Jurnal Riset Pendidikan Matematika最新文献

{"title":"Penerapan Metode MOOSRA pada Sistem Pendukung Keputusan Pemilihan E-commerce dalam Pembelian Produk Fashion","authors":"Elsa Fitria, Gani Gunawan","doi":"10.29313/jrm.v3i1.1745","DOIUrl":"https://doi.org/10.29313/jrm.v3i1.1745","url":null,"abstract":"Abstract. The growth of e-commerce in Indonesia continues to increase every year, especially with the pandemic accelerating e-commerce growth so that it is predicted to grow by 91%. Fashion products are a sector that is in great demand by e-commerce users in Indonesia. The many e-commerce platforms available today provide a variety of choices for consumers to buy fashion products according to the desired criteria. For this reason, a decision support system is needed to help the process of selecting e-commerce in the fashion sector with the right method. In this study, the selection of e-commerce in the fashion sector was carried out by applying the Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) method. The selection process uses 4 e-commerce alternatives, namely Shopee, Tokopedia, Lazada, and TikTok Shop, and the 5 criteria used are price, product, transaction process, service, and attractiveness. In this study the Entropy method was used to determine the weight of the criteria. The results showed that Shopee was an alternative choice for e-commerce in the fashion sector in the case study of active Unisba students with the highest performance score of 2.11960, followed by TikTok Shop of 1.87437 then Tokopedia of 1.53236 and finally Lazada of 1. 48977. \u0000Abstrak. Pertumbuan e-commerce di Indonesia terus meningkat tiap tahunnya, terlebih dengan adanya pandemi mengakselerasi pertumbuhan e-commerce hingga diprediksi bertumbuh sebesar 91%. Produk fashion menjadi sektor yang banyak diminati oleh pengguna e-commerce di Indonesia. Banyaknya platform e-commerce yang tersedia saat ini memberi beragam pilihan bagi konsumen untuk membeli produk fashion sesuai dengan kriteria yang diinginkan. Untuk itu diperlukan sebuah sistem pendukung keputusan untuk membantu proses pemilihan e-commerce di bidang fashion dengan metode yang tepat. Pada penelitian ini dilakukan pemilihan terhadap e-commerce di bidang fashion dengan menerapkan metode Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA). Proses pemilihan menggunakan 4 alternatif e-commerce yaitu Shopee, Tokopedia, Lazada, dan TikTok Shop, serta 5 kriteria yang digunakan yaitu harga, produk, proses transaksi, pelayanan, dan daya Tarik. Dalam penelitian ini metode Entropy digunakan untuk menentukan bobot kriteria. Hasil penelitian menunjukkan bahwa Shopee menjadi pilihan alternatif e-commerce dalam bidang fashion pada studi kasus mahasiswa aktif Unisba dengan perolehan skor kinerja tertinggi yaitu sebesar 2,11960 disusul oleh TikTok Shop sebesar 1,87437 kemudian Tokopedia sebesar 1,53236 dan terakhir Lazada sebesar 1,48977.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"155 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79771737","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":"Prediksi Hasil FIFA World Cup Qatar 2022 Menggunakan Machine Learning dengan Python","authors":"Syahrul Zein, Gani Gunawan","doi":"10.29313/jrm.v2i2.1382","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1382","url":null,"abstract":"Abstract. Predicting the outcome of the match is a big thing when it’s always expressed before the game starts, both from fans and analysts. To predict a match, we need a technology that can process input, analysis and output data, namely Machine Learning. Machine Learning is a system or computer to 'learn' independently and improve its capabilities automatically without the need for explicit written programming instructions. several algorithms to predict an event, namely Logistic Regression, K-Nearest Neighbors, Naïve-Bayes, Support Vector Machine, Neural Network and Random Forest. In this study, with the help of Scikit-Learn on Python, it was used to measure the accuracy of the FIFA World Cup 2006-2018 and predicts the results of the FIFA World Cup 2022. The SVM algorithm has the highest accuracy rate in 2010 and 2014. This means that if the same two teams meet in 2010, if they meet again 4 years later, they will have the same chance of winning. The Neural Network algorithm has the highest accuracy rate in 2006 and 2018. This means that if the same two teams met in 2006, if they met again 12 years later, they would have the same chance of winning. Prediction results show that Germany has a chance to win the FIFA