Article Per Year (5 Year)
p-Index From 2021 - 2026
9.719
P-Index
This Author published in this journals
All Journal Jurnal Sains dan Teknologi AKSIOMA: Jurnal Program Studi Pendidikan Matematika CESS (Journal of Computer Engineering, System and Science) ZERO : Jurnal Sains, Matematika dan Terapan INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Justek : Jurnal Sains Dan Teknologi Jurnal Pendidikan Matematika (JUDIKA EDUCATION) Query : Jurnal Sistem Informasi Zero : Jurnal Sains, Matematika, dan Terapan ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JOURNAL OF SCIENCE AND SOCIAL RESEARCH Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Math Educa Journal Imajiner: Jurnal Matematika dan Pendidikan Matematika JURNAL PEMBELAJARAN DAN MATEMATIKA SIGMA (JPMS) MUKADIMAH: Jurnal Pendidikan, Sejarah, dan Ilmu-ilmu Sosial Indonesian Journal of Education and Mathematical Science Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Mandalika Mathematics and Educations Journal G-Tech : Jurnal Teknologi Terapan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi FARABI: Jurnal Matematika dan Pendidikan Matematika Leibniz: Jurnal Matematika Mathematics and Applications (MAp) Journal Journal of Mathematics and Scientific Computing With Applications Jurnal Pijar MIPA Journal of Information Systems and Technology Research Jurnal MathEducation Nusantara Al-Ijtima: Jurnal Pengabdian Kepada Masyarakat Digital Transformation Technology (Digitech) Jurnal Ilmiah Ilmu Terapan Universitas Jambi Jurnal Riset Mahasiswa Matematika JME AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Journal of Technology and Computer (JOTECHCOM) Jurnal Pengabdian Mitra Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat Cermat : Jurnal Cendekiawan dan Riset Multidisiplin Akademik Terintegrasi
Rima Aprilia
Universitas Islam Negeri Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 76 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 76 Documents
Search

 4   5   6   7   8 
Comparison of agglomerative hierarchical clustering (AHC) algorithm and k-means algorithm in poverty data clustering in north sumatra Usna, Wilia; Aprilia, Rima
Desimal: Jurnal Matematika Vol. 7 No. 3 (2024): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v7i3.24373

Abstract

North Sumatra had the 17th lowest rate of poverty in 2023 out of 34 provinces, with 1,239.71 thousand people, or 8.15 percent, living there. Although there has been a decline in the poverty rate in 2023 compared to previous years, there are still many districts and cities in North Sumatra with significant rates of poverty; thus, this cannot be disregarded. The government must act to address this by providing the community with various forms of aid and increasing the number of job openings. To overcome this, one must first identify the cities or districts with the lowest to highest rates of poverty. This can be avoided with data mining, namely by applying the clustering technique. The Agglomerative Hierarchical Clustering (AHC) algorithm and the K-Means algorithm were the clustering techniques employed in this investigation. The Davies Bouldin Index (DBI) will then be used to validate the clustering results in order to ascertain which technique yields the best cluster. Three clusters were created using the AHC method: cluster 1 had 31 districts/cities, cluster 2 had one district/city, and cluster 3 had one district/city. Using the k-means approach, three clusters were identified: cluster 1, which included 22 districts/cities, had the lowest poverty rate; cluster 2, which included 10 districts/cities, had a moderate poverty rate; and cluster 3, which included 1 district/city, had the highest poverty rate. It was discovered through clustering validation that the k means method with a DBI value of 0.45 was the most effective approach for this investigation.
Application of de novo programming method in production planning at UMKM seasoning Opaque Tuntungan II Damanik, Mahyuni Br; Aprilia, Rima
Desimal: Jurnal Matematika Vol. 7 No. 3 (2024): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v7i3.24430

