, performing segmentation, analyzing pixels, detecting contours, and visualizing results using bounding boxes. The results show that the HSV method effectively detects objects, separates them from the background, and provides quantitative information, including pixel count, area percentage, and average HSV values for each color. Red, yellow, green, orange, purple, brown, and blue colors were successfully segmented, displaying clear and accurate objects, both for single and multiple objects, under various sizes and lighting conditions. These findings confirm that the HSV method is a simple, fast, and effective approach for color-based image analysis.
Parking Route Modeling Using the A* Algorithm for Density Reduction at the Faculty of Science and Technology, State Islamic University of North Sumatra Berutu, Asro Hayati; Nasution, Salsabila; Rahmadani, Suci
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Volume 1 Number 2, December 2025
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.46

Abstract

The increasing number of vehicles on university campuses has led to significant congestion, particularly around parking areas. This study aims to design an intelligent parking route model using the Density-Aware A* algorithm to minimize vehicle congestion within the Faculty of Science and Technology (FST) at UIN North Sumatra. The proposed approach represents the internal campus network as a weighted graph, where each edge integrates both spatial distance and a density penalty that reflects the occupancy-to-capacity ratio of each parking area. The algorithm was implemented and simulated using Python and the NetworkX library within Google Colab. The results show that the system accurately identifies the optimal parking route based on vehicle type and real-time occupancy data. For motorcycles, the optimal path is A > B > F with a total cost of 23.06, while for cars, the most efficient path is A > B > H with a total cost of 18.21. The findings indicate that incorporating density-based cost adjustments effectively balances travel efficiency and vehicle distribution, contributing to overall congestion reduction in the FST–FKM corridor. Future research should focus on integrating live sensor data and adaptive feedback mechanisms to support large-scale deployment across diverse campus environments.
Co-Authors Adha, Idyana Afdal Afdal, Afdal Aisyah, Fadinda Al-Mitsaq, Hafiz Ali Amran ardis, nurfaidah Aulia, Fatwa Azzahrah, Humairah Berutu, Asro Hayati Daharnis Daharnis Dina Sukma Firman Firman Firman Fitriani, Auliah Ginting, Rafael Lisinus Hairani, Mutiara Haq, Olim Zul Ilmil Harahap, Salsabilah Hariko, Rezki Hasibuan, Nurharisyah Husna, Assaidatul Ifdil Jamaris Jamaris Jannah, Raudha Nur Hidayah Al Karleni, Yeni Krismona, Elwas Berdha Kurniady, Dedy Lubis, Ramadan Nasir, Ehsan Netrawati, Netrawati Neviyarni, Neviyarni Nugraha, Summed P Nursyafitri, Dila Pawira, Elsa Adinda Suci Sugi Putra, Ade Herdian Rafli, Muhammad Rahayu, Arum Dewi Raisardhi, Abid Ramadhan, Roni Hikmah Rizka Rizka Salsabila, Nasywa Siregar, Esli Zuraidah Sitepu, Fatimah Azzahra Solfema Suci Rahmadani Sufyarma Marsidin Suhaili, Neviyarni Supiyandi Supiyandi Syahril, M Fiqri Syahril, M. Fiqri Umar, Nur Fadhilah Violina, Erwita Ika Wahyu Almizri Yeni Karneli Zadrian Ardi Zakki, Ahmad Zaky, Naufal