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Alpha Epsilon Journal of Mathematics
Published by Universitas Annuqayah
ISSN : -     EISSN : 30895626     DOI : https://doi.org/10.59005/aejm.v1i1
Core Subject : Education,
Mathematics
Alpha Epsilon Journal of Mathematics is an academic journal published by the Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Annuqayah. The journal is published twice a year, in January and July. Alpha Epsilon Journal of Mathematics is open access, allowing anyone to freely access and download the published articles. This journal has a broad focus and scope within the field of mathematics and related sciences, including algebra, real analysis, applied mathematics, computation, operations research, probabilistics, stochastic processes, and graph theory. Each article published in the Alpha-Epsilon Journal of Mathematics undergoes a rigorous review process by competent reviewers in the field. This process ensures that the published research meets high-quality standards and provides significant contributions to the advancement of science. With a dedication to disseminating knowledge and innovation in the field of mathematics, Alpha Epsilon Journal of Mathematics is committed to supporting researchers and academics in publishing their research results to the global community.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 12 Documents
 1   2 
Penerapan Metode Weight Product (WP) dalam Seleksi Penerima Beasiswa di SMAT Insan Hanifa Sumber Payung Faruq Kushartono
Alpha-Epsilon: Journal of Mathematics Vol 1 No 1 (2025): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i1.516

Abstract

This study aims to design a decision support system for identifying scholarship recipients using the Weighted Product method at SMAT Insan Hanifa Sumber Payung. The Weighted Product (WP) method is a commonly used technique in decision-making. Out of a total of 42 students, the decision support system will select 15 eligible students for the scholarship based on calculations using the WP method. The research results show that D31 achieved the highest score with a value of 0.030735641. This indicates that student D31 and 14 other students meet the criteria set as potential scholarship recipients. Additionally, the designed system is also rated well with a satisfaction level of 86.1%
Implementasi Metode Regresi Linear Berganda Dalam Memprediksi Santri Baru Di Pondok Pesantren Al-Falah Sumber Gayam Khalishatus Shafariyah; Siti Khotijah
Alpha-Epsilon: Journal of Mathematics Vol 1 No 1 (2025): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i1.517

Abstract

Al-Falah Islamic Boarding School Sumber Gayam, Kec. Kadur, Kab. Pamekasan is one of the boarding schools that fluctuates in terms of the number of new students each year. Therefore, predictions are very necessary to find out the number of new students who will register in the following year. The aim is to help the committee for accepting new students to be ready to prepare the boarding facilities as well as possible. The multiple linear regression method is the method used in this research to predict future conditions using previous data and to determine whether or not there is an influence exerted by the independent variable on the dependent variable. Annual student alumni data, boarding school facilities, annual fees and data on outstanding students are variables that are thought to influence the number of new students in 2023-204 by calculating MAPE and RMSE errors. The results of the research obtained as many as 98 new students based on testing the r2, r, F test and t test based on the sig value. < 0.05 which was calculated manually and SPSS version 26 calculations. The results show that the variables studied have a significant effect on the number of new students registering in 20232024 with a MAPE accuracy of 0.02% and an RMSE accuracy of 0.66%, this shows that the ability of the forecasting model formed can be said to be good or accurate.
Penerapan Algoritma Welch Powell Untuk Menyusun Jadwal Mata Kuliah Di IST Annuqayah Inda Arundani; Luluk Sarifah; Fiqih Rahman Hartiansyah
Alpha-Epsilon: Journal of Mathematics Vol 1 No 1 (2025): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i1.518

Abstract

Graph coloring is the giving of color to certain objects in the graph. These objects can be nodes, edges, and regions. This study aims to look at the process and results of graph coloring using the Welch Powell Algorithm in the preparation of class schedules for the Mathematics and Biology Study Program, Faculty of Mathematics and Natural Sciences, Annuqayah Institute of Science and Technology. The type of research used is descriptive qualitative research. The object of research in this study is the list of lecturers, list of courses, lecture active hours, and the number of rooms used. Data analysis was carried out by modeling a list of lecturers with a list of courses into a graph and determining the minimum color in the coloring process using Welch Powell's algorithm. In this research, we know the performance of the Welch Powell algorithm in compiling schedules for each study program and combined scheduling. Based on the scheduling results, it can be concluded that the application of Welch Powell's algorithm for combined scheduling is more effective and more efficient to use than scheduling for each study program. In addition to not overlapping between courses, it can also save space.
Analisis Metode Rantai Markov Untuk Memprediksi Status Pasien Di Pusat Kesehatan Masyarakat (Puskesmas) Guluk-Guluk Kabupaten Sumenep Ulfatul Husna; Fathorrozi Ariyanto; Prasanti Mia Purnama
Alpha-Epsilon: Journal of Mathematics Vol 1 No 1 (2025): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i1.519