World Cup 2022. \u0000Abstrak. Memprediksi hasil pertandingan adalah hal yang besar ketika selalu diungkapkan sebelum pertandingan dimulai, baik dari penggemar maupun analis. Untuk memprediksi kecocokan, diperlukan suatu teknologi yang dapat mengolah data input, analisis dan output yaitu Machine Learning. Machine Learning adalah sebuah sistem atau komputer untuk 'belajar' secara mandiri dan meningkatkan kemampuannya secara otomatis tanpa memerlukan instruksi pemrograman tertulis yang eksplisit. beberapa algoritma untuk memprediksi suatu kejadian yaitu Logistic Regression, K-Nearest Neighbors, Naïve-Bayes, Support Vector Machine, Neural Network dan Random Forest. Dalam penelitian ini, dengan bantuan Scikit-Learn on Python digunakan untuk mengukur akurasi FIFA World Cup 2006-2018 dan memprediksi hasil FIFA World Cup 2022. Algoritma SVM memiliki tingkat akurasi tertinggi pada tahun 2010 dan 2014. Artinya, jika dua tim yang sama bertemu di tahun 2010, jika bertemu lagi 4 tahun kemudian, mereka akan memiliki peluang yang sama untuk menang. Algoritma Neural Network memiliki tingkat akurasi tertinggi pada tahun 2006 dan 2018. Artinya jika dua tim yang sama bertemu pada tahun 2006, jika mereka bertemu lagi 12 tahun kemudian, mereka akan memiliki peluang yang sama untuk menang. Hasil prediksi menunjukkan bahwa Jerman berpeluang menjadi juara FIFA World Cup 2022.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"154 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86276853","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":"Prediksi Jumlah Penumpang Pesawat dengan Backpropagation Neural Network","authors":"Desy Pitriyani, Yurika Permanasari","doi":"10.29313/jrm.v2i2.1327","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1327","url":null,"abstract":"Abstract. The surge in passengers at Soekarno-Hatta International Airport in new normal era, urged the airport to have information about how many passengers in the next several time periods in order to know the proper plan and optimization of airport operations. This paper aims to use Backpropagation Neural Network methods to predict the number of airplane passengers. The data used is monthly data on the number of passengers on domestic flights at Soekarno-Hatta International Airport from January 2006 to April 2022 obtained from Badan Pusat Statistik (BPS). The results showed predictions with Backpropagation Neural Network method produced the best predictions with 19.77% MAPE. The prediction of the number of passengers in the next period, May 2022 is 1.060.500 passengers. \u0000Abstrak. Melonjaknya penumpang di Bandara Internasional Soekarno-Hatta pada era new normal, pihak bandara perlu memiliki informasi mengenai berapa banyak penumpang pada beberapa periode waktu ke depan guna mengetahui perencanaan dan pengoptimalan pengoperasian bandara yang tepat. Penelitian ini bertujuan untuk memprediksi jumlah penumpang pesawat menggunakan Backpropagation Neural Network. Data yang digunakan adalah data bulanan jumlah penumpang pesawat penerbangan domestik di Bandara Internasional Soekarno-Hatta mulai Januari 2006 hingga April 2022 yang diperoleh dari Badan Pusat Statistika (BPS). Hasil penelitian menunjukkan prediksi dengan metode Backpropagation Neural Network menghasilkan prediksi yang baik dengan MAPE 19,77%. Prediksi jumlah penumpang pada periode selanjutnya yaitu Mei 2022 adalah sebanyak 1.060.500 penumpang.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90308133","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 MATLAB dalam Akad Mudharabah dan Musyarakah Menggunakan Metode Profit and Loss Sharing","authors":"Willy Ledi Widia, Onoy Rohaeni","doi":"10.29313/jrm.v2i2.1343","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1343","url":null,"abstract":"Abstract. Muslims in Indonesia want a sharia-based economic principle, this can be applied to every aspect and transaction carried out. In profit sharing activities there are 2 contracts that can be used in banking, namely Al-Mudharabah and Al-Musyarakah. This study aims to determine the implementation of the profit and loss sharing method for mudharabah and musyarakah contracts. In this study, the focus is the profit-sharing system between Islamic banks and customers. The implementation of this research was carried out using MATLAB (Matrix Laboratorary). The results of this study indicate that the amount of installments paid each month is influenced by the agreement made at the beginning of the contract. From the results of the implementation of the profit and loss sharing