Bandung Conference Series: Mathematics最新文献

{"title":"Optimasi Keuntungan Produksi Dengan Metode Fuzzy Linear Programming","authors":"Salsabilla L Veliani, Erwin Harahap, Gani Gunawan","doi":"10.29313/bcsm.v3i2.7862","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.7862","url":null,"abstract":"Abstrak. Dalam dunia nyata, ketidakpastian banyak meliputi proses pengambilan keputusan. Termasuk membuat keputusan tentang ukuran produksi, yang sering dipengaruhi oleh ketidakpastian permintaan. Jika didekati dengan bentuk fuzzy, ketidakpastian yang dinyatakan dalam linguistik sangat tepat. Himpunan fungsi keanggotaan ukuran pemesanan dan biaya persediaan akan dihasilkan dengan menggunakan aturan aritmatika fuzzy untuk menentukan ukuran produksi dalam keadaan fuzzy. Metode fuzzy linear programming (FLP) digunakan untuk menangani ketidakpastian dalam mengambil keputusan. Dalam penelitian ini metode yang digunakan adalah studi literatur dan wawancara. Manfaat dari penelitian ini adalah meningkatkan efisiensi dan profitabilitas produksi, mengurangi biaya dan meminimalkan risiko dalam pengambilan keputusan produksi. Metode penelitian yang digunakan melibatkan pemodelan matematis dengan FLP, pengembangan cutting plane sebagai teknik optimalisasi, dan analisis terhadap hasil pemodelan dan solusi yang dihasilkan. Hasil penelitian ini menunjukan bahwa penggunaan metode FLP dapat menghasilkan solusi yang optimal. \u0000Abstract. In the real world, uncertainty pervades many decision-making processes. This includes making decisions about production size, which is often affected by demand uncertainty. When approached in fuzzy form, uncertainty expressed in linguistic terms is very appropriate. The set of membership functions of order size and inventory cost will be generated by using fuzzy arithmetic rules to determine the production size in a fuzzy state. The fuzzy linear programming (FLP) method is used to handle uncertainty in making decisions. In this research, the methods used are literature studies and interviews. The benefits of this research are to increase production efficiency and profitability, reduce costs and minimise risks in production decision making. The research method used involves mathematical modelling with FLP, development of cutting plane as an optimisation technique, and analysis of the modelling results and the resulting solution. The results of this study show that the use of the FLP method can produce an optimal solution.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"11 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":"121297052","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":"Pemetaan Hyperplane Pada Support Vector Machine","authors":"Sekhan Rozaki Kusuma Wardana Tommy Rustandi, Didi Suhaedi, Yurika Pemanasari","doi":"10.29313/bcsm.v3i2.8187","DOIUrl":"https://doi.org/10.29313/bcsm.v3i2.8187","url":null,"abstract":"Abstrak. Penelitian ini difokuskan pada klasifikasi biner dengan data linear, dengan tujuan untuk memahami penggunaan pemetaan hyperplane dalam klasifikasi data menggunakan SVM dan bagaimana contoh penerapannya dalam dunia nyata. Metode penelitian yang digunakan meliputi studi literatur terhadap contoh-contoh penerapan SVM dengan pemetaan hyperplane. Hasil penelitian menunjukkan bahwa pemetaan hyperplane penting dalam klasifikasi data dengan SVM. Pemetaan ini memungkinkan SVM untuk memisahkan dua kelas dengan optimal dalam ruang fitur yang lebih tinggi, sehingga meningkatkan performa klasifikasi. Contoh-contoh penerapan pemetaan hyperplane pada SVM dalam dunia nyata juga berhasil diidentifikasi, yang menggambarkan bagaimana SVM dengan pemetaan hyperplane dapat digunakan dalam berbagai masalah klasifikasi dalam kehidupan sehari-hari dalam bentuk numerik sebagai studi kasus pada penelitian ini. SVM dapat digunakan untuk klasifikasi dalam berbagai konteks, termasuk multikelas dan nonlinear, penelitian ini hanya memfokuskan pada klasifikasi biner dengan data linear. Selain itu, penelitian ini tidak secara mendalam membahas penanganan data yang tidak seimbang atau fitur tidak langsung dalam konteks klasifikasi dengan SVM. \u0000Abstract. This research was made on binary classification with linear data, with the aim of understanding the use of hyperplane regularity in data classification using SVM and how it is applied in the real world. The research method used includes a literature study of examples of SVM implementation with hyperplane recession. The results of this research show that the hyperplane is important in classifying data with SVM. This mapping allows the SVM to optimally unify the two classes in a higher feature space, thereby increasing classification performance. Examples of the application of hyperplane earthquakes to SVM in the real world were also identified, which illustrates how SVM with hyperplane earthquakes can be used in various classification problems in everyday life in numerical form as a case study in this study. SVM can be used for classification in various contexts, including multiclass and nonlinear, this study only focuses on binary classification with linear data. In addition, this research does not deeply discuss unbalanced handling data or indirect features in the context of classification with SVM.