Abstract

Optimization is a way of solving mathematical problems to get optimal results. One way to solve optimization problems is to use a linear program. One of the developments of linear program models that can be used in optimization problems is de novo programming. This research uses de novo programming to maximize profits at UMKM Seasoning Opaque. Based on the results of the analysis with the POM-QM application, it can be concluded that the production of Tuntungan II seasoning opaque factory for 7 weeks is optimal with the production of 2,031 kg of salted seasoning opaque, 1,170 kg of regular spicy seasoning opaque, and 3,381 kg of round spicy seasoning opaque. Using the De Novo Programming method, it was found that the optimal production for 7 weeks of the opaque spice factory in Tuntungan II for 7 weeks had a profit of Rp12,317,240.
Implementasi Metode AHP-MOORA dan AHP-SAW Pada Sistem Pendukung Keputusan Pemilihan E-Commerce Terbaik Wahyuni, Sri; Nasution, Hamidah; Aprilia, Rima
Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Vol. 8 No. 3 (2025): Volume 8 Nomor 3 Tahun 2025 (July - September)
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/proximal.v8i3.6587

Abstract

Indonesia is currently experiencing very rapid technological development compared to a few years ago. The digital era marked by the 4.0 revolution affects every aspect of people's perceptions and purchasing power of an online store or online store which is often referred to as E-Commerce. 96% of internet users have searched for and purchased goods and services online. Of the various choices of E-Commerce in Indonesia, it sometimes makes the public as consumers confused in choosing the best and superior E-Commerce if it is based on several categories such as price, product variations, payment method variations, and so on to make transactions. To help make it easier for consumers to choose the best E-Commerce, an appropriate decision support system is needed. In this study, the implementation of the AHP-MOORA and AHP-SAW methods was used. The best E-Commerce is determined based on the weight of the criteria of 100 respondents who actively use E-Commerce. Stating that the “Shopee” alternative is the best E-Commerce with an AHP-MOORA preference value (rank) of 0.309 and AHP-SAW of 0.974. The "Tiktok Shop" alternative ranks second with an AHP-MOORA preference value of 0.284 and an AHP-SAW of 0.928. The third rank is "Tokopedia" with a preference value of 0.278 on AHP-MOORA and a preference value of 0.907 on AHP-SAW. The conclusion of this study states that the AHP-MOORA and AHP-SAW methods can be used to determine the best E-Commerce.
Analisis Efisiensi Pelayanan Paspor Menggunakan Model Antrean M/M/1 di Kantor Imigrasi Medan Yusmanidar, Yusmanidar; Ningsi, Ria Sagita; Syahfitri, Sella; Aprilia, Rima
Digital Transformation Technology Vol. 5 No. 1 (2025): Periode Maret 2025
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v5i1.6386

Abstract

Penelitian ini membahas efektivitas sistem pelayanan paspor di Kantor Imigrasi Kelas I Khusus TPI Medan dengan pendekatan model antrean M/M/1. Permasalahan yang timbul berkaitan dengan tingginya jumlah permintaan yang tidak sebanding dengan kapasitas layanan, sehingga memicu antrean dan waktu tunggu yang signifikan. Kajian ini menggunakan metode deskriptif kuantitatif dengan menghitung parameter sistem seperti laju kedatangan (?), laju pelayanan (?), dan tingkat pemanfaatan (?). Hasil pengolahan data menunjukkan bahwa sistem beroperasi pada utilisasi penuh (? = 1), dengan rata-rata waktu dalam pelayanan sistem selama 25 menit. Rata-rata terdapat lima pemohon dalam sistem dan satu orang dalam antrean setiap waktu. Temuan ini menunjukkan perlunya peningkatan kapasitas atau prosedur efisiensi layanan untuk mengantisipasi permintaan. Rekomendasi strategi disampaikan untuk mendukung peningkatan kualitas pelayanan publik, khususnya dalam konteks administrasi keimigrasian.
Prediksi Curah Hujan Menggunakan Metode Average Based Dan Fuzzy Time Series Di Kabupaten Deli Serdang Adawiyah, Robiyatul; Aprilia, Rima
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 7, No 4 (2025): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v7i4.23476

