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Riri Syafitri Lubis

Universitas Islam Negeri Sumatera Utara, Medan, Indonesia

Author-ID : 3325332

Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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The comparison between the nearest neighbor algorithm and the a-star algorithm to determine the optimal route for distributing napkin tissue Riri Syafitri Lubis; Rima Aprilia; Ropiqoh Ropiqoh; Silvia Harleni
AXIOM : Jurnal Pendidikan dan Matematika Vol 13, No 1 (2024)
Publisher : State Islamic University of North Sumatra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30821/axiom.v13i1.19977

Distribution is a factor that greatly influences the success of a company in selling its products. PT. Medan Jutarasa is a company that operates in the napkin tissue industry and has a Distribution Center (DC) to supply products to distributors. Distribution of products to consumers requires appropriate planning and consideration of which route to use to obtain more time-efficient transportation costs. In the delivery process, the company experienced problems, especially in the distribution route. The Nearest Neighbor algorithm searches for customers to serve based on the shortest distance from the vehicle's last location for further distribution. Meanwhile, the A-Star algorithm finds the shortest path using minimum cost. This research aims to compare the Nearest Neighbor algorithm and the A-Star algorithm to determine the optimal route for distributing tissue napkins by PT. Millionaire Medan. Based on the research results, it was found that the route using the Nearest Neighbor algorithm was more optimal than the A-Star algorithm in the distribution of tissue napkins by PT. Millionaire Medan.

Optimasi Vehicle Routing Problem pada Distribusi Tabung LPG Menggunakan Metode Ant Colony Optimization Devitasari Simamora; Riri Syafitri Lubis; Sri Ulfa Rahayu
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.37481

Inefficient distribution can increase operational costs; therefore, determining optimal routes is essential to support an efficient distribution process. This problem can be formulated as a Vehicle Routing Problem (VRP), which concerns optimizing vehicle routes from a depot to multiple destinations with minimum travel distance. This study aims to optimize the distribution route of LPG cylinders at PT Jaya Sari Artha by considering 12 distribution points. The method used is Ant Colony Optimization (ACO), a heuristic algorithm inspired by the foraging behavior of ants in finding the shortest path. The data used consist of actual travel distances between distribution points obtained from Google Maps. The results show that the implementation of ACO in the VRP model produces a distribution route with a total distance of 117.40 km, shorter than the company’s initial route of 134.50 km. Thus, a distance saving of 17.10 km or 12.72% was achieved. These findings indicate that the ACO method is effective in solving VRP and improving the efficiency of LPG cylinder distribution in a real-world case.

Penerapan Logika Fuzzy Pada Pengendalian Mutu Minyak Kelapa Sawit dengan Metode Statistical Quality Control di PKS Ptpn II Pagar Merbau Dhea Auliya Ramadhani; Riri Syafitri Lubis; Rina Widyasari
Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Vol. 8 No. 4 (2025): Volume 8 Nomor 4 Tahun 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/proximal.v8i4.7151

Pengendalian mutu Crude Palm Oil (CPO) merupakan faktor krusial untuk menjaga standar kualitas dan daya saing PKS PTPN II Pagar Merbau. Metode konvensional seperti Statistical Quality Control (SQC) umum digunakan untuk memantau stabilitas proses produksi melalui peta kendali. Namun, SQC memiliki keterbatasan dalam menangani data yang bersifat ambigu atau samar (ketidakpastian) karena pendekatannya yang crisp (tegas), yang hanya mengklasifikasikan status proses sebagai "terkendali" atau "di luar kendali". Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pengendalian mutu CPO dengan mengintegrasikan metode SQC dan Logika Fuzzy. Penelitian ini menggunakan data parameter mutu utama CPO, seperti Asam Lemak Bebas (ALB), Kadar Air , dan Kadar Kotoran yang dianalisis terlebih dahulu menggunakan peta kendali SQC untuk menentukan batas-batas kontrol statistik. Selanjutnya, data tersebut dijadikan variabel input untuk Sistem Inferensi Fuzzy (FIS). Logika Fuzzy digunakan untuk memetakan data input yang ambigu ke dalam himpunan fuzzy (misalnya: Rendah, Normal, Tinggi) dan memprosesnya melalui basis aturan (IF-THEN) untuk menghasilkan output kualitatif berupa status mutu CPO (misalnya: Sangat Baik, Baik, Cukup, Buruk). Hasil penelitian menunjukkan bahwa penerapan Logika Fuzzy mampu memberikan penilaian status mutu yang lebih fleksibel, adaptif, dan informatif dibandingkan metode SQC murni. Sistem ini dapat memberikan peringatan dini yang lebih sensitif terhadap pergeseran kecil dalam proses, sehingga membantu manajemen PKS PTPN II Pagar Merbau dalam mengambil keputusan korektif yang lebih cepat dan tepat untuk menjaga konsistensi mutu CPO.