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"168 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":"125561602","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 Susceptible Infected Removed (SIR) Penyebaran COVID-19 di Indonesia Menggunakan Metode Runge Kutta","authors":"Devy Andriyani, G. Gunawan, Didi Suhaedi","doi":"10.29313/bcsm.v3i1.6984","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6984","url":null,"abstract":"Abstract.  COVID-19 first emerged in 2019 in Wuhan, the capital of  Hubei Province, China and spread around the world to date. The rapid spread of the virus has made researchers interested in modeling the spread of the virus. Research on epidemiological mathematical models regarding COVID-19, one of which was conducted by Mohamed Lounis & Dilip Kumar Mugal who estimated the parameters of the SIR COVID-19 model in Algeria, in this study will be carried out prediction of the peak of the spread of COVID-19 in Indonesia with mathematical modeling susceptible, infected, removed removed (SIR). Prediction of the peak of the spread is done using the Order 4 Runge Kutta method and python software. From a series of tests that have been carried out, the results of predicting the peak of the spread of COVID-19 in Indonesia occurred around October to November 2020. Based on comparisons with actual data, there was a difference in the results of peak spread where in the prediction can only predict one peak of spread, in fact there are 2 peak spreads, namely November to December 2020 and January 2021 to February 2021.  And the spread of the COVID-19 virus will be close to zero at 550 days after March 2020, which is around September 2021. \u0000Abstrak. COVID-19 pertama kali muncul pada tahun 2019 di Wuhan, Ibukota Provinsi Hubei, Tiongkok dan menyebar ke seluruh dunia hingga saat ini. Penyebaran virus yang sangat cepat membuat para peneliti tertarik untuk membuat model penyebaran virus tersebut. Penelitian tentang model matematika epidemiologi mengenai COVID-19 salah satunya dilakukan oleh Mohamed Lounis & Dilip Kumar Bagal yang melakukan estimasi parameter model SIR COVID-19 di Aljazair, pada penelitian ini akan dilakukan prediksi puncak penyebaran COVID-19 di Indonesia dengan pemodelan matematika Susceptible, Infected, Removed (SIR). Prediksi puncak penyebaran dilakukan dengan menggunakan metode Runge Kutta Orde 4 dan software python. Dari serangkaian pengujian yang telah dilakukan maka diperoleh hasil prediksi puncak penyebaran COVID-19 di Indonesia terjadi pada sekitar bulan Oktober hingga November 2020. Berdasarkan perbandingan dengan data actual, ditemukan perbedaan hasil puncak penyebaran dimana pada prediksi hanya dapat memprediksi satu kali puncak penyebaran, pada kenyatannya terjadi 2 kali puncak penyebaran yaitu bulan November hingga Desember 2020 serta Januari 2021 hingga Februari 2021. Dan angka penyebaran virus COVID-19 akan mendekati nol pada 550 hari setelah bulan Maret 2020 yaitu sekitar bulan September 2021.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121787237","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 Metode SAW dan Entropy pada Pemilihan Armada Travel","authors":"Muhammad Hamzah, Didi Suhaedi, Y. Ramdani","doi":"10.29313/bcsm.v3i1.6927","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6927","url":null,"abstract":"Abstract. Travel is a mode of transportation that can be used to travel the Jakarta – Bandung route. Many travel fleets that can be the user's choice. Errors in selecting travel fleets have an impact on user discomfort when traveling. In this research a decision support system will be built that will select the travel fleet that can be the user's choice. The method used is the SAW method. The SAW method is a method that can choose the best alternative from several alternatives based on criteria. The SAW method requires the weight given to each criterion. The Entropy method can be used to determine the weight of the criteria so that research is more objective. The SAW and Entropy method algorithms are: data input, data normalization based on cost/benefit criteria attributes, summing the normalized data for each criterion, calculating the entropy value of each criterion, summing the entropy values, calculating the final entropy weight, calculating the preference value of each alternative and sorting it. There are 6 alternative travel fleets that depart via the Pasteur area and end in the Cawang area, namely: Bhineka Shuttle, MyTrans Travel, Aya Travel, Lintas Shuttle, Jackal Holiday and DayTrans. The criteria used are: price, travel time, rating, facilities, and service. The final result of the calculation using the SAW and Entropy methods was chosen as a travel service recommendation, namely Lintas Travel with a final value of 0.94552021. \u0000Abstrak. Travel merupakan moda transportasi yang dapat digunakan untuk melakukan perjalanan rute Jakarta – Bandung. Banyak armada travel yang bisa menjadi pilihan pengguna. Kesalahan dalam pemilihan armada travel berimbas pada ketidaknyamanan pengguna saat melakukan perjalanan. Pada penelitian ini akan dibangun suatu sistem pendukung keputusan yang akan menyeleksi armada travel yang dapat menjadi pilihan pengguna. Metode yang digunakan adalah metode SAW. Metode SAW adalah salah satu metode yang dapat memilih alternatif terbaik dari beberapa alternatif berdasarkan kriteria. Metode SAW memerlukan bobot yang diberikan terhadap