Abstract

Markov chains are a method for predicting future events using certain techniques from current data. One application of the Markov Chain method is related to event prediction, such as predicting the number of patient statuses in a health center. It is hoped that predicting the number of patient statuses can be used in various program planning. This research using the Markov Chain method uses patient data in May 2023 at the Guluk-Guluk Health Center, Sumenep Regency. The data is analyzed to determine the transition from one state to another, then converted into a transition probability matrix and then searched for the steady state (equilibrium). Apart from being searched using the transition probability matrix, the steady state can be found using the substitution method. If the result values are aqual then the two method processes carried out are correct. The results of this research state that the Guluk-Guluk Community Health Center will experience steady state conditions that will occur in December 2024, with equilibrium conditions occurring in the 20th period. The respective transition probability values are 94.2% for improving conditions, 4 .9% for normal conditions, and 0.9% for severe conditions.
Solusi Numerik Model Matematika Pada Kasus Kecanduan Media Sosial Tiktok Di Pondok Pesantren Annuqayah Latee II Menggunakan Metode Runge Kutta Siti Romlah; Muhammad Thahiruddin; Luluk Sarifah
Alpha-Epsilon: Journal of Mathematics Vol 1 No 1 (2025): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i1.520

Abstract

TikTok social media is a medium that can develop users' creativity, but most users compete to express themselves due to frequently viewing content so that they are obsessed with creating content and continuously trying various content movements. This can result in an addiction to viewing or addiction to TikTok content movements. Modifying the TikTok social media addiction model is one of the objectives of this research, starting by distributing a questionnaire to 100 respondents. Next, a programming simulation was carried out using the Runge Kutta Butcher method with Python tools. With the results, the Runge Kutta Butcher method can provide high accuracy and is effective in solving the SEIIRS model. The population increased with an increase of 18 individuals exposed, indicating the possibility of movement of susceptible individuals. The decline in infected populations 1 and 2 shows that individuals in these populations are slowly becoming recovered individuals. Based on the findings of this research, it can be concluded that Santri PP Annuqayah Latee II had previously experienced TikTok addiction and would return to normal status (cured but vulnerable) on Day 200.
Cluster Perbandingan Ward dan Weighted Linkage dalam Pengelompokan Kecamatan Berdasarkan Data Guru PNS dan Non PNS di Kabupaten Pamekasan: Perbandingan Ward dan Weighted Linkage dalam Pengelompokan Kecamatan Berdasarkan Data Guru PNS dan Non PNS di Kabupaten Pamekasan Sibrul Choir; Tony Yulianto
Alpha-Epsilon: Journal of Mathematics Vol 1 No 2 (2025): July
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i2.613

Abstract

Perkembangan dunia pendidikan tidak terlepas dari sinergi antara tiga pihak utama, terutama guru yang menjadi penggerak utama kemajuan pendidikan. Mengingat peran sentralnya, keberadaan guru yang kompeten—baik yang bersertifikasi sebagai Pegawai Negeri Sipil (PNS) maupun non-PNS—sangat penting dalam mendorong kemajuan pendidikan nasional. Penelitian ini bertujuan untuk mengelompokkan kecamatan-kecamatan di Kabupaten Pamekasan berdasarkan jumlah guru PNS dan non-PNS pada jenjang Taman Kanak-Kanak (TK), Sekolah Dasar (SD), dan Sekolah Menengah Pertama (SMP) tahun 2023. Dua metode klasterisasi hierarkis, yaitu Ward Linkage dan Weighted Linkage, digunakan untuk melakukan pengelompokan wilayah. Evaluasi kualitas hasil klaster dilakukan menggunakan nilai Silhouette Coefficient (SC).
Dampak Pertumbuhan Industri Terhadap Tingkat Pengangguran Terbuka (TPT) di Kabupaten Pamekasan dengan Metode Regresi Linear Sederhana Lailatus Shobibatir Rohmah; Amaliyatul Hasanah
Alpha-Epsilon: Journal of Mathematics Vol 2 No 1 (2026): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v2i1.792

