Bandung Conference Series: Mathematics最新文献

{"title":"Penggunaan Rstudio dalam Pembuatan Aplikasi Peramalan Harga Emas dengan Metode Double Exponential Smooting Holt","authors":"Firdy Adi, Didi Suhaedi, Eti Kurniati","doi":"10.29313/bcsm.v3i2.9523","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.9523","url":null,"abstract":"Abstrak. Peramalan harga beli emas memiliki peranan penting dalam pengambilan keputusan investasi dan perencanaan keuangan.  Pada penelitian kali ini dilakukan perhitungan secara manual dan perhitungan menggunakan aplikasi dengan menggunakan Double Exponential Smooting dari Holt. Dalam pembangunan aplikasi digunakan RStudio sebagai alat pengembang dan bahasa R sebagai bahasa pemprogramannya. Dalam proses peramalan dilakukan terlebih dahulu pengumpulan data dari web Harga Emas Orang (harga-emas.org) dan didapat data berupa harga beli emas dan tanggal berupa format csv dengan rentan waktu 1 tahun dari 1 Mei 2022 sampai 31 April 2023 dengan data yang akan diolah unuk diteliti berjumlah 357 data harian. Setelah didapat data maka dilakukan pengujian terhadap data untuk mengetahui model yang cocok untuk digunakan dalam peramalan harga beli emas. Setelah dilakukan plot data emas dengan rentang waktu selama 1 tahun didapat bahwa  grafik plot emas menunjukkan adanya tren naik meskipun  dalam peningkatannya secara bertahap. Kemudian dilakukan peramalan menggunakan metode Double Exponential Smooting dari Holt karena syarat menggunakan metode Double Exponential Smooting dari Holt data harus menunjukkan adanya tren baik itu tren naik atau turun. Dan didapat nilai ramalan selamat 10 periode kedepan dengan tingkat MAPE (Mean Absolute Percentage Error) yang baik. \u0000Abstract. Forecasting the purchase price of gold has an important role in making investment decisions and financial planning. In this study, manual calculations were carried out and calculations using an application using Holt's Double Exponential Smoothing. In developing applications, RStudio is used as a developer tool and the R language as the programming language. In the Forecasting process, data is first collected from the People's Gold Price web (harga-emas.org) and data is obtained in the form of gold purchase prices and dates in the form of csv format with a timeframe of 1 year from 1 May 2022 to 31 April 2023 with data to be processed to be studied amounted to 357 daily data. After obtaining the data, a test is carried out on the data to find out which model is suitable for use in Forecasting the purchase price of gold. After plotting the gold data with a time span of 1 year, it was found that the gold plot graph shows an upward trend even though the increase is gradual. Then Forecasting is carried out using the Double Exponential Smoothing method from Holt because the conditions for using the Double Exponential Smoothing method from Holt are that the data must show a trend, whether it is an uptrend or a downtrend. And obtained Forecast value for the next 10 periods with a good level of MAPE (Mean Absolute Percentage Error).","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Panjang Populasi dan Banyak Generasi Algoritma Genetika pada Traveling Salesman Problem","authors":"Muhammad Iqbal Mubarok, Icih Sukarsih, Yurika Permanasari","doi":"10.29313/bcsm.v3i2.9467","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.9467","url":null,"abstract":"Abstrak. Traveling Salesman Problem (TSP) adalah masalah optimasi yang penting dalam bidang ilmu komputer dan matematika. Tujuan utama dari TSP adalah mencari rute terpendek yang melibatkan kunjungan ke sejumlah titik atau kota tertentu oleh seorang salesman. Algoritma Genetika (AG) telah menjadi salah satu pendekatan populer dalam menyelesaikan Traveling Salesman Problem karena kemampuannya untuk menghasilkan solusi yang mendekati optimum. Pada penelitian ini, dilakukan analisis mengenai panjang populasi dan banyak generasi pada Algoritma Genetika dalam menyelesaikan Traveling Salesman Problem. Tujuan penelitian ini adalah untuk menganalisis pengaruh kedua parameter tersebut terhadap kinerja Algoritma Genetika dalam mencapai solusi yang