Article Per Year (5 Year)
p-Index From 2021 - 2026
8.888
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 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 Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika 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 Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat
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 Social Sciences Transportation Other

Published : 71 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 71 Documents
Search

 4   5   6   7   8 
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.
Membentuk Generasi Berprestasi Melalui Edukasi Dan Pembinaan Agama Di Desa Pematang Cengkering Putri, Ayilzi; Rismayani, Rismayani; Mahaputri, Amanda Ulayyah; Hasibuan, Riza Sakhbani; Mawarni, Mawarni; Aprilia, Rima
Al-Ijtimā': Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2024): Oktober
Publisher : Lembaga Penelitian, Publikasi Ilmiah dan Pengabdian kepada Masyarakat (LP3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53515/aijpkm.v5i1.180

Abstract

Community service activities through the Real Work Lecture (KKN) program aim to make a tangible contribution to society through education and religious guidance, thereby enhancing the knowledge and skills of the community, especially the younger generation, to become individuals who excel both academically and spiritually. This KKN program is in line with one of the main pillars of the Tri Dharma of Higher Education, which is community service. In this program, students are given the opportunity to share knowledge and actively participate in education and the instillation of religion for the generation in Pematang Cengkering Village. The educational and religious activities that have been carried out, such as teaching in elementary schools, mentoring in kindergartens, evening Quran recitation, tutoring, and the Smart Kids Festival, have shown a significant positive impact on the academic development and character of children in Pematang Cengkering Village. These programs not only help students understand their lessons, but also build their self-confidence, strengthen their character, and enhance their spiritual quality, thus shaping a generation that excels in both academic and spiritual aspect.
PLANNING OF RAW MATERIAL INVENTORY TO MAKE TOFU METHOD WITH MATERIAL REQUIRETMENSPLANNING (MRP) Damayanti; Filia Sari, Rina; Aprilia, Rima; Iman, Nur
Journal of Mathematics and Scientific Computing With Applications Vol. 3 No. 2 (2022)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v3i2.79

Abstract

UD. Ai Kampung Bilah Tofu Factory, Labuhan Batu Regency is an industry that is engaged in the processing of Tofu. The purpose of this study is to determine the amount of tofu production from forecasting the number of requests for the previous period. Problem with UD. The aim of the Kampung Bilah Tofu Factory is that it has not implemented rules in controlling the supply of raw materials. In the production process, there are often obstacles, namely the use of raw materials and orders that are not appropriate. Optimum planning and inventory of material requirements is carried out using the Material Requirement Planning method. MRP is a method of planning and scheduling better inventory on a product that is produced. In this study the Material Requirement Planning method, the lot sizing technique used is Lot For Lot, Economic Order Quantity, Priode Order Quantity. Based on the calculation results, Material Requirement Planning using the lot sizing technique, namely Lot For Lot, produces a total cost of Rp. 2,640,000 minimum orders for raw materials.
Application of the Support Vector Regression Method with the Grid Search Algorithm to Predict Movement Gold Price Puspita, Reni; Cipta, Hendra; Aprilia, Rima
Jurnal Pijar Mipa Vol. 19 No. 2 (2024): March 2024
Publisher : Department of Mathematics and Science Education, Faculty of Teacher Training and Education, University of Mataram. Jurnal Pijar MIPA colaborates with Perkumpulan Pendidik IPA Indonesia Wilayah Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpm.v19i2.6607