Abstract

Pengangguran merupakan salah satu permasalahan utama yang dihadapi oleh banyak daerah di Jawa Timur , termasuk Kabupaten Pamekasan. Di kabupaten pamekasan pertumbuhan industri menjadi salah satu faktor yang dapat mengurangi tingkat pengangguran terbuka karena dapat menyerpa tenaga kerja. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana hubungan antara pertumbuhan industri terhadap tingkat pengangguran terbuka di kabupaten pamekasan. Data yang digunakan pada penelitian ini adalah pertumbuhan industri dan tingkat pengangguran terbuka pada tahun 2013 – 2023. Penelitian ini menggunakan regresi linear sederhana untuk mengatahui sejauh mana hubungan antara pertumbuhan industri terhadap tingkat pengangguran terbuka (TPT) di kabupaten Pamekasan. Hasil penelitian ini menunjukkan bahwa pertumbuhan industri berpanguruh negatif terhadap tingkat pengangguran artinya apabila pertumbuhan industri meningkat maka akan terjadi penurunan terhadap tingkat pengangguran terbuka begitupun sebaliknya.
Peramalan Peramalan Persentase Penduduk Miskin (PPM) Di Kabupaten Pamekasan Menggunakan Model Statistik Time Series Dengan Metode Autoregressive Integrated Moving Average (ARIMA): Peramalan Persentase Penduduk Miskin (PPM) Di Kabupaten Pamekasan Menggunakan Model Statistik Time Series Dengan Metode Autoregressive Integrated Moving Average (ARIMA) Nurul Jannah; Amaliyatul Hasanah
Alpha-Epsilon: Journal of Mathematics Vol 1 No 2 (2025): July
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

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

Abstract

Kemiskinan merupakan salah satu masalah yang kompleks di Indonesia termasuk di kabupaten Pamekasan, karena tingkat kemiskinan akan mempengaruhi salah satu indikator keberhasilan suatu negara. Berdasarkan permasalahan tersebut, penelitian ini bertujuan untuk memprediksi persentase penduduk di kabupaten Pamekasan pada 3 tahun mendatang. Data yang digunakan adalah data time series persentase penduduk miskin di kabupaten Pamekasan dari tahun 2010 sampai tahun 2024. Model ARIMA yang digunakan adalah ARIMA (0,3,1) yang dipilih berdasarkan kriteria RMSE, MAE, dan MAPE. Hasil penelitian menunjukan bahwa model ARIMA dapat memprediksi persentase penduduk miskin dengan baik. Peramalan untuk tahun 2025 menunjukkan bahwa persentase penduduk miskin diperkirakan akan menurun menjadi 12,82%, pada tahun 2026 menjadi 11,91%, dan pada tahun 2027 menjadi 10,74% dengan nilai MAPE adalah 4,795%, nilai MAE adalah 0,695, dan nilai RMSE adalah 1,089% yang berarti memiliki tingkat keakuratan peramalan yang sangat baik karena nilai MAPE < 10% dan nilai RMSE tergolong kecil. Hasil penelitian ini dapat digunakan sebagai acuan untuk perencanaan kebijakan pemerintah dalam pengentasan kemiskinan di kabupaten Pamekasan.
Peramalan Perbandingan Metode Exponential Moving Average dan Weighted Moving Average Dalam Peramalan Angka Kemiskinan Di Kabupaten Pamekasan: Perbandingan Metode Exponential Moving Average dan Weighted Moving Average Dalam Peramalan Angka Kemiskinan Di Kabupaten Pamekasan Eka Yanti; Luluk Sarifah
Alpha-Epsilon: Journal of Mathematics Vol 1 No 2 (2025): July
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/aejm.v1i2.803

Abstract

This study aims to predict the best method in a forecasting system using the Exponential Moving Average (EMA) and Weighted Moving Average (WMA) methods. In the simulation stage, the data used is the poverty rate data in Pamekasan Regency from 2015 to 2024 as actual data to predict the 2025 data. Meanwhile, the comparison process is carried out by looking at the accuracy level of each method based on the MSE and MAPE values. Based on the results of data simulations from the two methods tested, it is known that the Exponential Moving Average (EMA) and Weighted Moving Average (WMA) are suitable for predicting poverty rates in Pamekasan Regency, because the resulting MAPE value is between 20% -50%.
Prediksi Jumlah Stunting Kabupaten Pamekasan Menggunakan Metode Statistical Parabolic Iis Setiana; Luluk Sarifah
Alpha-Epsilon: Journal of Mathematics Vol 2 No 1 (2026): January
Publisher : Department of Mathematics, Faculty of Mathematics and Scince, Universitas Annuqayah

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

Abstract

Indonesia is a country that is included in the target of high stunting management in the world, so stunting remains a problem that needs to be addressed. For example, the number of stunting in Pamekasan Regency. Currently, Pamekasan Regency is included in the target of stunting management with a stunting prevalence of 25.1% covering 21 health centers from 13 sub-districts. The purpose of this study is to predict the number of stunting in Pamekasan Regency in 2018-2024 using the statistical parabolic method. Statistical parabolic is one method that is able to make predictions based on past data, then in this study used data on the number of stunting in 2018-2024 obtained from the Pamekasan Regency Health Office. After calculating the predicted number of stunting in 2018-2024 based on the MAPE value obtained the result of 5.45%. Therefore, it can be concluded that the statistical parabolic method is good to be used to predict the number of stunting in 2025-2026.

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