method, it is concluded that by using the mudharabah contract, the installment amount will be the same as the principal installment, while in the implementation of the musharaka contract, the installment amount will be obtained from the installment size plus the profit sharing loss. And with the help of the MATLAB program it can make it easier to calculate profit sharing and installments that must be paid every month. \u0000Abstrak. Umat Islam di Indonesia menginginkan adanya prinsip perekonomian dengan berbasis syariah, hal tersebut dapat diaplikasikan pada setiap aspek maupun transaksi yang dilakukan. Dalam kegiatan bagi hasil ada 2 akad yang dapat digunakan dalam perbankan yaitu Al-Mudharabah dan Al-Musyarakah. Penelitian ini bertujuan untuk mengetahui implementasi metode profit and loss sharing untuk akad mudharabah dan akad musyarakah. Dalam penelitian ini yang menjadi fokus adalah sistem bagi hasil antara bank syariah dengan nasabah. Implementasi penelitian ini dilakukan dengan menggunakan MATLAB (Matrix Laboratorary). Hasil penelitian ini menunjukan bahwa besarnya angsuran yang dibayarkan setiap bulannya dipengaruhi oleh kesepakatan yang dilakukan diawal akad. Dari hasil Implementasi metode profit and loss sharing disimpulkan bahwa dengan menggunakan akad mudharabah maka besar cicilan akan sama dengan angsuran pokok, sedangkan pada pelaksanaan akad musyarakah besar cicilan akan didapat dari besar angsuran ditambah dengan besar bagi hasil kerugian. Dan dengan bantuan program MATLAB dapat memudahkan untuk menghitung bagi hasil dan angsuran yang harus dibayarkan setiap bulannya.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81257185","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":"Ekstraksi Data Digital Menggunakan Teknik Max Pooling dan Average Pooling","authors":"Puspa Meliuwati, Eti Kurniati","doi":"10.29313/jrm.v2i2.1338","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1338","url":null,"abstract":"Abstract. Digital data processing requires algorithms that can process data optimally. Processing large amounts of data requires a large number of parameters to produce accurate output. Then the classification accuracy at a certain point will decrease, therefore a process is needed that can extract the required number of parameters, one of which is using the pooling process. Pooling is a selection process to reduce the resolution on an insignificant feature map. Two methods in pooling, namely max pooling and average pooling, work by dividing the layer into several small grids and then taking the largest value or average value of each grid to compose the reduced digital data matrix. The pooling process requires padding to adjust the filter matrix by filling the empty parts of the matrix with the number 0. The size of the filter matrix does not affect the size of the pooling matrix. The smaller the filter matrix size, the more detailed the pooling process will be. The displacement of the filter matrix in the data matrix is ​​determined by the magnitude of the stride. The smaller the stride size, the more detailed it will be, but the larger the pooling matrix will be. \u0000Abstrak. Pengolahan data digital membutuhkan algoritma yang dapat memproses data secara optimal. Pemrosesan data jumlah besar membutuhkan jumlah parameter yang besar pula untuk menghasilkan output yang akurat. Maka alkurasi klasifikasi pada titik tertentu akan menurun, oleh karena itu dibutuhkan sutu proses yang dapat mengekstraksi jumlah parameter yang diperlukan salah satunya menggunakan proses pooling. Pooling adalah proses melakukan seleksi untuk mengurangi resolusi pada peta ciri yang tidak signifikan. Dua metode dalam pooling yaitu max pooling dan average pooling, bekerja dengan membagi layer menjadi beberapa grid kecil lalu engambil nilai terbesar atau nilai rata-rata setiap grid untuk Menyusun matriks data digital yang telah direduksi. Proses pooling memerlukan padding untuk menyesuaikan matriks filter dengan mengisi bagian-bagian kosong matriks dengan angka 0. Ukuran matriks filter tidak mempengaruhi ukuran matriks pooling. semakin kecil ukuran matriks filter maka proses pooling akan semakin rinci. Perpindahan matriks filter pada matriks data ditentukan oleh besarnya stride. Semakin kecil ukuran stride akan semakin rinci akan tetapi ukuran matriks pooling akan semakin besar.