mendekati optimal. Digunakan studi kasus pendistribusian suatu produk UMKM (Usaha Mikro Kecil dan Menengah) di Bandung. Evaluasi dilakukan berdasarkan panjang rute terpendek yang ditemukan oleh Algoritma Genetika dalam jumlah iterasi tertentu. Hasil eksperimen menunjukkan bahwa dengan peningkatan panjang populasi pada Algoritma Genetika dapat meningkatkan kemampuan algoritma untuk menemukan solusi yang lebih baik. Dengan jumlah individu dalam populasi yang lebih besar, algoritma memiliki lebih banyak kesempatan untuk menjelajahi ruang solusi dan menemukan rute terpendek yang memenuhi kriteria Traveling Salesman Problem. \u0000Abstract. The Traveling Salesman Problem (TSP) is an important optimization problem in the fields of computer science and mathematics. Its main objective is to find the shortest route that involves visiting a specific set of points or cities by a salesman. Genetic Algorithms (GA) have become a popular approach in solving the Traveling Salesman Problem due to their ability to generate solutions that approximate optimality. In this study, an analysis was conducted on the population size and number of generations in the Genetic Algorithm for solving the Traveling Salesman Problem. The aim of this research was to analyze the influence of these two parameters on the performance of the genetic algorithm in achieving near-optimal solutions. A case study was conducted on the distribution of a small and medium-sized enterprise (SME) product in Bandung. The evaluation was based on the shortest route length discovered by the the Genetic Algorithms within a specified number of iterations. The experimental results indicated that increasing the population size in the Genetic Algorithms can enhance the algorithm's ability to find better solutions. With a larger number of individuals in the population, the algorithm had more opportunities to explore the solution space and discover the shortest routes that met the the Traveling Salesman Problem criteria.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129608947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Penyelesaian Masalah Multiple Criteria Decision Making dalam Pemilihan Supplier Obat Menggunakan Metode WASPAS","authors":"Annisa Melinia Rahayu, Didi Suhaedi, Yurika Permanasari","doi":"10.29313/bcsm.v3i2.8778","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8778","url":null,"abstract":"Abstrak. Penilaian supplier dengan pemantauan langsung yang dilakukan apotek untuk memilih supplier obat. Hal ini mempengaruhi pengambilan keputusan yang tidak efektif dan terlalu subjektif. Metode Multiple Criteria Decision Making (MCDM) digunakan untuk menentukan supplier obat terbaik berdasarkan beberapa kriteria yang telah ditentukan dan dianggap mempengaruhi pemilihan supplier terbaik bagi apotek yang bersangkutan. Dalam penelitian ini, metode Weighted Aggregated Sum Product (WASPAS) diterapkan untuk memilih supplier obat terbaik di apotek. Metode WASPAS dipilih karena kemampuannya dalam menangani banyak kriteria dan mempertimbangkan preferensi pembuat keputusan.  Terdapat 32 alternatif supplier yang dinilai berdasarkan kriteria harga, waktu pengiriman, penawaran program, dan pelayanan. Dari hasil perangkingan, terdapat 5 supplier obat teratas yang dipilih yaitu supplier Ae, supplier V, supplier T, supplier M, dan supplier F. Perangkingan tersebut diurutkan dari nilai akhir tertinggi, yaitu 2,4131 untuk supplier Ae, hingga nilai akhir terendah, yaitu 1,7395 untuk supplier Q. Dengan demikian, metode WASPAS dapat digunakan sebagai alat bantu pengambilan keputusan dalam memilih supplier obat terbaik. \u0000Abstract. The evaluation of suppliers with direct monitoring conducted by pharmacies to select drug suppliers affects ineffective and overly subjective decision-making. The Multiple Criteria Decision Making (MCDM) method is used to determine the best drug supplier based on several predefined criteria considered to influence the selection of the best supplier for the respective pharmacy. In this research, the Weighted Aggregated Sum Product (WASPAS) method is implemented to select the best drug supplier in the pharmacy. WASPAS method was chosen due to its ability to handle multiple criteria and consider decision-makers' preferences. There are 32 alternative suppliers evaluated based on criteria such as price, delivery time, program offerings, and services. From the ranking results, the top 5 drug suppliers selected are supplier Ae, supplier V, supplier T, supplier M, and supplier F. These rankings are arranged from the highest final score, 2.3141 for supplier Ae, to the lowest final score, 1.7395 for supplier Q. Therefore, the WASPAS method can be used as a decision-making tool in selecting the best drug supplier.