Rizki Budiman
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Analisis Python Penggunaan Musik Sebagai Pengobatan Gangguan Mental Raja Adi Pranata; Jeremy Reynald; Farhan Armandy Rasyid; Joevan Alezka; Muhammad Indra Ferdinand; Tubagus Zakki Ibrahim Ahmad; Rizki Budiman; Rahmi Yulia Ningsih
Jurnal Publikasi Teknik Informatika Vol. 2 No. 2 (2023): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v2i2.1721

Abstract

Music has become an important part of mental healing efforta. This is because music can reduce anxiety, such as symptoms of depression, anxiety, fear and have a positive effect on mood. However, research that describes statistically and explains visually is still rarely done. Therefore, this study aims to describe statistically and visualize the effectiveness of music as a healing of mental disorders. Through the literature study method, namely the search for references related to mental diseases and music, and pyton analysis, namely to conduct statistical data analysis and visualize data. The results explained that sufferers of mental disorders who listen to music are anxiety, depression, insomnia, OCD, the average age of listening to music that is affected by mental disorders of 14 years to 20 years as many as 300 people, on average per day listening to music for three hours a day as many as 175 as many as 175 People, the effectiveness of healing listening to music as many as 548 people from 736 people or in a percentage of 74.5% of the success rate of music in curing mental illness. This study proves that mental disorders can be cured by listening to music, especially music with rock and pop genres. This research contributes to the knowledge of listening to music into an alternative to healing mental disorders.Therefore future research is necessary to study in other mental disease disorders, not limited to patients with anxiety, Isomania, depression, OCD.
Value engineering using Indonesia’s 2022 National Guideline through decision-making framework for cost optimization in highway infrastructure projects: a case study Abma, Vendie; Citra Dwi Puspita Sari; Tri Nugroho Sulistyantoro; Rizki Budiman
Teknisia Vol 31 No 1 (2026): Teknisia
Publisher : Jurusan Teknik Sipil, Fakultas Teknik Sipil dan Perencanaan, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknisia.vol31.iss1.art2

Abstract

Infrastructure project often requires a balancing manage between design needs, functional performance, and limited financial resources. It has driven the need for Value Engineering (VE) methods to enhance projects and optimize cost without reducing the quality and performance. This study aims to explore the field implementation of Indonesia’s National Technical Guideline No. 4/P/BM/2022 by the Directorate General of Highways (Bina Marga) on VE within a toll road infrastructure project, using the Solo–Yogyakarta Toll Road (Package 1.2) as a case study. Emphasizing value optimization and cost optimization, the study adopts a mixed-method approach that integrates a Pareto principle-based identification of major cost components, a zero–one decision matrix to assess several common borrow material (CBM) sources, a cost–benefit evaluation, and expert insights from fifteen experienced highway engineers. The findings show that combining the use of both Wedi and Sampang quarries provides the best overall value, offering the optimal balance of haul distance, material quality, operational feasibility, and total project costs. The recommended choice results in a cost saving of IDR 51.16 billion (5.05%) while maintaining the required functional performance. Results of the study confirm that systematically implementing the national VE guideline can effectively guide decision-making, enhance project value, and deliver measurable economic benefits. The evaluative process developed offers a practical and replicable framework for applying VE procedures in infrastructure projects, especially in developing countries that need structured methods for cost optimization.