Abstract

Gold is an investment with the smallest risk because it can be sold anytime and anywhere. In Indonesia, gold bullion as an investment product is known for its purity level of 99.99%, namely gold bullion produced by PT. Aneka Tambang (Antam) through its Precious Metals business unit. Apart from its pure production, Antam gold bullion is easier to resell anytime and anywhere because it has an official certificate from the international gold standardisation institution, namely LBMA (London Bullion Market Association), to more easily estimate the value of gold bullion when sold. To overcome this, predictions of future gold prices are needed. In this research, one of the prediction methods is Support Vector Regression with the Grid Search Algorithm. In this method this method will be used to predict the price of gold, which aims to predict and find out the price of gold one year in the future to produce a level accuracy (MAPE) of 5.43% and the prediction of gold prices increasing from 2023-June-01 to 2024-March-23 while experiencing a decline starting in 2024-March-24. Research by examining the relationship between variables, which emphasises data consisting of numbers so that it is analysed based on statistical procedures using the Support Vector Regression method with data sourced from the daily price of gold bullion through PT. Gallery 24 Pawnshops, North Sumatra. Where this method is very well used in predicting by choosing the best kernel used is the linear kernel because, from these three kernels, the best hyperparameters were obtained for predicting gold price movements using a linear kernel with a division for training and testing data of 60: 40. The MAPE value obtained was 5.43.
Monte Carlo Simulation Of Estimating Clean Water Supplies Walid, Fajari Husnul; Dur, Sajaratud; Aprilia, Rima
ZERO: Jurnal Sains, Matematika dan Terapan Vol 5, No 1 (2021): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v5i1.11099

Abstract

Estimates are important tools in effective and efficient planning for predicting future events. Identical estimates of the future values of a variable for planning or decision making of a situation to estimate future values. Monte Carlo simulation is a simulation model that involves a series of random and sampling with a probability distribution that can be known and determined, then this simulation can be used. In this study, data is taken from the amount of water usage in PDAM Tirtanadi H.M branch. Yamin, North Sumatra from January 2018 to June 2019. Then, the data is processed and analyzed using Monte Carlo Simulation to determine the forecast results in the years that follow. The result is an estimated amount of water usage in 2019 and 2020 at PDAM Tirtanadi H.M branch. Yamin, North Sumatra is 8,604,556 and 8,592,873. The estimated amount of water use is down from the amount of water use in 2018 which reached 8,685,356. The amount of water usage in 2018, 2019 and 2020 decreases by about .
SIMULASI PENGENDALIAN PERSEDIAAN ALAT TULIS KANTOR PADA DINAS PERKEBUNAN DAN PETERNAKAN PROVINSI SUMATERA UTARA DENGAN METODE MONTE CARLO Sari, Rina Filia; Aprilia, Rima; Widyasari, Rina; Afnaria, Afnaria; Suhaimi, Syech; Putri, Chindy Aulia
Jurnal Pengabdian Mitra Masyarakat Vol 3, No 2 (2024): Edisi Maret
Publisher : Universitas Islam Sumatear Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/jurpammas.v3i2.9284

Abstract

In a Government Agency, office stationery supplies are an absolute necessity. The provision of adequate office stationery will facilitate performance. This study aims to predict the demand for office stationery using Monte Carlo Simulation. Monte Carlo is a numerical analysis method that uses random number samples. The data used in this study are primary data in the form of the number of stock items and the number of requests for goods from January to December 2023. The accuracy result using the Monte Carlo method for Year 2024 is 91.78%. This shows that the Monte Carlo method simulation can be used to predict the demand for stationery for the following year.
Penggunaan Model Aritmatik dan Geometrik dalam Laju Pertumbuhan Penduduk di Kota Medan pada Tahun 2029 Syahfitri, Sella; Deasy, Deasy; Sugarda, Ahmad; Aprilia, Rima
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 1 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/2xnt8c71

Abstract

Population growth is an important issue for the country in Indonesia because a significant increase in population growth can lead to a lack of housing for the growing population. This study aims to determine the rate of population growth in the city of Medan by using arithmetic and geometric models to find the results of calculations of the population of the city of Medan in the next 10 years based on standard deviations and correlation coefficients. The use of the arithmetic (linear) model for population growth increases constantly and is not seen from the number of previous populations, while the geometric (exponential) model assumes the number of people seen from how large the previous population is, then the growth every year will be rapid (not fixed). The results show that the geometric model has the smallest standard deviation value of 61,320,657 compared to the arithmetic model with the largest standard deviation value of 61,321,357. It can be concluded that the geometric model is used in calculating the population growth rate of the city of Medan in 2029 because the geometric model has the smallest standard deviation which produces the population in 2020 of 2,301,101 people and in 2029 of 2,501,069
Analisis Pertumbuhan Mendekati Kapasitas Terhadap Status Gizi Anak dengan Model Logistik Aprilia, Rima; Siregar, Aulia Rahman; Fernanda, Fariz Hakim; Suhendra, Irfan; Siregar, Nurmala Sari
AKSIOMA : Jurnal Sains Ekonomi dan Edukasi Vol. 2 No. 1 (2025): AKSIOMA : Jurnal Sains, Ekonomi dan Edukasi
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/ws1rtt04

