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All Journal Edumatsains Science and Technology Indonesia Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Zero : Jurnal Sains, Matematika, dan Terapan JISTech (Journal of Islamic Science and Technology) Eksakta : Berkala Ilmiah Bidang MIPA GERVASI: Jurnal Pengabdian kepada Masyarakat Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam PRISMATIKA: Jurnal Pendidikan dan Riset Matematika Jurnal Absis : Jurnal Pendidikan Matematika dan Matematika Indonesian Journal of Education and Mathematical Science Jurnal Statistika dan Matematika (Statmat) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal of Science and Technology Indonesian Community Journal Multi Proximity: Jurnal Statistika Universitas Jambi Jurnal Pengabdian Masyarakat Pinang Masak SEWAGATI: Jurnal Pengabdian Kepada Masyarakat BATIK: Jurnal Pengembangan dan Pengabdian Masyarakat Multikultural Journal of Mathematics, Computation and Statistics (JMATHCOS)
Yurinanda, Sherli
Universitas Jambi
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Optimasi Penjadwalan Petugas Penjagaan Portal Dinas Perhubungan Batang Hari dengan Algoritma Genetika Aryani, Lira; Yurinanda, Sherli
JISTech (Journal of Islamic Science and Technology) Vol 10, No 1 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i1.23318

Abstract

Penjadwalan shift penjagaan portal di Dinas Perhubungan Batang Hari masih dilakukan secara manual, yang menimbulkan sejumlah permasalahan seperti distribusi kerja yang tidak merata, bentrokan antar petugas, dan proses penyusunan jadwal yang cukup memakan waktu. Permasalahan ini berdampak pada efektivitas operasional dan menurunkan kepuasan kerja petugas lapangan. Penelitian ini bertujuan untuk merancang penjadwalan yang optimal dan adil bagi seluruh petugas dengan memanfaatkan algoritma genetika. Metode yang digunakan mencangkup tahapan pengumpulan data jadwal dan petugas, representasi kromosom, inisialisasi populasi, evaluasi fitness, seleksi, crossover, dan mutasi. Hasil dari penelitian ini memuat nilai fungsi objektif terbaik(terkecil) yaitu kromosom 35=[0,0,6] dengan f(x)=4 jadwal ini memenuhi kebutuhan shift malam, tapi kosong di pagi dan siang. Nilai fungsi objektif mendekati ideal (f(x)  8-10) yaitu kromosom 16=[1,0,6], kromosom 11= [4,0,2], kromosom 13=[2,0,6], dll. Jadwal ini lebih seimbang, tetapi masih memiliki kelebihan atau kekurangan disalah satu shift. Nilai fungsi objektif tertinggi (terburuk) misal kromosom 36= [4, 2, 8]  dan kromosom 7= [3,3,8] dengan f(x)=26 jadwal ini mengalami kelebihan alokasi petugas secara ekstream, tidak efisien. Penelitian ini menunjukkan bahwa algoritma genetika merupakan metode yang efektif dalam mengatasi permasalahan penjadwalan jaga portal di Dinas Perhubungan Batang Hari. Namun dalam penelitian ini fungsi objektif menunjukkan bahwa sebagian besar solusi belum sepenuhnya optimal.
Forecasting PT Pertamina Geothermal Energy TBK (PGEO) Share Prices using the Arch-Garch Model Ramadhan, Ramadhan; Yurinanda, Sherli; Sarmada, Sarmada
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9493

