cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Hasanuddin
Contact Email
cvraskhamediagroup@gmail.com
Phone
+6282362440765
Journal Mail Official
ikosstemi@gmail.com
Editorial Address
Jalan Gurilla No. 2 Sidorejo, Kec. Medan Tembung 20222
Location
Kota medan,
Sumatera utara
INDONESIA
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik Dan Multi-disiplin Ilmu
Published by CV. Raskha Media Group
ISSN : -     EISSN : 31232574     DOI : https://doi.org/10.64803/ikosstemi
Core Subject : Religion, Humanities, Science, Education, Engineering,
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu (IKOSSTEMI) dengen No. ISSN: 3123-2574 (online) merupakan salah satu kegiatan yang diselenggarakan oleh Raskha Media Group Publisher. Seminar Nasional IKOSSTEMI (Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu) dilaksanakan untuk memberikan dorongan kepada para Dosen, Mahasiswa, dan Penelitidalam melakukan publikasi di Forum Ilmiah Nasional dengan harapan manfaatnya dapat segera dirasakan masyarakat secara luas.
Arjuna Subject : Umum - Umum
Articles 13 Documents
 1   2 
Education on Green Computing Awareness at SMK Free Methodist Medan Saragih, Mas Uhur Abdillah; Nasution, Muhammad Zikri Al Hakim; Simatupang, Rizky Agung
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu Vol. 1 (2025)
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/ikosstemi.v1.86

Abstract

Green computing education was conducted at SMK Free Methodist Medan on March 25, 2024, to improve students’ understanding of environmentally friendly information technology practices. The main issue identified was the low awareness of energy consumption in ICT devices, electronic waste management, and efficient computing behavior. The purpose of this study is to evaluate the effectiveness of the education program using lectures, demonstrations, and interactive discussions. The research method used is descriptive, with data collected through observation and questionnaires. The results show a 67% improvement in student understanding after the program. The activity had a positive impact on initial behavioral changes among students in adopting more energy-efficient ICT usage. These findings highlight the importance of implementing green computing education in vocational schools as a foundation for environmentally aware digital behavior.  
AlfaOne Application Redesign Using Lean UX Method Anjeli, Saiba; Try Hafsani, Yuke; Efendi, Yoyon; Tashid, Tashid; Utami, Nurul
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu Vol. 1 (2025)
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/ikosstemi.v1.87

Abstract

AlfaOne application is a digital service application owned by PT Sumber Alfaria Tri Jaya TBK which not only provides transaction features, but also various supporting services that make it easier for users to carry out daily activities digitally. This application is designed to increase ease of access to services for users without having to come directly to physical outlets. The existence of the AlfaOne application is expected to increase service effectiveness, reduce queues at outlets, and encourage increased use of digital services. However, based on the results of initial observations, the features and interface design of the AlfaOne application are considered less than optimal and less attractive, resulting in a decrease in user interest and comfort in using the application. Therefore, a redesign of the user interface (UI) and user experience (UX) is needed as a basis for building a platform that is more attractive, easy to use, and in accordance with user needs. The Lean UX method was chosen in this study because it focuses on user satisfaction through an iterative, collaborative, and user feedback-based design process. Based on the results of the analysis, implementation, and evaluation, this study produced a final prototype which is a combination of prototype A and prototype B which has been validated in terms of appearance, functionality, as well as criticism and suggestions from users and technical parties. Prototype A was selected for 3 features and prototype B was selected for the other 3 features. On the login page, design B was selected with a percentage of 53%, the home page was selected with a percentage of 57%, and the history page was selected with a percentage of 62%. In addition, the results of the study showed that the proposed interface design has consistency in the use of color, typography, icons, and layout, and provides a more understandable user experience in accessing features and information as needed. The final design was tested using the Usability Testing method to measure the level of ease of use and user acceptance of the proposed alfaone application design.
Moodify: An Intelligent Music Player Based on User Mood Using Machine Learning Lubis, Abdul Hadi; Sakti, Rendra Jogia; Royhan, Abdullah; Sunandri, Ika Bagus; Sitanggang, Andrian Agustin; Efendi, Yoyon
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu Vol. 1 (2025)
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/ikosstemi.v1.92

Abstract

Mood plays a vital role in influencing human productivity, emotions, and learning effectiveness. Music is widely known as one of the media that can influence and adjust human mood. However, most music player applications still rely on manual playlist selection and do not adapt dynamically to the user's emotional condition. This study proposes Moodify, an intelligent music player application that utilizes machine learning techniques to detect user mood and provide personalized music recommendations. The problem addressed in this research is the lack of adaptive music recommendation systems based on real-time user mood. The purpose of this research is to design and analyze a mood-based music recommendation system that can enhance user experience. The research method uses a machine learning-based classification approach to identify user mood from input data, followed by a recommendation algorithm that matches music characteristics with detected moods. The results show that Moodify is able to recommend music that aligns with user emotional states, improving comfort and engagement. This research contributes to the development of intelligent multimedia applications that support emotional well-being and personalized digital experiences.

Page 2 of 2 | Total Record : 13

 1   2 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 1 (2025)