Pengaruh Model Pembelajaran Kooperatif Tipe Think Pair Share Terhadap Kemampuan Berpikir Kreatif Matematis Siswa SMP Febri Muhamar Chaniago; Riri Syafitri Lubis; Suci Dahlya Narpila
Educational Journal Vol. 1 No. 3 (2026): FEBRUARI-APRIL
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/vs25ap22

The research, entitled "The Effect of the Think Pair Share Cooperative Learning Model on Junior High School Students' Mathematical Creative Thinking Skills," is based on the fact that in mathematics learning, teachers often teach students in conventional learning, where learning always focuses on teacher explanations. Consequently, not many teachers are able to help students develop thinking skills in solving mathematical problems. Therefore, teachers need to use good learning methods to help test students' creative thinking skills in mathematics. The research methodology used quantitative research with a posttest control group design approach. The study population was students of Madrasah Tsanawiyah Al Ittihadiyah Medan with a sample size of 22 students in the experimental group and 22 in the control group. The sampling technique used by the researcher was cluster random sampling. The data collection technique was a mathematical creative thinking ability test. Instrument validity testing used each formula assisted by using Microsoft Excel. An Independent Sample t-Test was also used to test the research hypothesis. The results of the study revealed that there was an influence between the cooperative learning model of the think pair share type on the mathematical creative thinking abilities of junior high school students. This can be seen from the results of the Independent sample t-test which showed that the significance value was 0.000 < 0.05 so that H0 was rejected and H1 was accepted. From the research findings above, the think pair share type cooperative learning model can be used as an alternative learning model in the mathematics learning process, especially for material that requires creative thinking skills.

MARKETING GAMES AND SENSITIVITY ANALYSIS FOR ANY NUMBER OF COMPANIES Almira Amir; Ruth Mayasari Simanjuntak; Yenny Suzana; Riri Syafitri Lubis; Fatmah Syarah; Fajriana Fajriana; Zahedi Zahedi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0927-0940

In the business world, advertising plays a crucial role in shaping market dynamics. This study analyzes advertising competition among companies by calculating the optimal profits for two to four competitors and postulating a general formula for a larger number of companies. Sensitivity analysis is employed to observe how changes in advertising parameters affect profits. The simulation results indicate that in the case of four companies, the optimal spending (Xopt) ranges from 137246 to 191288, while the optimal profit (Popt) ranges from 38693.1 to 92702. The sensitivity analysis shows that companies with higher advertising effectiveness achieve greater profits, whereas those with lower effectiveness tend to experience reductions in both allocation and profit. With the aid of Maple and Excel, this research extends previous advertising competition models by providing a comprehensive framework for optimizing advertising budgets in oligopolistic markets.

Risk Analysis of Oyster Mushroom Cultivation Success through Artificial Neural Network with Backpropagation Algorithm Fazri Aslam; Riri Syafitri Lubis
KUBIK Vol 10 No 1 (2025): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung

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

Consumption mushroom cultivation is still rare in most parts of Indonesia, although the demand for this agricultural product continues to increase. Mushroom business opportunities are actually quite promising. This research aims to analyze the prediction of the risk level of oyster mushroom cultivation success using the artificial neural network method with the Backpropagation algorithm. This research combines qualitative and quantitative approaches, with data analysis methods in the form of Backpropagation algorithm training implemented through MATLAB software. Based on the results of testing or training conducted using the 5-3-1 Artificial Neural Network (JST) architecture and Epoch 1, the minimum error is 0.6 or 4 kg of yield (IDR 80,000), while the maximum error is 0.7 or 5 kg of yield (IDR 100,000). with a training MSE of 0.0964 with This means that artificial neural networks can create patterns to predict the yield of oyster mushroom cultivation.

