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All Journal Media Statistika Matematika: Jurnal Teori dan Terapan CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Cendekia : Jurnal Pendidikan Matematika International Journal of Supply Chain Management Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications Kumawula: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat International Journal of Research in Community Services Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling SisInfo : Jurnal Sistem Informasi dan Informatika Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Herlina Napitupulu
Departemen Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Padjadjaran
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Penerapan Model Support Vector Machine Pada Kasus Klasifikasi Teks Berdasarkan Tujuan SDGS Ke Tiga, Empat, Dan Enam Saprilian Hidayat; Herlina Napitupulu; Nurul Gusriani
SisInfo Vol 6 No 2 (2024): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/sisinfo.v6i2.893

Abstract

Text classification is a branch of Natural Language Processing (NLP) that enables computers to understand, interpret, and respond to text in a comprehensible language. Classifying texts based on the Sustainable Development Goals (SDGs) is crucial because monitoring the progress of SDGs remains a challenge. Previous studies have shown that text classification techniques using the BERT model have proven effective in classifying texts based on SDG goals. This research utilizes data sourced from the OSDG community website. The method employed is the Support Vector Machine Multiclass (SVM) model and TF-IDF word representation. This research aims to classify texts based on the Sustainable Development Goals (SDGs), specifically focusing on goals three, four, and six., evaluate the model's performance based on the F1-Score metric, and determine the optimal values for the hyperparameters regularized constant and gamma in the RBF kernel. The results of this research yielded a default F1-Score of 97.95% and a post-tuning F1-Score of 97.95%, with the optimal values of C=1, gamma=1, and kernel=rbf.
Determining Premium for Disaster Reinsurance Program through Supply Chain Risk Management: An Application of Peak Over Threshold (POT) Approach Sukono, Sukono; Subartini, Betty; Napitupulu, Herlina; Novitasari, Ela; Santoso, Agus; Ghazali, Puspa Liza; Saputra, Jumadil
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.4305

Abstract

The purpose of this study is to determine the pricing (premium) for disaster reinsurance program. For those, this study uses the Peak Over Threshold (POT) approach, where the method pays attention to the pattern of heavy tail behaviour on the number of victims killed due to disaster events through extreme values with a reference value called the threshold u. The results of the analysis showed that the reinsurance premiums for flood disaster per year that must be paid by insurance company is IDR 712,008,900.50 with the maximum amount of reinsurance risk, L is IDR20,000,000,000.00, the insurance company retention, S is IDR200,000,000.00, the sensitivity minimum number of victims in one disaster event  with 5 people. In conclusion, the reinsurance premium per year that must be paid by insurance companies to reinsurance companies will be increasing when the insurance company retention S is smaller, the maximum amount of risk covered by reinsurance L is greater, and the number of victims died u decreases.
Estimated Value-at-Risk Using the ARIMA-GJR-GARCH Model on BBNI Stock Hidayana, Rizki Apriva; Napitupulu, Herlina; Sukono, Sukono
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.317

Abstract

Stocks are investment instruments that are much in demand by investors as a basis in financial storage. Return and risk are the most important things in investing. Return is a complete summary of investment and the return series is easier to handle than the price series. The movement of risk of loss is obtained from stock investments with profits. One way to calculate risk is value-at-risk. The movement of stocks is used to form a time series so that the calculation of risk can use time series. The purpose of this study was to find out the Value-at-Risk value of BBNI Shares using the ARIMA-GJR-GARCH model. The data used in this study was the daily closing price for 3 years. The time series method used is the model that will be used, namely the Autoregressive Integrated Moving Average (ARIMA)-Glosten Jagannathan Runkle - generalized autoregressive conditional heteroscedastic (GJR-GARCH) model. The stage of analysis is to determine the prediction of stock price movements using the ARIMA Model used for the mean model and the GJR-GARCH model is used for volatility models. The average value and variants obtained from the model are used to calculate value-at-risk in BBNI shares. The results obtained are the ARIMA(1,0,1)-GJR-GARCH(1.1) model and a significance level of 5% obtained value-at-risk of 0.0705.
Inventory Control of Vaccine Products in Pharmaceutical Company Using The Economic Order Quantity Model and Monte Carlo Simulation Rahmadini, Nurhaliza; Supian, Sudradjat; Napitupulu, Herlina
International Journal of Global Operations Research Vol. 4 No. 4 (2023): International Journal of Global Operations Research (IJGOR), Nopember 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i4.257