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128311217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Metode Certainty Factor dan Teorema Bayes sebagai Sistem Pendukung Keputusan Diagnosis Penyakit Limfoma","authors":"Audina Tri Hardiyani, E. Harahap, Didi Suhaedi","doi":"10.29313/bcsm.v3i2.7870","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.7870","url":null,"abstract":"Abstrak. Limfoma adalah istilah umum untuk berbagai jenis kanker darah yang timbul karena berada dalam sistem limfatik yang menyebabkan pembesaran kelenjar getah bening. Limfoma disebabkan oleh sel limfosit B atau T, yaitu sel darah putih dalam keadaan normal untuk menjaga daya tahan tubuh dan menangkal infeksi bakteri menjadi abnormal dengan membelah lebih cepat dari sel biasa. Limfoma dibagi menjadi 2 jenis, yaitu limfoma Hodgkin (LH) dan limfoma non-Hodgkin (LNH). Penerapan sistem pakar merupakan faktor ketidakpastian, untuk meminimalisir tingkat ketidakpastian seorang ahli menggunakan metode Certainty Factor (CF) dan Teorema Bayes (TB) untuk menggambarkan keyakinan seorang ahli. Penelitian bertujuan untuk mengetahui hasil perbandingan metode mana yang akan menghasilkan nilai validasi tertinggi. Berdasarkan hasil penelitian yang telah dilakukan, metode CF memiliki nilai persentase tertinggi dibandingkan TB dengan menyajikan nilai yang diperoleh dari metode LH CF sebesar 98% merupakan kemungkinan yang besar, sedangkan hasil persentase nilai LH TB sebesar 56% kecil kemungkinannya. \u0000Abstract. Lymphoma is a general term for various types of blood cancers that arise because they are in the lymphatic system that causes enlargement of the lymph nodes. Lymphoma is caused by B or T lymphocyte cells, which are white blood cells under normal circumstances to maintain the body's resistance and ward off bacterial infections to become abnormal by dividing faster than ordinary cells. Lymphoma is divided into 2 types, namely Hodgkin lymphoma (LH) and non-Hodgkin lymphoma (LNH). The implementation of the expert system is an uncertainty factor, to minimize the level of uncertainty an expert uses the Certainty Factor (CF) method and Bayes' Theorem (TB) to describe the beliefs of an expert. The study aims to find out the results of the comparison of which method will produce the highest validation value. Based on the results of research that has been carried out, the CF method has the highest percentage value compared to TB by presenting the average value obtained from the CF LH method of 98% is a large possibility, while the percentage result of the average value of LH TB of 56% is a little likely.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129012387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimasi Laba Produksi Ayam Geprek Menggunakan Metode Simplek dengan Bantuan QM for Windows","authors":"Natasha Sabila Alfath, E. Harahap, M. Y. Fajar","doi":"10.29313/bcsm.v3i2.9153","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.9153","url":null,"abstract":"Abstrak. Optimalisasi keuntungan dapat diterapkan melalui beberapa metode, salah satunya yaitu program linear. Program linear dpat digunakan untuk mengoptimalkan keuntungan pada suatu perusahaan, baik perusahaan besar maupun kecil atau UMKM. UMKM Ayam Geprek Waika yang berada di kawasan Sarijadi, Kota Bandung menjadi salah satu UMKM yang memiliki permasalahan yang sering dihadapi oleh UMKM yaitu bagaimana mengkombinasikan faktor-faktor produksi yang dimiliki dengan tepat agar dapat menghasilkan keuntungan yang maksimal. Maka