Investment Risk Analysis of Gold, the Indonesia Composite Index (IHSG), and BBCA Stock in Indonesia using the Value At Risk (Var) Method With A Variance–Covariance Approach Aida Febriana Tanjung; Hani Maulida Hasibuan; Panca Taufik Kurahman; Fakhrur Rozi Nasution; Riri Syafitri Lubis
JISTech (Journal of Islamic Science and Technology) Vol 11, No 1 (2026)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v11i1.28790

Investments in various financial instruments such as gold, the Indonesia Composite Index (IHSG), and individual stocks carry different levels of risk due to market price fluctuations. These differences require investors to understand potential risks in order to manage their portfolios optimally. Therefore, a quantitative risk measurement method is needed. Value at Risk (VaR) is a method used to estimate the maximum potential loss at a given confidence level and time horizon. This study aims to analyze and measure investment risk in gold, IHSG, and BBCA stock in Indonesia using the Value at Risk (VaR) method with a variance–covariance approach. The data consist of monthly closing prices from April 2024 to March 2025, implying a 1-month VaR horizon with confidence levels of 90%, 95%, and 99%. The results show that the VaR value at the 95% confidence level (1-month horizon) is (4,033.25) for gold, (8,064.47) for IHSG, and (7,931.17) for BBCA stock. At a higher confidence level of 99%, the VaR increases to (5,704.31) for gold, (11,405.74) for IHSG, and (11,217.20) for BBCA stock. These findings indicate that IHSG and BBCA stock have higher potential maximum losses compared to gold, consistent with their higher volatility levels. These results suggest that the variance–covariance VaR method provides measurable quantitative risk estimates across different confidence levels and time horizons, making it useful for investment decision-making and structured portfolio risk management.

Penerapan Model Arima Pada Nilai Penutupan Indeks Harga Saham Gabungan Untuk Data yang Hilang Elma Dwi Ariana Aprilia Zam; Widi Ihdina Nabilla; Ahmad Syahrial Pohan; Riri Syafitri Lubis
JISTech (Journal of Islamic Science and Technology) Vol 10, No 2 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i2.28361

Penelitian ini bertujuan untuk menerapkan model Autoregressive Integrated Moving Average (ARIMA) meramalkan nilai penutupan Indeks Harga Saham Gabungan (IHSG) harian periode November 2024 hingga November 2025 yang mengandung missing value. Ditemukan sebanyak 121 data hilang yang menyebabkan ketidakteraturan interval waktu, sehingga dilakukan penanganan missing value menggunakan metode interpolasi linear. Tahapan analisis meliputi eksplorasi data, pengujian kestasioneran menggunakan uji Augmented Dickey-Fuller (ADF), differencing untuk mencapai kestasioneran, identifikasi model menggunakan ACF, PACF, dan Extended Autocorrelation Function (EACF), serta pemilihan model terbaik berdasarkan kriteria Akaike Information Criterion (AIC). Hasil analisis menunjukkan bahwa model ARIMA (0,1,1) merupakan model terbaik dengan nilai AIC terendah dibandingkan model kandidat lainnya. Model ini juga memenuhi asumsi diagnostik residual yang meliputi white noise, normalitas, dan homokedastisitas. Evaluasi akurasi model menunjukkan nilai RMSE sebesar 985,29 dan MAPE sebesar 11,61%, yang mengindikasikan kemampuan peramalan yang cukup baik. Dengan demikian, model ARIMA (0,1,1) dapat digunakan sebagai alat bantu dalam peramalan pergerakan IHSG dan mendukung pengambilan keputusan investasi.

Penerapan Metode Regresi Probit Biner dalam Menganalisis Faktor-Faktor yang Berpengaruh pada Tingkat Partisipasi Angkatan Kerja Wanita Ristika Dian Utami; Riri Syafitri Lubis; Hendra Cipta
Justek : Jurnal Sains dan Teknologi Vol 8, No 2 (2025): Juni
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i2.29162