Abstract

Salah satu elemen kunci yang mendukung industri pertanian Indonesia adalah curah hujan. Petani harus menggunakan prakiraan curah hujan yang akurat untuk memilih waktu terbaik dalam setahun dan jenis tanaman, terutama di daerah yang rawan perubahan iklim seperti Kabupaten Deli Serdang. Pendekatan Average-Based Fuzzy Time Series digunakan dalam penelitian ini untuk memperkirakan curah hujan. BMKG Kabupaten Deli Serdang menyediakan data sekunder, yang terdiri dari 68 titik data curah hujan bulanan dari Januari 2019 hingga Agustus 2024. Metode ini diawali dengan menentukan universalitas detail, membagi data ke dalam interval berdasarkan rata-rata selisih absolut, melakukan fuzzifikasi, membentuk hubungan logika fuzzy (Fuzzy Logical Relationship dan FLRG), serta menghasilkan prediksi curah hujan. Evaluasi hasil dilakukan menggunakan nilai RMSE dan MAE untuk mengukur tingkat akurasi. Hasil penelitian menunjukkan bahwa metode ini mampu memberikan prediksi yang cukup baik terhadap data curah hujan yang bersifat fluktuatif. Dengan demikian, metode Fuzzy Time Series Berbasis Rata-rata dapat digunakan sebagai salah satu alternatif dalam memprediksi data iklim seperti curah hujan.
Analisis Model Matematika pada Penanggulangan Pencemaran Udara Adella Aulia Mukti; Husein, Ismail; Aprilia, Rima
Leibniz: Jurnal Matematika Vol. 5 No. 02 (2025): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v5i02.630

Abstract

Penelitian ini menggunakan pendekatan kuantitatif dengan metode pemodelan matematika berbasis data sekunder dari Dinas Lingkungan Hidup (DLH) Kota Medan. Data mencakup konsentrasi karbon monoksida (CO), karbon dioksida (CO?), dan oksigen (O?) pada empat kawasan berisiko tinggi pencemaran, yaitu kawasan industri, perkantoran, permukiman, dan area dengan kepadatan kendaraan tinggi. Model yang diterapkan adalah Vector Autoregression (VAR), yang mampu menangkap hubungan dinamis antarvariabel tanpa perlu membedakan variabel endogen dan eksogen. Sebelum pemodelan, dilakukan uji stasioneritas dengan Augmented Dickey-Fuller (ADF), penentuan lag optimal, serta uji kausalitas Granger. Hasil penelitian menunjukkan adanya tren peningkatan konsentrasi CO, penurunan CO?, dan kenaikan moderat kadar O?. Model VAR yang dibangun memiliki akurasi yang baik dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 7,85%, sehingga efektif digunakan untuk peramalan jangka pendek pencemaran udara. Dengan demikian, pemodelan ini dapat menjadi dasar analisis dan perumusan strategi penanggulangan pencemaran udara di Kota Medan.
Application of Geographically Weighted Panel Regression (GWPR) on Tuberculosis Disease in North Sumatra Province Khairani, Sabila; Aprilia, Rima
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 3 (2025): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v10i3.996

Abstract

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis and remains a serious health problem in Indonesia, particularly in North Sumatra Province. The increase in the number of cases from 2021 to 2023 indicates the need for an analytical approach that simultaneously considers spatial and temporal aspects. This study aims to apply the Geographically Weighted Panel Regression (GWPR) method to analyze the development of tuberculosis and identify the factors that significantly contribute to its spread in 33 regencies/cities in North Sumatra. Based on the results of the Chow and Hausman tests, it was found that the Fixed Effect Model (FEM) is the most suitable panel data approach to use before applying the GWPR model. The analysis shows that the three variables that most significantly influence the number of tuberculosis cases spatially are the population size, gender (male), and age ≥14 years. The application of GWPR with adaptive bisquare weighting resulted in the best model with an AIC value of 1141.567 and a coefficient of determination (R²) of 0.99578, indicating that GWPR is a highly effective approach for analyzing the spatial spread of infectious diseases such as tuberculosis. The GWPR model is able to explain the spread of tuberculosis more accurately compared to FEM because GWPR can capture the varying influence of each variable in each region, whereas FEM only produces a single coefficient value that applies to the entire area without considering the existing spatial variations.
Klasifikasi Kualitas Air Sungai Dengan Metode Random Forest Tanjung, Muhammad Afrizal; Aprilia, Rima
SAINTIFIK Vol 11 No 2 (2025): Saintifik: Jurnal Matematika, Sains, dan Pembelajarannya
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/saintifik.v11i2.611