penelitian ini bertujuan untuk menentukan keuntungan maksimal yang dapat diperoleh pada usaha Ayam Geprek Waika menggunakan Pemrograman Linier metode Simpleks. Jenis penelitian ini  adalah jenis studi kasus menggunakan penelitian yang bersifat kuantitatif dengan menentukan variabel-variabel yang akan diteliti. Jenis data yang digunakan pada penelitian ini yaitu data primer melalui observasi langsung dan wawancara dengan narasumber pengusaha Ayam Geprek Waika. Selanjutnya data tersebut akan dianalisis menggunakan Linear Programming metode simpleks berbantuan  Software QM for Windows yang bertujuan untuk mencari solusi optimal. Hasil dari analisis penelitian bahwa untuk memperoleh keuntungan yang optimal maka UMKM Ayam Geprek Waika harus memproduksi setiap jenis ayam sebanyak 1.300 potong ayam dengan keuntungan yang akan diperoleh adalah sebesar Rp 11.050.000 dalam periode satu bulan. Kenaikan keuntungan yang diperoleh oleh UMKM Ayam Geprek Waika adalah 12,29% dari kondisi faktual ke kondisi optimal yaitu sebesar Rp 1.210.000. \u0000Abstract. Optimization of profits can be applied through several methods, one of which is a linear program. Linear programs can be used to optimize profits in a company, both large and small companies or MSMEs. Ayam Geprek Waika MSME located in the Sarijadi area, Bandung City, is one of the MSMEs that has problems that are often faced by MSMEs, namely how to combine the factors of production owned appropriately in order to generate maximum profits. So this study aims to determine the maximum profit that can be obtained at Ayam Geprek Waika business using Linear Programming Simplex method. This type of research is a type of case study using quantitative research by determining the variables to be studied. The type of data used in this study is primary data through direct observation and interviews with Waika Geprek Chicken entrepreneurs. Furthermore, the data will be analyzed using Linear Programming simplex method assisted by QM for Windows Software which aims to find the optimal solution. The results of the research analysis that to obtain optimal profits, MSMEs Ayam Geprek Waika must produce each type of chicken as many as 1,300 pieces of chicken with the profit to be obtained is Rp 11,050,000 in a one-month period. The increase in profits obtained by UMKM Ayam Geprek Waika is 12.29% from the previous month.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126077060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aplikasi Power BI pada Perhitungan Iuran Normal dan Kewajiban Aktuaria Menggunakan Metode Accrued Benefit","authors":"Thalia Yasmine Puspitasari, Onoy Rohaeni, E. Harahap","doi":"10.29313/bcsm.v3i2.9211","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.9211","url":null,"abstract":"Abstrak. Program Dana Pensiun merupakan salah satu aspek penting dalam pengelolaan sumber daya manusia suatu perusahaan atau lembaga. Pengelolaan program dana pensiun yang efektif adalah kunci untuk memastikan keamanan dan kestabilan keuangan bagi para pensiunan di masa depan. Pada penelitian, peneliti melakukan perhitungan program dana pensiun menggunakan metode Accrued Benefit yang merupakan salah satu pendekatan yang umum digunakan dalam menghitung manfaat pensiun berdasarkan masa kerja dan gaji karyawan. Metode Accrued Benefit mengacu pada perhitungan manfaat pensiun berdasarkan akumulasi kontribusi dan keuntungan yang diperoleh selama masa kerja karyawan. Analisis ini bertujuan untuk mengidentifikasi potensi perubahan program dana pensiun, mengevaluasi kinerja dan stabilitas program yang ada, serta menyusun strategi pengelolaan yang lebih optimal untuk kepentingan karyawan dan perusahaan. Untuk aplikasi data program dana pensiun, Peneliti menggunakan aplikasi Power BI, yang merupakan alat bisnis inteligensia yang populer untuk memvisualisasikan dan menganalisis data secara interaktif. Power BI memungkinkan peneliti untuk menggali wawasan dari data pensiun yang kompleks dan mempresentasikan hasil analisis secara intuitif melalui dashboard yang dinamis. Hasil dari analisis ini diharapkan dapat memberikan wawasan dalam meningkatkan