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"129 9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79597163","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 Inference Fuzzy Mamdani dalam Seleksi Penerima Bantuan Sosial Tunai Kabupaten Belitung Timur","authors":"Sentya Agus Savitri, Didi Suhaedi","doi":"10.29313/jrm.v2i2.1383","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1383","url":null,"abstract":"Abstract. Cash Social Assistance is a form of government intervention through the Indonesian Ministry of Social Affairs in order to provide a social safety stimulus in the midst of the COVID-19 pandemic. However, in the process there are still obstacles, one of which is in determining the recipients of Cash Social Assistance. The use of the Mamdani Fuzzy Inference System is one method that can be used in the process of determining the recipients of Cash Social Assistance. In its use, Fuzzy Mamdani has four stages, starting from the stages of forming fuzzy sets, application of the Implication function, composition of rules to defuzzification or affirmation. Mamdani's Fuzzy Inference System describes the output in numerical form which determines the eligibility of Cash Social Assistance Recipients. In order to simplify the work, the calculation uses the Toolbox in Matlab. There are 10 fuzzy rules used. The result of the research is a feasibility determination system that has an accuracy value of 92.1835% and this determination system can be used as a reference in the process of determining the recipients of Cash Social Assistance. \u0000Abstrak. Bantuan Sosial Tunai merupakan bentuk perwujudan Intervensi Pemerintah melalui Kementrian Sosial RI dalam rangka memberikan stimulus Pengaman Sosial di tengah masa pandemik COVID-19. Akan tetapi dalam prosesnya masih terdapat kendala salah satunya dalam penentuan penerima Bantuan Sosial Tunai. Penggunaan Sistem Inference Fuzzy Mamdani merupakan salah satu metode yang bisa digunakan dalam proses penentuan penerima Bantuan Sosial Tunai. Dalam Penggunaannya Fuzzy Mamdani memiliki empat tahapan yang dilakukan, mulai dari tahapan pembentukan himpunan fuzzy, aplikasi fungsi Implikasi, komposisi aturan sampai defuzifikasi atau penegasan.Variabel yang digunakan adalah Status Pekerjaan Kepala Keluarga, Kondisi Lantai, Kondisi WC, Penghasilan, Dinding. Sistem Inference Fuzzy Mamdani menggambarkan keluaran (Output) dalam bentuk numerik yang menjadi penentu kelayakan Penerima Bantuan Sosial Tunai. Dalam mempermudah pengerjaan, perhitungannya menggunakan Toolbox pada Matlab. Fuzzy rules yang digunakan sebanyak 10 aturan. Hasil dari penelitian berupa sebuah sistem penentuan kelayakan yang memiliki nilai akurasi sebesar 92,1835 % dan sistem penentuan ini dapat dijadikan acuan dalam proses penentuan penerima Bantuan Sosial Tunai.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"2023 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86864363","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 Efek Pergeseran Kurva Penawaran terhadap Keseimbangan Pasar dalam Shortrun pada Pasar Persaingan Sempurna","authors":"Gian Fitriani Utami, Eti Kurniati","doi":"10.29313/jrm.v2i2.1165","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1165","url":null,"abstract":"Abstract. Market equilibrium in the short run in a perfectly competitive market is a condition in which the quantity supplied is equal to the quantity demanded. One way to analyze the market equilibrium in the short run is to analyze the effect of a shift in the supply curve on the market equilibrium. This study analyzes the effect of the shift in the supply curve on the market balance in the short term. The purpose of this study is to analyze the effect of a shift in the supply curve on prices and the equilibrium quantity in the short run in a perfectly competitive market. The equilibrium price is determined in the decision-making process of consumers and producers. A shift in the supply and demand curves will cause a new market equilibrium or the market equilibrium price and quantity to change. The change will depend on the slope of the demand curve and supply curve. \u0000Abstrak. Keseimbangan pasar dalam jangka pendek pada pasar persaingan sempurna merupakan kondisi dimana jumlah penawaran sama dengan jumlah permintaan. Salah satu cara untuk menganalisis keseimbangan pasar dalam jangka pendek menggunakan analisis efek pergeseran kurva penawaran terhadap keseimbangan pasar. Pada penelitian ini menganalisis efek pergeseran kurva penawaran terhadap keseimbangan pasar dalam periode jangka pendek. Tujuan dari penelitian ini adalah menganalisis efek pergeseran kurva penawaran terhadap harga dan jumlah keseimbangan dalam jangka pendek pada pasar persaingan sempurna. Harga keseimbangan ditetapkan dalam proses pengambilan keputusan para konsumen dan produsen. Pergeseran kurva permintaan dan penawaran akan menyebabkan keseimbangan pasar baru atau harga dan jumlah keseimbangan pasar berubah. Perubahan tersebut akan tergantung pada kemiringan kurva permintaan dan kurva penawaran.