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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Matematika UNAND International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Radhiah Radhiah
Universitas Syiah Kuala
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Engineering Mathematics Physics

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Perbandingan Kualitas Suara Smartphone Menggunakan Metode Dynamic Time Warping (DTW) Inas Salsabila; Samsul Anwar; Radhiah Radhiah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.341 KB) | DOI: 10.29207/resti.v5i1.2764

Abstract

Smartphones are telecommunication devices that play a significant role in daily life. The sound quality produced by a smartphone becomes important for users, considering that poor sound quality might cause misunderstandings in communication. This study provides an illustration of the application of Dynamic Time Warping (DTW) in the comparison of the sound quality produced by a smartphone. In addition to the DTW, the median test and its confidence interval are also used to determine the sound quality of a smartphone. The data employed are primary data in the form of voice recordings of six people that saying five sample sentences, each of which is repeated five times through four different smartphone types that are used as examples. So that the total voice recordings for each smartphone are 150 pieces. This study aims to compare the sound quality produced by those smartphones. The results of this study indicate that although smartphones type 2, 3 and 4 have similar sound quality, the sound quality produced by smartphones type 4 is more stable than other types. Therefore, this study concludes the smartphone type 4 is the smartphone with the most satisfying sound quality. Furthermore, this study showed that the DTW method is effective in analyzing the sound quality of a smartphone.
Average-based fuzzy time series for forecasting blood bag availability: Implications for health resilience and emergency preparedness in Banda Aceh, Indonesia Ikhsan Maulidi; Nurafni Fazriani; Radhiah Radhiah; Vina Apriliani; Sarbaini
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 4 No. 1 (2026): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v4i1.1138

Abstract

Background: Blood availability remains a major challenge in healthcare systems, particularly in developing countries where the demand for blood often exceeds the available supply. Accurate forecasting of blood collection is therefore important to support effective blood inventory management at blood transfusion units. Aims: This study aims to apply the Average-Based Fuzzy Time Series method to forecast the number of collected blood bags at the Blood Transfusion Unit (UTD) of the Indonesian Red Cross in Banda Aceh, both in total and by blood type. Method: Monthly blood collection data from January 2016 to September 2020 were analyzed using the Average-Based Fuzzy Time Series model. The forecasting procedure involved constructing fuzzy intervals using the average-based approach, forming fuzzy logical relationships, and performing defuzzification. Model performance was evaluated using Mean Squared Error (MSE) and Average Forecasting Error Rate (AFER). Result: The second-order model provided the best forecasting performance with an AFER value of 13.67% and an accuracy of approximately 86.33%, producing a prediction of 2054 blood bags for October 2020. Forecasting by blood type yielded predictions of 529 (A), 702 (O), 738 (B), and 154 (AB) blood bags. Conclusion: The results indicate that the Average-Based Fuzzy Time Series method is effective for forecasting blood bag availability and can support planning and management of blood supply at blood transfusion units. Furthermore, the proposed approach has potential applications in defense and emergency contexts by supporting medical logistics planning, improving preparedness, and enhancing the resilience of blood supply systems during military operations and disaster response.
Optimal Bonus-Malus Premium with the Claim Frequency Distribution is Negative Binomial and the Claim Severity Distribution is Truncated Weibull Ikhsan Maulidi; IZZAH MAULIDIA; Radhiah Radhiah; Vina Apriliani
Jurnal Matematika UNAND Vol. 15 No. 2 (2026)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.15.2.179-195.2026

Abstract

The optimal bonus-malus system is a system for determining the amount of premium in the next period based on the frequency and severity of claims filed by policyholders in the previous period. In this article, we study the insurance premium formula using the optimal bonus-malus system with the claim frequency has a negative binomial distribution and the claim severity has a truncated Weibull distribution. The method to derive the bonus-malus formula uses a Bayes solution with a quadratic loss function. The formula obtained has been also applied to the data of motor vehicle insurance to calculate the risk premium that must be paid by the policyholder. From the calculation results, the insurance premiums that use the optimal bonus-malus system with a truncated Weibull distribution are more profitable for both the company and the insurer than the Weibull distribution.
Co-Authors Ikhsan Maulidi Inas Salsabila IZZAH MAULIDIA Nurafni Fazriani Samsul Anwar Sarbaini Vina Apriliani