Abstract

This study focuses on forecasting the daily closing price of PT Pertamina Geothermal Energy Tbk (PGEO) stocks, recognizing the non-stationary and volatile nature of financial time series data. Traditional forecasting methods, such as the ARIMA (Autoregressive Integrated Moving Average) model, are often insufficient for such data because they rely on the assumption of homoscedasticity, or constant variance in the residuals. An analysis of PGEO's daily stock prices from November 2023 to July 2024 revealed significant fluctuations, indicating the presence of heteroscedasticity, where the variance of the residuals is not constant. In tackling this problem, the study utilized the ARCH (Autoregressive Conditional Heteroskedasticity) and GARCH (Generalized Autoregressive Conditional Heteroskedasticity) frameworks, purpose-built to identify and model the phenomenon of volatility clustering within financial datasets. By integrating the ARIMA model with GARCH, the study aimed to create a more robust forecasting tool. After testing various combinations, the MA(1)–GARCH(1,1) model was identified as the most suitable for predicting PGEO's stock prices. This model successfully captured the fluctuating volatility and produced a highly accurate forecast, as evidenced by a Mean Absolute Percentage Error (MAPE) of just 2.97%. A MAPE value below 10% is generally considered to represent a very high level of forecasting accuracy, confirming the effectiveness of the chosen model in providing reliable short-term predictions for stock market movements. Keywords: ARCH-GARCH, Stock price forecasting, ARIMA
ANALISIS CLUSTER PROGRAM ANGGARAN UNTUK MENINGKATKAN EFISIENSI DENGAN METODE K-MEDOIDS DI SEKRETARIAT DPRD PROVINSI JAMBI Srikandi; Sherli Yurinanda
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 7 No 2 (2025)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menganalisis efisiensi program anggaran di Sekretariat DPRD Provinsi Jambi menggunakan metode K-Medoids. Data yang digunakan mencakup realisasi anggaran tahun 2022 dan 2023. Metode K-Medoids dipilih karena kemampuannya mengelompokkan data secara robust terhadap outlier. Analisis dilakukan melalui beberapa tahapan, termasuk pendeteksian outlier, standarisasi data, dan penentuan jumlah cluster optimal dengan metode elbow. Hasil penelitian menunjukkan adanya empat cluster program anggaran dengan karakteristik pencapaian yang berbeda. Cluster 1 mencakup program dengan realisasi anggaran yang tinggi, sedangkan cluster 4 menunjukkan program dengan realisasi rendah. Temuan ini memberikan dasar untuk pengambilan keputusan strategis dalam meningkatkan efisiensi dan efektivitas pengelolaan anggaran.
Analysis of Factors Influencing Learning Motivation of Students in the Faculty of Science and Technology at Universitas Jambi Using Structural Equation Modeling (SEM) Sarmada, Sarmada; Yurinanda, Sherli; Rozi, Syamsyida; Irawan, Randi
Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Vol. 13 No. 1 (2025): Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam
Publisher : Prodi Pendidikan Matematika FTIK IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/jpmipa.v13i1.5696

Abstract

Abstract: Learning motivation is the driving force that ensures the continuous learning process to achieve educational goals. This study analyzes the factors influencing students' learning motivation. The sample consists of active students from the Faculty of Science and Technology at Jambi University. The research employs a quantitative survey method, with data collected through a Likert-scale questionnaire. Data analysis is conducted descriptively using Structural Equation Modeling (SEM). Three exogenous variables are examined: learning strategies, learning facilities, and learning environment, while learning motivation serves as the endogenous variable. The results indicate that learning strategies contribute the most to learning motivation, followed by the learning environment and learning facilities. Overall, these latent variables have a positive impact on learning motivation. Abstrak: Motivasi belajar adalah dorongan yang memastikan berlangsungnya proses pembelajaran secara berkesinambungan agar tujuan pembelajaran dapat tercapai. Penelitian ini melakukan analisis terhadap faktor-faktor yang memengaruhi motivasi belajar mahasiswa. Sampel yang digunakan adalah mahasiswa aktif di Fakultas Sains dan Teknologi Universitas Jambi. Metode digunakan adalah survei kuantitatif dengan pengambilan data melalui kuesioner berskala Likert. Analisis data dilakukan secara deskriptif menggunakan Structural Equation Modeling (SEM). Ada tiga variabel eksogen yang digunakan yaitu cara belajar, fasilitas belajar, dan lingkungan belajar. Sedangkan motivasi belajar digunakan sebagai variabel endogen. Hasil penelitian menunjukkan bahwa cara belajar memberikan kontribusi paling besar terhadap motivasi belajar, diikuti oleh lingkungan belajar dan fasilitas belajar. Secara keseluruhan, variabel-variabel laten tersebut memiliki pengaruh positif terhadap motivasi belajar.  
Application of Fuzzy Time Series Chen and Cheng Methods to Forecast Profit in a State-Owned Insurance Company Fajrin, Dirani Amaris; Yurinanda, Sherli; Sarmada, Sarmada
Indonesian Journal of Education and Mathematical Science Vol 6, No 3 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara (UMSU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijems.v6i3.26750