Abstract: The female labor force participation rate (LFPR) describes the percentage of the female population of working age who are engaged in economic activities. In this condition, the problem that often arises is that the LFPR of women is still lower than the LFPR of men, and the gap between the two is quite far. The purpose of this study is to find out what factors affect the LFPR of women in North Sumatra Province. The method used is binary probit regression method. The data revealed that 45.5% of districts/cities in North Sumatra Province were classified as low LFPR category. The results showed that the level of education (X1) and the informal sector (X5) had a significant effect on female TPAK with a classification accuracy value of 93.9%, indicating that the binary probit regression model used was able to classify the data correctly with a high level of accuracy.Abstrak: Tingkat partisipasi angkatan kerja (TPAK) wanita menggambarkan persentase populasi wanita pada usia kerja yang terlibat dalam kegiatan ekonomi. Dalam kondisi ini, masalah yang sering muncul adalah TPAK wanita masih lebih rendah dari TPAK laki-laki, dan kesenjangan antara keduanya cukup jauh. Tujuan dari penelitian ini yaitu untuk mengetahui faktor-faktor apa saja yang berpengaruh terhadap TPAK wanita di Provinsi Sumatera Utara. Metode yang digunakan adalah metode regresi probit biner. Data mengungkapkan bahwa 45,5% kabupaten/kota di Provinsi Sumatera Utara tergolong dalam kategori TPAK rendah. Hasil penelitian menunjukkan tingkat pendidikan (X1) dan sektor informal (X5) berpengaruh signifikan terhadap TPAK wanita dengan nilai ketepatan klasifikasi sebesar 93,9% menandakan model regresi probit biner yang digunakan mampu mengklasifikasikan data dengan tepat memiliki tingkat akurasi yang tinggi.

PENERAPAN METODE MONTE CARLO DALAM MEMPREDIKSI JUMLAH PENGANGGURAN DI SUMATERA UTARA mutia hatina dewi; Riri Syafitri Lubis; Hendra Cipta
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4642

Abstract: Unemployment is still a problem that often occurs in every region, including in every area in North Sumatra. Unemployment rates can inevitably lead to an increase in poverty. And this can continuously trigger other losses such as rampant robbery, theft, fraud and even crimes that will harm the general public. The purpose of this study, among others, is to predict the number of unemployed in each district/city of North Sumatra from 2021 to 2025 using the Monte Carlo method and find out whether this method can be used to predict population such as unemployment. The advantage of this method lies in strong numerical calculations in simulating data by producing accurate values and the results of predicting the number of unemployed in 2021, 2023 and 2024 have decreased with the number of unemployed each year ranging from 426383, 426383 and 399403 people. Meanwhile, for 2022 and 2025 it will be an increase of 43260 and 41605 people. Keyword: Predicting, Number of Unemployed, Monte Carlo Abstrak: Pengangguran masih menjadi permasalahan yang kerap terjadi di setiap daerah termasuk di setiap daerah yang ada di Sumatera Utara. Tingkat pengangguran yang tidak terelakan dapat memicu terjadinya peningkatan kemiskinan, kriminalitas. seperti maraknya perampokan, pencurian, penipuan bahkan kejahatan yang akan merugikan khalayak ramai maupun kesenjangan sosial dan dampak negatif lainnya. Tujuan dari penelitian ini antara lain untuk memprediksi jumlah pengangguran di setiap daerah Sumatera Utara perkabupaten/ kota tahun 2021 sampai dengan 2025 dengan menggunakan metode Monte Carlo serta mengetahui apakah metode tersebut dapat digunakan dalam memprediksi kependudukan seperti pengangguran. Keunggulan metode ini terletak pada perhitungan numerik yang kuat dalam mensimulasikan data dengan menghasilkan nilai yang akurat dan hasil dari memprediksi jumlah pengangguran di tahun 2021, 2023 dan 2024 mengalami penurunan dengan jumlah pengangguran disetiap tahunnya berkisar 426383, 426383 dan 399403 jiwa. Sedangkan untuk tahun 2022 dan 2025 mengalami kenaikan sebesar 43260 dan 41605 jiwa. Kata kunci: Prediksi, Jumlah Pengangguran, Monte Carlo

