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Jurnal Diferensial
Published by Universitas Nusa Cendana
ISSN : -     EISSN : 27759644     DOI : -
Core Subject : Economy, Health, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Public Health
Jurnal Diferensial adalah jurnal sains yang bertujuan untuk menyebarluaskan hasil riset-riset ataupun kajian pustaka pada bidang ilmu matematika dan terapannya. Artikel-artikel pada jurnal ini difokuskan kepada bidang ilmu matematika dan terapannya. Ruang lingkup atau bidang ilmu yang diterima dijurnal ini (tetapi tidak terbatas pada) adalah Analisis, Aljabar, Teori Graf, Optimisasi, Riset Operasi, Statistik, Biomatematika.
Arjuna Subject : Matematika - Matematika Terapan
Articles 3 Documents
 1 
Search results for , issue "Vol 8 No 1 (2026): April 2026" : 3 Documents clear
Implementasi Fuzzy Mamdani pada Sistem Pendukung Keputusan Pemilihan Mobil Listrik Parwitasari, Ikha Puspita; Setyawan, Azis Putra
JURNAL DIFERENSIAL Vol 8 No 1 (2026): April 2026
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v8i1.25024

Abstract

The rapid development of electric vehicles (EVs) has led to a wide variety of models with different specifications and prices, requiring a method that can evaluate multiple criteria simultaneously. This study applies the Mamdani fuzzy inference system to assess the suitability of EVs based on six key variables: price, production year, driving range, passenger capacity, power, and battery capacity. Triangular membership functions are used to represent the linguistic variables, and the rule base reflects realistic decision preferences. Through fuzzification, Mamdani inference, aggregation, and defuzzification, crisp suitability scores are produced for each vehicle. Results show that EVs with high specifications and proportional prices achieve the highest scores, while those with high prices but low specifications rank lowest. The fuzzy Mamdani approach effectively integrates linguistic and subjective criteria to support structured decision-making in EV selection.
A Solutions of the Linearized Two-Dimensional Generalized Dispersive Wave Equation with Mixed Derivative via the Residual Power Series Method Ali, Nawzad Hasan
JURNAL DIFERENSIAL Vol 8 No 1 (2026): April 2026
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v8i1.26631

Abstract

This article applies the Residual Power Series Method (RPSM) to solve the Linearized Two-Dimensional Generalized Dispersive Wave Equation (L-2DGDWE) featuring the mixed derivative term $u_{xt}$. The RPSM is based on the general Taylor series formula combined with a residual error function minimization. A new analytical solution is investigated in this work. The analytical solution is designed to find approximate solutions via RPSM, and these obtained results are compared with exact solutions to demonstrate the precision, reliability, and rapid convergence of the proposed method. Graphical representations at different time instances are provided to visualize the solution behavior.
An Analysis of the COVID-19 Agenda Using Big Data from Social Media: A Comparative Study across Countries with R Programming İşleyen, Şakir; Zebari, Amar Yahya; Jameel, Hasan Hazim
JURNAL DIFERENSIAL Vol 8 No 1 (2026): April 2026
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v8i1.26853

Abstract

Social media platforms are becoming increasingly important as sources of public discourse and real-time data analysis, as the COVID-19 epidemic has highlighted. Using the hashtag #COVID19, this study examines COVID-19-related tweets from seven nations (the US, Germany, South Korea, Iraq, Spain, Italy, and Turkey) in order to find trends in engagement and correlations. Similarities between public attitude and government communications are examined by statistical techniques such as content analysis, frequency analysis, and cross-delay correlation, as well as R programming. The findings show that tweet patterns from different countries are highly correlated, and that the Iraqi government's tweets with a typical theme were more popular than those with a COVID-19 theme. This study provides information on cross-border communication tactics in times of crisis and illustrates the potential of big data analytics for comprehending global phenomena.

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