keberlanjutan dan efisiensi program dana pensiun. Selain itu, aplikasi Power BI yang digunakan dapat menjadi referensi bagi perusahaan lain yang ingin meningkatkan pengelolaan program dana pensiun mereka dengan pendekatan yang lebih modern. \u0000Abstract. Pension fund program is one aspect important in management source Power man something company or institution. Effective management of pension fund programs is key For ensure security and stability finance for future retirees In research, researchers do pension plan calculations use method Accrued Benefit which is one common approach used in count benefit pension based on length of service and salary employee. Method Accrued Benefits refers to calculations benefit pension based on accumulation contributions and profits earned during working time employee. Analysis This aim for identify potency changes to the pension fund program, evaluate performance and stability of existing programs, as well develop a more optimal management strategy for interest employees and companies. For pension fund program data application, Researcher use application Power BI, which is a tool business popular intelligence for visualize and analyze data interactive. Power BI makes it possible researcher for dig outlook of complex pension data and present results analysis in a manner intuitive via a dynamic dashboard. Result of analysis This expected can give outlook in increase sustainability and efficiency of pension fund programs. Besides that is, the Power BI application used can become reference for other companies that want increase pension fund management they with a more modern approach.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131518827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementasi Sistem Pendukung Keputusan Pemilihan Menu Makanan Terbaik untuk Penderita Gastroesophageal Reflux Disease (Gerd) dengan Menggunakan Metode Topsis","authors":"Devie Ratna Mutia, Erwin Harahap, Didi Suhaedi","doi":"10.29313/bcsm.v3i2.8562","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8562","url":null,"abstract":"Abstrak. Sistem pendukung keputusan (SPK) merupakan penerapan sistem informasi yang dirancang untuk membantu pengguna dalam mengambil keputusan dengan menggunakan model matematis. Dalam SPK terdapat metode Multiple Criteria Decision Making (MCDM), suatu metode digunakan untuk pengambilan keputusan dalam situasi di mana beberapa kriteria yang dipertimbangkan dalam waktu bersamaan. MCDM memiliki beberapa metode yang sudah banyak dikembangkan, salah satunya metode Topsis. Penelitian ini dilakukan untuk memanfaatkan SPK pada pemilihan menu makanan terbaik dengan metode Topsis, untuk membantu penderita Gastroesophageal Reflux Disease (GERD). Menu makanan sangat penting ditentukan untuk penderita GERD, salah satunya dalam kandungan gizi yang terdapat pada makanan. Kandungan lemak, asam, gas, dan kafein yang berlebihan merupakan kandungan yang dapat memicu terjadinya GERD. Sehingga dapat diperoleh menu makanan setiap kelompok dari hasil nilai preferensi dan pemeringkatan, kelompok menu makanan pokok peringkat tertinggi yaitu Nasi Merah dan peringkat terendah Nasi Pecel, kelompok menu sayuran peringkat tertinggi Tumis Tauge dan peringkat terendah Gudeg. Kelompok menu lauk pauk peringkat tertinggi Ikan Panggang dan peringkat terendah Rawon, kelompok menu dessert peringkat tertinggi Jasuke dan peringkat terendah Brownies. Kelompok menu minuman peringkat tertinggi Jus Melon dan peringkat terendah Teh Botol. Jika dilihat dari kriteria, nilai preferensi dan hasil pemeringkatan tertinggi memiliki nilai kandungan lemak, asam, gas, dan kafein yang sangat rendah. \u0000Abstract. Decision support systems (DSS) are the implementation of information systems designed to assist users in making decisions using mathematical models. In SPK there is the Multiple Criteria Decision Making (MCDM) method, a method used for decision making in situations where several criteria are considered at the same time. MCDM has several methods that have been developed, one of which is the Topsis method. This research was conducted to utilize DSS in choosing the