Abstract

PT. Taspen (Persero) as a state-owned enterprise in the services sector needs to analyze financial performance to understand the fluctuations in quarterly profit in 2022. This study uses the Fuzzy Time Series (FTS) forecasting method with two approaches, namely Fuzzy Time Series Chen and Fuzz Time Series Cheng, to predict profit and dividend prospects. The analysis stage of Chen's Fuzzy Time Series method includes determining the set of the universe (U), forming intervals, defining fuzzy sets, determining the membership value of each data, fuzzification of data, formation of Fuzzy Logic Relationships (FLR) and Fuzzy Logic Relationship Groups (FLRG), forecasting and defuzzification. Meanwhile, Cheng's Fuzzy Times Series method has similar stages but is equipped with FLRG weighting into the W matrix and standardization of the W matrix*. The results of the calculation of forecasting accuracy through MAPE, MSE, and MAE show that Cheng's Fuzzy Time Series method is more accurate than Chen's Fuzzy Time Series, with a smaller error value. This confirms that Cheng's Fuzzy Times Series method is more reliable in projecting PT. Taspen (Persero). 
Penerapan Algoritma Rivest-Shamir-Adleman (RSA) pada Enkripsi Uniform Resource Locator (URL) Website untuk Keamanan Data Trisnawati, Theodora Tantri; Yurinanda, Sherli; Syafmen, Wardi; Multahadah, Cut
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 2 December 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v11i2.21169

Abstract

PT. Rezeki Surya Gasindo is a company that uses websites to store important company data, one of which is customer personal data. PT. Rezeki Surya Gasindo's website is protected by a login system. However, a login system alone is not enough to protect the data stored on the website from cases of data theft by third parties. One solution to this problem is to encrypt the website's Uniform Resource Locator (URL) to increase the security level of data stored on the website. In this research, the Rivest-Shamir-Adleman (RSA) algorithm is used for the encryption process. The aim of this research is to determine the process of applying the Rivest-Shamir-Adleman (RSA) algorithm to the Uniform Resource Locator (URL) encryption of the PT. Surya Gasindo's website. The success of applying encryption with the RSA algorithm is observed from changes in the get parameter value that appears in the URL bar. The encrypted message is the customer, the get parameter in the Customer menu, which contains the consumer's personal data. By choosing two large prime numbers, namely 151 and 173, and taking one of the public keys/encryption keys, namely 16379, the result is that the get parameter in the URL bar has changed to the code string 5a9cb05811aa6e4c. The RSA algorithm has been successfully applied to the website URL.
Prediksi Pajak Pertambahan Nilai pada Penyediaan Jasa dengan Metode Fuzzy Time Series Model Chen Lestari, Sri; Yurinanda, Sherli
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 2 December 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v11i2.22724

Abstract

For companies, tax is a burden or fee that must be paid to the state as a taxpayer. The taxes that must be paid by the company can affect the profits earned. Therefore, efforts are needed to reduce or minimize the tax burden. Efforts to minimize the tax burden include tax planning. Tax planning that is often used by companies is tax planning on Value Added Tax (VAT), because all production activities are closely related to the VAT burden. Tax planning for VAT can be done by maximizing the amount of input VAT. To be able to identify the amount of input VAT in the next period, predictions can be made on the input VAT value. The uncertain VAT value and limited data collection make it possible to predict the VAT value using the fuzzy time series method. One model that can be used in fuzzy time series is the Chen model, because it has better accuracy values than the Song and Chissom models. Based on this research, it can be seen that the results of the prediction of the VAT value for the provision of services at PT Pertamina Hulu Rokan Zone 1, for the period July 2023 using the fuzzy time series Chen model method in second order obtained IDR 1,455,000,000 with a forecasting accuracy of 82.1%. In this way, PT PHR Zone 1 can maximize input VAT of IDR 1,455,000,000 so that the goal of minimizing the tax burden is achieved.
Co-Authors Afrianda, Vionica Afrianto, Muhammad Ficky Aryani, Lira Aryani, Reni CUT MULTAHADAH Darvi Mailisa Putri Devianto, Dodi Ditya Ismi Budiarti Fajrin, Dirani Amaris Fitriyani Fitriyani Gusmanely Z Gusmi Kholijah Ilham Yusuf Triputra Irawan, Randi Khaira, Ulfa Mardhotillah, Bunga Mardian Peslinof Margaretha Pasaribu Multahadah, Cut Multhadah, Cut Niken Rarasati Nurhadi, Miranda Sukma Ramadhan Ramadhan Rizqa Raaiqa Bintana Samsidar Samsidar Sarmada Sarmada Sarmada, Sarmada Sarmada, Sarmada Sormin, Corry Sri Lestari Srikandi Suci Wulandari Suci Wulandari Sufri Sufri Susi Marisa Syamsyida Rozi Trisnawati, Theodora Tantri Ulfa Khaira, Ulfa Wardi Syafmen Yanuar, Ferra Yoza Fendriani