Abstract

The prevalence of malnutrition in children under five in Indonesia shows an estimate of future nutritional status based on current and past trends. A logistical population model is used in this study, which assumes that at some point in time, the population will reach equilibrium. The purpose of this study is to analyze the nutritional status of children under five aged 0-23 months in 2027 (t=9) using a logistics model. The data used came from the Central Statistics Agency (BPS) between 2016 and 2018, and is predicted for the period 2019 to 2027, assuming that the capacity limit (k) is 10,611.02. This study shows that type I and II logistics models can be used accurately to understand near-capacity growth related to children's nutritional status. The analysis shows that by 2027, it is estimated that there will be 359.35 children under five who will achieve optimal nutritional status.
Forecasting passport application demand using the chen average-based FTS method at the Medan immigration office Laila Agustin Pohan; Aprilia, Rima
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529274

Abstract

The rising demand for passport services in Medan reflects increasing public mobility and highlights the need for accurate forecasting. This study aims to predict the number of passport applications at the Class I Special Immigration Office (TPI) Medan using the Chen Average-Based Fuzzy Time Series method. The research applies a quantitative approach using secondary monthly data from January 2020 to September 2025. The forecasting procedure involves defining the universe of discourse, forming intervals, conducting fuzzification, developing fuzzy logical relationships and groups (FLR/FLRG), and performing defuzzification to produce forecast values. The results indicate that the model effectively captures fluctuations in actual data, achieving a Mean Absolute Percentage Error (MAPE) of 38.61%. These findings classify the model’s accuracy as fairly good for forecasting administrative time series data. Therefore, the Chen Average-Based Fuzzy Time Series method provides a reliable analytical tool for predicting future passport demand and supports improved planning and policy development in immigration services.
Co-Authors Adawiyah, Robiyatul Adella Aulia Mukti Afnaria, Afnaria Afsari, Khaila Amanda Ulayyah Mahaputri Andy Sapta Anjeli, Sarifah Annisa Fadhillah Putri Siregar Aprianingsih, Melinda Ardiansyah, Fikri Nur Atika Nabila Ayilzi Putri Br. Rambe, Ramadiani Damanik, Mahyuni Br Damayanti Darmawan, Dian Deasy, Deasy Dedy Juliandri Panjaitan Della Arsita sari Dewi, Desi Erni Diah Reka Putri Ellysa Syahfitri 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 Mahyuni Br Damanik Majidah, Nur Marwan Marwan Mawarni Mawarni Mawarni Mawarni 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 Nuriman Astuti Batubara 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 Sakhbani Hasibuan Sajaratud Dur Sajaratud Dur, Sajaratud Sapta, Andy Setiawan, Agun Siregar, Annisa Fadhillah Putri Siregar, Aulia Rahman Siregar, Machrani Adi Putri Siregar, Nurmala Sari Siti Aisyah Siti Handayani Sri Wahyuni Suci Pranasari Suendri Suendri, Suendri Sugarda, Ahmad Suhaimi, Syech Suhendra, Irfan Sulaiman Ananda Harahap Syahfitri, Sella Syahputri, Nenna Irsa Tanjung, Muhammad Afrizal Tarigan, Umar Abdul Gani Taufik Hidayat Manurung Tri Handayani Triase Triase Usna, Wilia Walid, Fajari Husnul Widyasari, Rina Wulandari, Mitha Yolandini Eka Putri Yuda, Muhammad Wira Yulinda, Jeni YUSMANIDAR, YUSMANIDAR Zakaria, Nur Haryani