Abstract

Health is a basic need in human life. People spend a lot of money to maintain their health. One of the preventive health service options is to vaccinate. Indonesia is a country that can produce its own vaccines with its local pharmaceutical companies. The company faces stiff competition in today's rapidly growing market. Therefore, evaluation and assessment are needed to measure the progress of the company's development. One useful assessment is a company's financial review. Inventory control ensures that the planned approach can minimize costs without disrupting the production process. This research simulates data of demand and analyzes the inventory control based on simulated data. The object used in this research is the inventory of products of pharmaceutical companies. The data used is secondary data such as data of product quantity sold per period, purchasing cost, order cost, holding cost, shortage cost, and lead time. The method used for inventory control is Economic Order Quantity (EOQ) model and Monte Carlo simulation. The simulation results on the monthly demand for vaccine products show that the total demand for one year is 3.394.805 vials for Vaccine A, 1.320.900 vials for Vaccine B and 107.345 for Vaccine C. Based on simulated data processing, calculations using the probabilistic EOQ model result in total inventory costs of Rp.456.918.008.386,14 for Vaccine A, Rp 218.292.795.949,34 for Vaccine B, and Rp. 9.177.930.319,05 for Vaccine C.
Application of Black Scholes Method to Determining Premium Insurance In the Potato Agricultural Based on Price Index Sutisna, Sarah; Sukono, Sukono; Napitupulu, Herlina
International Journal of Global Operations Research Vol. 4 No. 4 (2023): International Journal of Global Operations Research (IJGOR), Nopember 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i4.258

Abstract

Potato is one of the leading horticultural commodities. Potato farming business often experiences price fluctuations that cause losses to farmers.The government is making efforts to minimize the farmers' losses by issuing agricultural insurance programs. This study aims to determine the relationship between potato prices at the provincial level and potato prices at the farmer level and to determine agricultural insurance premiums based on the price index. The data used are potato price data at the West Java Province level and potato price data at the farmer level in Pangalengan District. The correlation between provincial level prices and farmer level prices can be obtained using the Pearson Product Moment correlation method. The price index is calculated using the relative price index method. Determination of the premium to be paid by farmers using the Black-Scholes method. The results of the analysis show that potato prices at the West Java Province level have a very strong correlation with farmer prices in Pangalengan District in October. Based on the Black-Scholes method, the premium value depends on the trigger value obtained with a price range between IDR 9,806,100.00 to IDR 10,267,784.00 for a sum insured of IDR 39,403,000 per one contract period. Various premium values can be a consideration for farmers in choosing an agricultural insurance policy.
Inventory Control for Eyeglass Supply Using the P Model Based on Sales Products Sales Forecasting (Case Study: Merry Optic Bandung) Suripto, Adi; Nahar, Julita; Napitupulu, Herlina
International Journal of Global Operations Research Vol. 4 No. 4 (2023): International Journal of Global Operations Research (IJGOR), Nopember 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i4.255

Abstract

Inventory is a resource owned by the company to be used in the production process to meet consumer demand. Companies must be able to control inventory appropriately in order to avoid excess or shortage of inventory by using inventory control. Inventory control is a necessary part of a company that requires an appropriate inventory policy to meet uncertain needs. Based on this background, this study discusses the single item inventory model in the form of photochromic glasses at Merry Optik to find the optimal total inventory cost. In meeting the uncertain needs of the company, the Additive Decomposition forecasting method is used in order to find out the forecast sales data pattern in the future. Uncertain demand causes the inventory system to be probabilistic, so it is necessary to carry out probabilistic inventory control. The P model of the case of back orders was chosen because the range of ordering periods is fixed and the company can buy inventory when it runs out before the time the inventory order is made so that buyers can wait until the inventory arrives. By using Model P for the case of back orders, the company can obtain the period between orders, the total cost of inventory, and the optimal level of service. Based on the results of this study, a pattern of sales forecast data is obtained which repeats every 12 months. Companies must order glasses within a period of 32 days between orders so that it is optimal and able to provide a reduction in the total inventory cost of IDR 21,828,771 with a service level of 95%. Companies can save on inventory costs if they use shorter periods between orders. The total cost of inventory can be more optimal if the company reduces the cost of storing inventory in the warehouse.
Systematic Literature Review on Adjustable Robust Shortest Path Problem Fauziyah, Wida Nurul; Chaerani, Diah; Napitupulu, Herlina
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 4 (2023): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i4.17648

Abstract

In real-world optimization problems, effective path planning is important. The Shortest Path Problem (SPP) model is a classical operations research that can be applied to determine an efficient path from the starting point to the end point in a plan. However, in the real world, uncertainty is often encountered and must be faced. Significant uncertainty factors in the problem of determining the shortest path are problems that are difficult to predict, therefore new criteria and appropriate models are needed to deal with uncertainty along with the required efficient solution. The uncertainty factor can be formulated using an uncertain SPP optimization model, assuming parameters that are not known with certainty but are in an uncertain set. Problems with uncertainty in mathematical optimization can be solved using Robust Optimization (RO). RO is a methodology in dealing with the problem of data uncertainty caused by errors in data measurement. The uncertainty in the linear optimization problem model can be formed by loading the uncertainty that only exists in the constraint function by assuming its uncertainty using the Robust Counterpart (RC) methodology. In this paper, we will review the literature on the two-stage optimization model for the SPP problem using an Adjustable Robust Counterpart (ARC).
Optimalization Route to Tourism Places in West Java Using A-STAR Algorithm Yudha, Muhammad Helambang Prakasa; Supian, Sudrajat; Napitupulu, Herlina
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i3.17032