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80784651","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":"Penggunaan Metode Principal Component Analysis dalam Menentukan Faktor Dominan","authors":"Gina Enzellina, Didi Suhaedi","doi":"10.29313/jrm.v2i2.1192","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1192","url":null,"abstract":"Abstract. Principal Component Analysis is a statistical technique that has been widely used in terms of data processing. This study aims to extract interrelated variables. This type of research is quantitative in nature by taking the case of fundraising in Dompet Dhuafa, West Java. The variables in this study are the ten types of collection funds from 2016-2021 with 72 data. This shows that the selection of the dominant factor can be used by the principal component analysis method. The results of this study show that there are 10 variables (=Fidyah, =Zakat MPZ, =Zakat Fitrah, =Kurban, =Bound Infak, =Thematic Infak, =Humanity, =Waqf, =Infak ,=Zakat ) which is extracted into 5 Principal Components based on the eigen1 value , where the first Principal Component is showing the most dominant factor. The first principal component is zakat with a loading value of 0.414 and a variance percentage of 19.39% from 64.37%. Based on the fact in Dompet Dhuafa that the dominant factor is zakat with a percentage of 40%. So that the relative error of the research results is the same as the real data of 0.035. \u0000Abstrak. Principal Component Analysis adalah teknik statistik yang sudah digunakan secara luas dalam hal pengolahan data.  Penelitian ini bertujuan untuk mengekstraksi variabel yang saling berhubungan. Jenis peneitian ini bersifat kuantitatif dengan mengambil kasus dana penghimpunan di Dompet Dhuafa Jawa Barat. Variabel dalam penelitian ini ialah ke sepuluh jenis dana penghimpunan dari tahun 2016-2021 dengan data sebanyak 72. Hal ini menunjukan bahwa pemilihan faktor dominan dapat digunakan metode principal component analysis. Hasil dari penelitian ini menunjukan ada 10 variabel (=Fidyah, =Zakat MPZ, =Zakat Fitrah, =Kurban, =Bound Infak, =Thematic Infak, =Humanity, =Waqf, =Infak ,=Zakat ) yang diekstraksi menjadi 5 Principal Component berdasarkan nilai eigen≥1 , dimana principal component pertama ialah menunjukan faktor yang paling dominan karena memiliki nilai keragaman total yang paling besar. Principal Component pertama ialah zakat dengan nilai loading  sebesar 0,414 dan presentase varians sebesar 19,39% dari 64,37% . Berdasarkan kenyataan di Dompet Dhuafa bahwa faktor dominan adalah zakat dengan persentase sebesar 40 %.  Sehingga galat relatif hasil penelitian sama dengan data real sebesar 0.035.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89433402","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":"Penggunaan Hybrid K-Means dan General Regression Neural Network untuk Prediksi Harga Saham Indeks LQ45","authors":"Gilland Achyar, Onoy Rohaeni","doi":"10.29313/jrm.v2i2.1193","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1193","url":null,"abstract":"Abstract. General Regression Neural Network (GRNN) is a nonparametric method of developing the concept of an artificial neural network. The GRNN operation is based on the estimated expected output value determined by the input set. One of the characteristics of GRNN is that the number of neurons in the pattern layer will increase with the amount of training data. This problem can be solved with K-means. The K-means method in this study aims to obtain various groups of training data based on similar characteristics so that it is easier for GRNN to study data in a group and reduce the problem of network complexity and large computations. One of the implementations of hybrid K-means & GRNN is to predict the price of the LQ45 stock index. The LQ45 stock price index is a combination of 45 stock members with high liquidity. One of the efforts before market participants make a decision to invest is to predict the stock index in the future to understand the investment prospects of a company in the future so as to reduce the risk for investors in investing. The results of this study indicate that the K-Means & GRNN hybrid model has a MAPE value of 0.943%. The results of the LQ45 index stock price prediction