best food menu using the Topsis method, to help sufferers of Gastroesophageal Reflux Disease (GERD). The food menu is very important to determine for GERD sufferers, one of which is the nutritional content found in food. Excessive fat, acid, gas and caffeine content are ingredients that can trigger GERD. So that the food menu for each group can be obtained from the preference value and ranking results, the staple food menu group with the highest rank is Red Rice and the lowest rank is Nasi Pecel, the vegetable menu group has the highest rank Tumis Bean Sprouts and the lowest rank is Gudeg. The side dish menu group has the highest rank Grilled Fish and Rawon the lowest rank, Dessert menu group has the highest rank Jasuke and Brownies the lowest rank. The drink menu group has the highest rating Melon Juice and the lowest rating is Botol Tea. When viewed from the criteria, the preference value and the highest rating results have very low ","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129994147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Metode Mean-Semivariance dan Mean Absolute Deviation Untuk Menentukan Portfolio Optimal Menggunakan Python","authors":"Bilqis Khairun Nisa, Onoy Rohaeni, Erwin Harahap","doi":"10.29313/bcsm.v3i2.8549","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8549","url":null,"abstract":"Abstrak. Investasi merupakan kegiatan menanamkan modal dengan tujuan mendapatkan keuntungan. Salah satu investasi pada aset keuangan yaitu investasi saham. Saham merupakan investasi yang berisiko tinggi karena harga saham yang fluktuatif. Untuk menghindari risiko yang akan mempengaruhi return saat berinvestasi, maka perlu membentuk portofolio optimal. Portofolio optimal merupakan portofolio yang memberikan return maksimum dan memiliki risiko minimum. Pada penelitian ini dibahas mengenai pembentukan portofolio optimal dengan menggunakan metode Mean Semivariance dan Mean Absolute Deviation. Dari hasil perhitungan pada penelitian ini metode Mean Semivariance memperoleh return sebesar 0.0035% dan risiko sebesar 0.080518%. Sedangkan dengan menggunakan metode Mean Absolute Deviation diperoleh return sebesar 0.000273% dan risiko sebesar 0.022276%. \u0000Abstract. Investment is an investment activity with the aim of making a profit. One of the investments in financial assets is stock investment. Stocks are a high-risk investment because stock prices fluctuate. To avoid risks that will affect returns when investing, it is necessary to form an optimal portfolio. Optimal portfolio is a portfolio that provides maximum return and has minimum risk. This study discusses the formation of an optimal portfolio using the Mean Semivariance and Mean Absolute Deviation methods. From the calculation results in this study the Mean Semivariance method obtained a return of 0.0035% and a risk of 0.080518%. Meanwhile, using the Mean Absolute Deviation method, a return of 0.000273% and a risk of 0.022276% are obtained.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115299816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Path Analysis dan Penerapannya pada Bantuan Sosial","authors":"Sri Imas Nur Azizah, Y. Ramdani, Gani Gunawan","doi":"10.29313/bcsm.v3i2.8918","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8918","url":null,"abstract":"Abstrak. Path Analysis ialah sebuah teknik untuk menganalisis hubungan sebab akibat yang merupakan pengembangan dari analisis regresi linear berganda, jika variabel independent exogenous nya mempengaruhi variabel dependent endogenous tidak hanya secara langsung tetapi juga secara tidak langsung. Seperti halnya analisis regresi, Path Analysis atau Analisis Jalur dapat digunakan untuk melihat dan menentukan variabel apa saja atau jalur mana saja yang dihipotesiskan memiliki unit satuan yang berbeda-beda sehingga perlu dilakukan standardisasi untuk menjadikan semua unit satuan dari variabel yang akan hilang dan skala tiap variabel akan seragam. Penelitian ini dilakukan untuk mengetahui pengaruh sebab akibat pada data penerimaan bantuan sosial. Selama ini tingkat pendidikan pada keluarga miskin dipengaruhi oleh faktor ekonomi yang