Co-Authors Ahmad Sugarda Ahmad Syahrial Pohan Aida Febriana Tanjung Ainun Palihah Almira Amir Ananda, Lyra Anggeraini, Maulida Anggi Pranata Annisa, Nur Alvi Arjuna, Dimas Bagus Aslam, Fazri Aulia Turrizqiya Batu, Annisa Rajaq Lumban Bella Syahrani Nasution Blaster, Irena Br Siahaan, Erika Handayani Cynthia, Mayang Modelina Dara Nurul Hasnah Dedy Juliandri Panjaitan Devitasari Simamora dewi, mutia hatina Dhea Auliya Ramadhani Dian Darmawan Didik Santoso Didik Santoso Dinda Renata Cecilia Dwi Haprida Ningsih Elma Dwi Ariana Aprilia Zam Elma Dwi Ariana Aprilia Zam Elpita Sari Hasibuan Erika Handayani Br Siahaan Evi Borliana Siregar Fachrur Rozi Fadhliyah, Annisa Fadilatus Sahraini Siregar Fadillah, Yanna Rezki Fajriana Fajriana Fajriana, Fajriana Fakhrur Rozi Nasution Farwansyah, Mhd Rio Fatmah Syarah Fatmawati, Ayu Isnaini Fazri Aslam Febri Muhamar Chaniago Fernando, Anjas Fikri Husin Batubara Fuja Nauli Pasaribu Giawa, Freddy Gishela Agra Moukia Gurusinga, Ditha Aulia Hani Maulida Hasibuan Harleni, Harleni Hazizah, Salsabillah Hendra Cipta Heni Pujiastuti Ilham Salim Siregar Ilham Syaputra Indah Kholila Indah, Windi Rezeki Ir Zulkarnain, Ayu Najmita Binti Irena Blaster Ismail Husein, Ismail Kartika , Dinda Khairun Nikmah Latersia, Egya Dora Lisa Setia Ningsih M Agung Pradana Manurung, Silvi Khairiyah Maudya Nur Azura Mhd Ikhsan Rifki Mohammad Badri Muhammad Arfie Munawar Muhammad Farhan Mingka Muhammad Vikry Rezky Rambe Muliawan, Hari mutia hatina dewi Nadhila, Nurul Nasution, Alfina Febriani Nasution, Dafa Al Qifti Nasution, Fakhrur Rozi Nasution, Hamidah . Neliwati Neliwati Nenna Irsa Syahputri Nina Amanda Nova Audry Utami Nurmadani Nurmawati Nurmawati Nurmawati Nurul Nadhila Nusantara, Badai Charamsar Palihah, Ainun Panca Taufik Kurahman Pertiwi, Fina Nur Pohan, Siti Rolizah Pradana, M Agung Prasetya, Nurul Huda Pratiwi, Miftah Pulungan, Ahmad Fauzan Putri Harahap, Rahmelia R. Maisaroh Rezyekiyah Siregar Rahma Miyati Rahmat Darmawan, Rahmat Rakhmawati, Fibri Riani Dwi Lestari Ricka Afriani Rima Aprilia Rima Aprilia Rina Filia Sari Rina Filia Sari, Rina Filia Rina Sari Filia Rina Widyasari Rina Widyasari Ristika Dian Utami Ritonga, Nurhalimah Rivani Kabrina Br Surbakti Rizkina, Ayu Rizky Mulyani Ropiqoh Ropiqoh Ropiqoh, Ropiqoh Rusydi Ananda Ruth Mayasari Simanjuntak Ruth Mayasari Simanjuntak Sahraini Siregar, Fadilatus Sajaratud Dur Samsudin, Samsudin Sari, Evi Indah Serdano, Akbar Silvia Harleni Sintia Agustina Siregar Siregar, Evi Borliana Siregar, Fadilatus Sahraini Siregar, Tanti Jumaisyaroh Siti Jubaidah Siti Zunaida Nasution Sri Ulfa Rahayu Suci Dahlya Narpila, Suci Dahlya Suci Permata Sari Suendri, Suendri Sulaiman Ananda Harahap Supiah Supiah Susanti, Komaria Susilowati, Rahmi Suzana, Yenny Syafitri, Ellysa Syahfitri, Fatharani Syahputra, Bayu Teza Syahputri, Linna Syahputri, Nenna Irsa Syarah, Fatmah Tanti Jumaisyaroh Siregar Tri Amisri, Nurul Hasanah Tri Handayani Tri Lutfiah Wardah Turrizqiya, Aulia Utami, Destia Nada Vani Hajari Wenny Marta Dolok Saribu Widi Ihdina Nabilla Widyasari, Rina Widyasari, Rina Windi Rezeki Indah Wulandari Wulandari Wulandari, Mitha Yahfizham Yahfizham Yenny Suzana Yoffa Sunita Yulanda Novita Zebua Yulinda, Jeni Zahedi Zahedi Zakaria Alfikri Sirait Zam, Elma Dwi Ariana Aprilia

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