Abstract

Kualitas air sungai memegang peranan penting bagi kesehatan publik dan pelayanan perkotaan, namun banyak sungai di Indonesia menunjukkan indikasi pencemaran. Studi ini menerapkan algoritma Random Forest untuk mengklasifikasikan mutu air tiga sungai di Kota Medan berdasarkan data pemantauan sekunder tahun 2023–2024 dari Dinas Lingkungan Hidup. Dataset berisi 72 observasi dengan sembilan parameter utama, yaitu TSS, pH, BOD, COD, DO, Nitrat, Nitrit, Total Coliform, dan Amonia. Skema pemodelan meliputi pra pengolahan data, pembagian latih–uji 80:20 secara terstratifikasi, pelatihan Random Forest dengan 100 pohon, serta evaluasi menggunakan akurasi dan matriks kebingungan pada subset uji. Hasil menunjukkan akurasi keseluruhan 100 persen pada data uji, dengan ketepatan penuh pada kedua kelas yang dikaji (Kelas II dan Kelas III). Analisis kepentingan fitur mengindikasikan bahwa Total Coliform dan COD merupakan penentu paling dominan, diikuti Nitrat dan DO, sedangkan TSS, pH, Ammonia, dan parameter lain memberi kontribusi menengah hingga rendah. Temuan ini menegaskan efektivitas Random Forest untuk tugas klasifikasi mutu air sungai dan memberikan wawasan prioritas parameter bagi pengendalian pencemaran. Secara praktis, pendekatan ini dapat mendukung pemantauan berbasis data dan pengambilan keputusan pengelolaan kualitas air di tingkat daerah.
Machine Learning-Based Naïve Bayes Classification of Pineapple Productivity: A Case Study in North Sumatra Suendri, Suendri; Aprilia, Rima; Br. Rambe, Ramadiani; Zakaria, Nur Haryani
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24034

Abstract

Background: Pineapple is a major agricultural commodity in Indonesia, especially in North Sumatra, where increasing demand calls for improved productivity. Although machine learning has been widely applied in agriculture, most prior studies on pineapple focus on fruit quality assessment or employ complex, less interpretable models, leaving a gap in lightweight and practical approaches for productivity classification. Objective: This study aims to evaluate the novelty and effectiveness of the Naïve Bayes algorithm in classifying pineapple productivity based on agronomic characteristics, addressing the underexplored use of this method for productivity prediction in pineapple cultivation. Methods: A descriptive quantitative approach was applied using secondary data from the Labuhan Batu Agricultural Extension Center, consisting of 52 records with seven agronomic parameters. The dataset was divided into 31 training and 21 testing samples, and the Naïve Bayes model was implemented using RapidMiner 7.1, with performance measured by accuracy. The small dataset size is recognized as a limitation that may affect generalizability. Results: The Naïve Bayes model achieved an accuracy of 86.67%, effectively distinguishing between productive and unproductive pineapples and demonstrating its suitability for agricultural classification tasks even with limited data. Conclusion: This study highlights the novelty and practicality of applying Naïve Bayes for pineapple productivity classification, offering an interpretable and computationally efficient alternative to more complex models. Future work should address dataset limitations by incorporating larger and more diverse samples and exploring hybrid or ensemble approaches to further enhance performance and support precision agriculture.
Vehicle Routing Problem as a Solution for Determining Goods Delivery Routes PT. Kreasi Beton Nusa Persada Panjaitan, Dedy Juliandri; Aprilia, Rima; Anjeli, Sarifah
JST (Jurnal Sains dan Teknologi) Vol. 12 No. 3 (2023): Oktober
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v12i3.67809