Abstract

Various algorithms can be used in the problem of finding the optimal route, one of which is the A-STAR Algorithm. The characteristic for recording routes that have been evaluated is one of the advantages of the A-STAR Algorithm. This study focuses on finding the optimal route to tourism places in West Java Province. In the application of the A-STAR Algorithm, distance data and density data are used from each line segment in West Java Province. The heuristic values used are converted from density data. The A-STAR algorithm is implemented using Python so that the optimal route to tourism places in West Java Province is obtained.
Optimal Control of Vaccination and Treatment of Varicella Disease (Chicken Pox) Aisyah, Ranti Rivani; Firdaus, Hamidah 'Alina; Napitupulu, Herlina; Anggriani, Nursanti
Jurnal Matematika Integratif Vol 20, No 2: Oktober 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n2.56410.197-208

Abstract

Varicella, or chickenpox, is an infectious disease that can affect anyone, especially children under the age of 10. Vaccination and medication are key measures in reducing the number of infections and the risk of Varicella infection. A mathematical SEITR model has been developed to describe this disease mathematically. Stability of the equilibrium points and the basic reproduction number of the developed model were then determined. Control was also applied to vaccination and medication with the aim of minimizing the infected population and the costs of vaccination and treatment. These control measures were incorporated into the SEITR model. Finally, Pontryagin’s Maximum Principle was used in the optimization process. This optimal control process significantly reduced the number of infected individuals, thereby effectively controlling the spread of Varicella.
PERAMALAN INDEKS ULTRAVIOLET DI KOTA BANDUNG MENGGUNAKAN METODE LONG SHORT-TERM MEMORY Satyaputra, Ida Bagus Wira Krishna; Napitupulu, Herlina; Gusriani, Nurul
Jurnal Matematika Integratif Vol 20, No 2: Oktober 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n2.58798.249-258

Abstract

Peramalan nilai indeks Ultraviolet (UV) memainkan peran penting dalam menjaga kesehatan masyarakat dan pengelolaan lingkungan. Penelitian ini bertujuan untuk menghasilkan nilai peramalan indeks UV di Kota Bandung pada tanggal 1–30 April 2024 menggunakan Metode Long Short-Term Memory (LSTM). Metode LSTM merupakan pengembangan dari metode Recurrent Neural Network (RNN). RNN diubah dengan menambahkan mekanisme gate untuk menyimpan informasi jangka panjang sehingga mengurangi resiko munculnya exploding gradients dan vanishing gradients. Model LSTM dalam penelitian ini dibangun menggunakan 1 input layer dengan 400 unit cell dan 1 output dense layer dengan fungsi update bobot adam optimizer, randomizer bobot glorot uniform distribution, dan 400 jumlah epoch. Performa model peramalan diuji menggunakan RMSE dan MAPE. Pada data training menghasilkan nilai RMSE sebesar 0,28 dan MAPE sebesar 11%. Untuk data testing menghasilkan nilai RMSE sebesar 0,48 dan MAPE sebesar 14%. Hasil peramalan indeks UV di Kota Bandung menunjukkan bahwa selama bulan April nilai rata-rata indeks UV adalah 2,27, hal ini mengartikan bahwa masyarakat Kota Bandung dapat beraktivitas diluar tanpa perlu mengkhawatirkan bahaya sinar UV.
Co-Authors Adi Suripto, Adi Agus Santoso Aisyah, Ranti Rivani Albert Raja Harungguan Alit Kartiwa Alit Kartiwa Ariesandy, Sena Asep K. Supriatna Betty Subartini Diah Chaerani Dwi Purnomo Dwi Susanti Edi Kurniadi Edi Kurniadi Edi Kurniadi Ema Carnia Eman Lesmana Erwin Harahap Ewen Hokijuliandy Fauziyah, Wida Nurul Febrianty, Popy Firdaniza Firdaniza Firdaus, Hamidah 'Alina Ghazali, Puspa Liza Hadiana, Asep Id Helma Syifa Izzadiana Hidayana, Rizki Apriva Ida Widianingsih Ira Sumiati Ismail Bin Mohd Jeane R. M. D. P Chantique Julita Nahar, Julita Kusumaningtyas, Valentina Adimurti Melina Melina Melina Melina, Melina Michael Lim Michelle Selina Buntara Muhammad Deni Johansyah Muhammad Helambang Prakasa Yudha Muhammad Ribhan Hadiyan Nabilla, Ulya Norizan Mohamed Novitasari, Ela Nursanti Anggriani Nurul Gusriani Nurul Gusriani, Nurul Rahmadini, Nurhaliza Rayyan Al Muddatstsir Fasa Riaman Riaman Ridwan Pandiya Saprilian Hidayat Saputra, Jumadil Satyaputra, Ida Bagus Wira Krishna Siti Aizal Yasni Ellena Sudrajat Supian Sukono . Supian, Sudradjat Supian, Sudrajat Sutisna, Sarah Valentina Adimurti Kusumaningtyas Valerie ​Valerie Valerie ​Valerie Viona Prisyella Balqis Viona Prisyella Balqis Wida Nurul Fauziyah Yosza Dasril Yudha, Muhammad Helambang Prakasa Yulison Herry Chrisnanto Yuyun Hidayat