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All Journal Protasis: Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya Jurnal Arjuna : Publikasi Ilmu Pendidikan, Bahasa dan Matematika Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Zahra Putri
Unknown Affiliation
Humanities Astronomy Education Health Professions Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Penggunaan Bahasa Indonesia dalam Pembelajaran Matematika Zahra Putri; Angelyca; Ika Febriana; Roberto Karlos Sinaga
Protasis: Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya Vol. 3 No. 1 (2024): Juni : Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/protasis.v3i1.134

Abstract

Mathematics teaching and learning faces significant challenges, including the use of language as a communication tool. So the research was carried out to determine the use and correlation of language, especially Indonesian with and in learning mathematics. The scope of this research is the use of language in mathematics and the correlation between the two. This research uses a qualitative descriptive method with literature study. From the research, it was found that language and mathematics are positively correlated and language is used to describe mathematical concepts and to explain patterns, properties and relationships between mathematical objects.
Implementasi Pendekatan Aktuaria Untuk Perhitungan Dana Pensiun Anita Talia; Danu Rama Dani; Zahra Putri
Jurnal Arjuna : Publikasi Ilmu Pendidikan, Bahasa dan Matematika Vol. 3 No. 1 (2025): Jurnal Arjuna : Publikasi Ilmu Pendidikan, Bahasa dan Matematika
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/arjuna.v3i1.1463

Abstract

A pension fund program is a crucial instrument in the social security system, playing a vital role in ensuring economic stability and financial well-being for individuals in their later years. This program is designed as a form of long-term financial planning aimed at providing protection for workers after they enter retirement. Through this, workers are promised structured benefits in the form of pension funds or allowances, ensuring sustainable income security. Long-term financial planning, particularly for retirement, has become an essential need in the modern economy. This research explores the implementation of actuarial approaches in pension fund calculations utilizing Python programming to enhance the calculation process. The research aims to determine the total promised pension funds allocated across the working period to calculate funding requirements more systematically. Simulated data is used to compare manual calculation results with Python-based estimations. Python is expected to provide additional efficiency in estimating future pension needs. The findings demonstrate that actuarial calculation methods, supported by programming technology, can enhance accuracy in projections and assist in determining the appropriate amount for pension fund programs.
Penggunaan Python dalam Pengerjaan Induksi Matematika Salsabila Arvi; Ikrimah Sabina Triadi; Zahra Putri; Rhamanda Ardiansyah Lubis; Fitriyani Fitriyani
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 2 No. 5 (2024): Oktober: Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v2i5.251

Abstract

Mathematics is a science that is structured deductively and systematically. Proof in Mathematics is important because it can enable critical thinking logically, and the truth of a hypothesis can be tested. Mathematical induction is a proof method that has 2 steps, namely basis and induction. With advances in technology today, there are many applications that can make this proof easier, such as Python. This research uses quantitative and qualitative approaches to prove the effectiveness of using Python compared to manual proof. The results show that Python not only speeds up work but also minimizes errors that could occur if done manually. With this research we recommend further exploitation of mathematical induction in other programming applications.
Co-Authors Angelyca Anita Talia Danu Rama Dani Fitriyani Fitriyani Ika Febriana Ikrimah Sabina Triadi Rhamanda Ardiansyah Lubis Roberto Karlos Sinaga Salsabila Arvi