Abstract

VRP distributions have had difficulty overcoming the problem of finding channels with minimal depots to locations that have different places with different total demand. The purpose of this study is to analyze the problem of transportation routes in the distribution of products obtained from the initial location of distribution to users. This type of research is qualitative research. This research was conducted at PT. Nusa Persada Concrete Creations. The Nearest Neighbor method is used to determine the distribution of routes. The Local Search method is carried out to evaluate and improve the distribution of routes carried out at the beginning with the Nearest Neighbors method. The data analysis process consists of several stages with the Nearest Neighbor method and the LocalSearch method. The results of the study, namely the Model Vehicle Routing Problem (VRP) applied in determining ready mix delivery routes at PT. Nusapersada Concrete Creation using nearest and local neighbor methods. Vehicle Routing Problem (VRP) models using nearest and local neighbor methods can be used applied in determining ready mix delivery routes to limited companies. Nusapersada Concrete Creations. This makes distance and time more effective, as well as more cost efficient. New routes generated This is a route improvement solution that PT. The application of the Nusapersada Concrete Creations model results in a new route that reduces the distance closer, faster completion time, and fuel cost savings for truck vehicles compared to the initial route. This makes distance and time more effective, as well as more cost efficient.
Co-Authors Adawiyah, Robiyatul Adella Aulia Mukti Afnaria, Afnaria Afsari, Khaila Amanda Ulayyah Mahaputri Anjeli, Sarifah Aprianingsih, Melinda Ardiansyah, Fikri Nur Atika Nabila Ayilzi Putri Batubara, Nuriman Astuti Br Damanik, Mahyuni Br Surbakti, Rivani Kabrina Br. Rambe, Ramadiani Damanik, Mahyuni Br Damayanti Darmawan, Dian Deasy, Deasy Dedy Juliandri Panjaitan Dewi, Desi Erni Diah Reka Putri Fairuz, Ersya Nurul Fajari Husnul Walid Fayed, Heba A. Fazariani, Nabila Fernanda, Fariz Hakim Fibri Rakhamawati Filia Sari, Rina Firmansyah Firmansyah Hasibuan, Riza Sakhbani Hema Pebria Rollingka Hendra Cipta Husna, Wilia Indah Widya Hanzani Irvan Ginting Ismail Husein, Ismail Khairani, Sabila Laila Agustin Pohan Lisa Setia Ningsih MA, Wilda Syahrani Mahaputri, Amanda Ulayyah Majidah, Nur Marwan Marwan Mawarni Mawarni Mawarni Mawarni Maymunah Tarigan, Siti Melati, Melati Puspita Sari Lubis Miwadari Miwadari Muhammad Harits Azhari Muhammad Ridwan Mutiara, Tia Nasution, Ainil Hafizha Nasution, Hamidah . Nasution, Syahronal Hidayat Ningsi, Ria Sagita Nur Iman Nuri Prasuci Prasetya, Nurul Huda Puspita, Reni Putri Rahma Novia Putri, Ayilzi Putri, Chindy Aulia Rahayu, Tiwi Rakhmawati, Fibri Rina Filia Sari Rina Filia Sari, Rina Filia Rina Widyasari Riri Syafitri Lubis Riri Syahfitri Lubis Rismayani Rismayani Rismayani Rismayani Riza Faishol Riza Sakhbani Hasibuan Sajaratud Dur Sajaratud Dur, Sajaratud Sapta, Andy Sari, Della Arsita Setiawan, Agun Siregar, Annisa Fadhillah Putri Siregar, Aulia Rahman Siregar, Machrani Adi Putri Siregar, Nurmala Sari Siregar, R Maisaroh Rezyekiyah Siti Aisyah Siti Handayani Sri Wahyuni Suci Pranasari Suendri Suendri, Suendri Sugarda, Ahmad Suhaimi, Syech Suhendra, Irfan Sulaiman Ananda Harahap Syahfitri, Ellysa Syahfitri, Sella Syahputri, Nenna Irsa Tanjung, Muhammad Afrizal Tarigan, Umar Abdul Gani Taufik Hidayat Manurung Tri Handayani Triase Triase Usna, Wilia Via, Azizah Nurma Walid, Fajari Husnul Widyasari, Rina Wulandari, Mitha Yolandini Eka Putri Yuda, Muhammad Wira Yulinda, Jeni YUSMANIDAR, YUSMANIDAR Zakaria, Nur Haryani