dibantu pemerintah daerah dengan adanya bantuan sosial. Data yang digunakan merupakan data bantuan sosial dari salah satu bantuan sosial yaitu bantuan PKH pada komponen pendidikan. Berdasarkan hasil Path Analysis dengan SPSS, didapat terdapat pengaruh langsung antara penerima bantuan tingkat SD terhadap penerima tingkat SMP sebesar 0,000 < 0,05, terdapat pengaruh langsung antara penerima bantuan tingkat SMP terhadap penerima tingkat SMA sebesar 0,000 < 0,05, terdapat pengaruh langsung antara penerima bantuan tingkat SMA terhadap Jumlah penerima bantuan sosial sebesar 0,000 < 0,05, terdapat pengaruh langsung antara penerima bantuan tingkat SMP terhadap Jumlah penerima bantuan sosial sebesar 0,000 < 0,05, terdapat pengaruh langsung antara penerima bantuan tingkat SD terhadap Jumlah penerima sebesar 0,000 < 0,05, terdapat pengaruh secara simultan antara tingkat SD, SMP dan SMA terhadap Jumlah Penerima Bantuan sebesar 81,5% dan sisanya sebesar 18,5% dipengaruhi oleh variabel lain yang tidak diteliti. \u0000Abstract. Path analysis is a technique for analyzing causal relationships which is a development of multiple linear regression analysis, if the exogenous independent variable affects the endogenous dependent variable not only directly but also indirectly. As with regression analysis, Path Analysis or Path Analysis can be used to see and determine which variables or which paths are hypothesized to have different units, so standardization is necessary to make all units of variables disappear and the scale of each variable will be uniform. This research was conducted to determine the causal effect on social assistance receipt data. So far, the level of education in poor families is influenced by economic factors assisted by the local government with social assistance. The data used is social assistance data from one of the social assistance programs, namely PKH assistance in the education component. Based on the results of Path Analysis with SPSS, it was found that there was a direct effect between elementary school beneficiaries and junior high school beneficiaries of 0.000 <0.05, there was a direct effect between junior high school","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115816366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Penerapan Metode Mixed Autoregressive and Moving Average Untuk Peramalan Harga Saham LQ45","authors":"Gita Sarah Prabawati, Onoy Rohaeni, Eti Kurniati","doi":"10.29313/bcsm.v3i2.8535","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8535","url":null,"abstract":"Abstrak. Saham merupakan investasi yang nilainya sangat fluktuatif. Kondisi seperti ini menyebabkan investor berhadapan dengan risiko. Risiko dapat berkurang apabila investor bisa membuat prediksi dengan ketelitian yang baik. Tujuan penelitian ini adalah untuk mendapatkan model dan dapat meramalkan harga saham beberapa waktu kedepan. Metode peramalan yang akan digunakan dalam penelitian ini adalah Mixed Autoregressive and Moving Average yaitu gabungan antara model Autoregresif dan Moving Average (ARMA). Penelitian ini menggunakan penutupan harga saham LQ45 periode 1 Maret 2022 hingga 28 April 2023. Hasil yang diperoleh adalah model terbaik yaitu ARMA (1,1). Model layak digunakan karena diperoleh nilai MAPE dengan kategori sangat baik. \u0000Abstract. Stock is an investment whose value is very volatile. Conditions like this cause investors to face risks. Risk can be reduced if investors can make predictions with good accuracy. The purpose of this research is to get a model and be able to predict stock prices some time in the future. The forecasting method that will be used in this study is the Mixed Autoregressive and Moving Average, which is a combination of the Autoregressive and Moving Average (ARMA) models. This study uses the closing price of LQ45 shares for the period March 1, 2022 to April 28, 2023. The results obtained are the best model, namely ARMA (1,1). The model is suitable for use because the MAPE value is obtained in a very good category.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117007361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}