for the next period show the LQ45 index price of Rp1,002,28. \u0000Abstrak. General Regression Neural Network (GRNN) merupakan metode nonparametrik dari pengembangan konsep jaringan syaraf tiruan. Operasi GRNN didasarkan pada estimasi nilai harapan output ditentukan oleh himpunan input. Salah satu karakteristik dari GRNN adalah jumlah neuron pada pattern layer akan bertambah seiring meningkatnya jumlah data pelatihan. Permasalahan tersebut dapat diatasi dengan K-means. Metode K-means pada penelitian ini bertujuan untuk mendapatkan berbagai kelompok data pelatihan yang dikelompokkan berdasarkan karakteristik yang serupa sehingga GRNN lebih mudah mempelajari data dalam suatu kelompok serta mengurangi masalah kompleksitas jaringan dan jumlah komputasi yang besar. Salah satu implementasi hybrid K-means & GRNN adalah memprediksi harga saham indeks LQ45. Harga saham indeks LQ45 merupakan gabungan dari 45 anggota saham dengan likuiditas yang tinggi. Salah satu upaya sebelum pelaku pasar mengambil keputusan untuk berinvestasi adalah memprediksi nilai indeks saham pada waktu yang akan datang untuk memahami prospek investasi saham sebuah perusahaan pada masa yang akan datang sehingga mengurangi resiko bagi investor dalam berinvestasi. Hasil dari penelitian ini menunjukkan bahwa model hybrid K-Means & GRNN memiliki nilai MAPE sebesar 0.943%. Hasil prediksi harga saham Indeks LQ45 untuk periode selanjutnya menunjukkan harga indeks LQ45 sebesar Rp1.002,28.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86076441","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":"Model Perhitungan Pendanaan Program Pensiun Manfaat Pasti Menggunakan Metode Projected Unit Credit","authors":"Jessica Delianti, Onoy Rohaeni","doi":"10.29313/jrm.v2i2.1162","DOIUrl":"https://doi.org/10.29313/jrm.v2i2.1162","url":null,"abstract":"Abstract. The defined benefit pension program is a program organized by the Pension Fund. The calculation of defined benefit pension plan funds is carried out using the actuarial calculation method which calculates the cash value of pension benefits, normal contributions, and actuarial obligations. This study uses the projected unit credit method where the benefits are calculated according to the services provided up to the date of calculation. Based on the calculation results, the normal contribution for participants with the same basic salary and different years of service has a difference of  while for participants with a basic salary and years of cooperation there is a difference of  where participants with the longest working period and the largest basic salary will pay a larger contribution with smaller installments every year. The amount of the actuarial obligation will be equal to the value of the pension benefit to be received. Likewise, the value of pension benefits, for participants with the same basic salary and different years of service, there is a difference of, while for participants with different basic salaries and years of service there is a difference of . Thus, the basic salary affects the cash value of the pension benefit more than the length of service. \u0000Abstrak. Program pensiun manfaat pasti merupakan suatu program yang diselenggarakan oleh lembaga Dana Pensiun. Perhitungan pendanaan program pensiun manfaat pasti dilakukan menggunakan metode perhitungan aktuaria yang menghitung nilai tunai manfaat pensiun, iuran normal, dan kewajiban aktuaria. Penelitian ini menggunakan metode projected unit credit dimana besar manfaatnya dihitung sesuai dengan jasa yang telah diberikan sampai dengan tanggal perhitungan. Berdasarkan hasil perhitungan bahwa iuran normal untuk peserta dengan gaji pokok sama dan masa kerja berbeda memiliki selisih 5% sedangkan untuk peserta dengan gaji pokok berbeda dan masa kerja sama memiliki selisih 34% dimana peserta dengan masa kerja terlama dan gaji pokok terbesar akan membayar iuran lebih besar dengan cicilan lebih kecil tiap tahun. Besarnya kewajiban aktuaria akan sama besar dengan nilai manfaat pensiun yang akan diterima. Begitu juga dengan nilai manfaat pensiun, untuk peserta dengan gaji pokok sama dan masa kerja berbeda memiliki selisih  sedangkan untuk peserta dengan gaji pokok berbeda dan masa kerja sama memiliki selisih . Dengan demikian besar gaji pokok lebih mempengaruhi nilai tunai manfaat pensiun dibandingkan dengan masa kerja.","PeriodicalId":31272,"journal":{"name":"Jurnal Riset Pendidikan Matematika","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90979787","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}