setiap kriteria. Metode Entropy dapat digunakan untuk menentukan bobot kriteria supaya penelitian lebih objektif. Algoritma metode SAW dan Entropy yaitu: input data, normalisasi data berdasarkan atribut kriteria cost/benefit, menjumlahkan data normalisasi setiap kriteria, menghitung nilai entropy setiap kriteria, menjumlahkan nilai entropy, menghitung bobot entropy akhir, menghitung nilai preferensi setiap alternatif serta mengurutkannya. Terdapat 6 alternatif armada travel yang memiliki rute keberangkatan melalui daerah Pasteur dan menyudahi tujuan ke daerah Cawang yaitu: Bhineka Shuttle, MyTrans Travel, Aya Travel, Lintas Shuttle, Jackal Holiday, dan DayTrans. Kriteria yang digunakan yaitu: harga, waktu tempuh, rating, fasilitas, dan pelayanan. Hasil akhir perhitungan menggunakan metode SAW dan Entropy terpilihlah rekomendasi layanan travel yaitu Lintas Travel dengan nilai akhir 0,94552021.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115822519","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 Algoritma K-Nearest Neighbor, Greedy dan Brute Force dalam Menentukan Rute Pengiriman Barang","authors":"Muhamad Ihsan Maulidan, Gani Gunawan, M. Fajar","doi":"10.29313/bcsm.v3i1.6403","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6403","url":null,"abstract":"Abstract. The buying and selling transaction system that is widely used by the public today is the online buying and selling system. In the online buying and selling system, of course there is a process of sending goods. One of the goods delivery companies in Indonesia is J&T Express Cicurug, Sukabumi Regency, West Java. In the process of shipping goods, of course, a shipping line with the shortest distance is needed in order to streamline the process of sending goods. Delivery route problems can be solved using the Traveling Salesman Problem algorithm, in this study using the K-Nearest Neighbor (KNN) algorithm, the Greedy algorithm, and the Brute Force algorithm. This study aims to determine and compare the routes and distances traveled in the delivery of goods using the K-Nearest Neighbor algorithm, the Greedy algorithm and the Brute Force algorithm. The results obtained are that the K-Nearest Neighbor algorithm produces a total distance of 24.05 km, for the Greedy algorithm it produces a total distance of 23.5 km. Meanwhile, with the Brute Force algorithm, it is equal to 21.74 km. So using the Brute Force algorithm can produce better routes and total mileage compared to the K-Nearest Neighbor algorithm and the Greedy algorithm. \u0000Abstrak. Sistem transaksi jual beli yang sudah banyak masyarakat memanfaatkannya saat ini adalah dengan sistem jual beli online. Pada sistem jual beli online tentu terdapat proses pengiriman barang. Salah satu perusahaan pengirim barang yang ada di Indonesia ialah J&T Express Cicurug Kabupaten Sukabumi Jawa Barat. Pada proses pengiriman barang tentu perlu suatu rute pengiriman dengan jarak tempuh yang terpendek agar dapat mengefisienkan proses pengiriman barang. Permasalahan rute pengiriman barang dapat diselesaikan dengan algoritma pada Travelling Salesman Problem, dalam penelitian ini yaitu menggunakan algoritma K-Nearest Neighbor (KNN), algoritma Greedy, dan algoritma Brute Force. Penelitian ini bertujuan untuk menentukan serta membandingkan rute dan jarak tempuh dalam pengiriman barang menggunakan algoritma K-Nearest Neighbor, algoritma Greedy dan algoritma Brute Force. Hasil yang diperoleh yaitu dengan algoritma K-Nearest Neighbor menghasilkan total jarak tempuh sepanjang 24,05 km, untuk algoritma Greedy menghasilkan total jarak tempuh sebesar 23,5 km. Sedangkan dengan algoritma Brute Force yaitu sebesar 21,74 km. Jadi, dengan menggunakan algoritma Brute Force dapat menghasilkan rute dan total jarak tempuh yang lebih baik dibandingkan dengan algoritma K-Nearest Neighbor dan algoritma Greedy.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122191745","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 Pengendalian Persediaan Perishable Item dengan Metode Economic Order Quantity pada District Aminda Cafe Jatinangor","authors":"Aulia Fitri Hayuningtyas, Eti Kurniati, M. Fajar","doi":"10.29313/bcsm.v3i1.6381","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6381","url":null,"abstract":"Abstract. Along with the development of the economy, competition between companies is becoming increasingly stringent. This condition encourages companies to compete with other companies. The company seeks to meet consumer demand, one of which is by preparing the necessary supplies so that there are no shortages or excesses. The purpose of this research is to determine the number of economic orders. The method used is the Economic Order Quantity (EOQ). Based on the calculation results in the case study, the number of economical orders for each order was 114 kg of ribs, 208 kg of chicken, 70.73 kg of salmon, 135 kg of tenderloin, and 108 kg of short plates. The total inventory costs in one year are ribs of IDR 238,204,623, chicken IDR 178,113,289, salmon IDR 231,303,035, tenderloin IDR 259,549,288, and shortplate IDR 269,652,192. The total cost of inventory for 5 types of raw materials for 1 year is IDR 1,175,749,772. \u0000Abstrak. Seiring dengan perkembangan ekonomi persaingan antar perusahaan menjadi semakin ketat. Kondisi ini mendorong perusahaan untuk bersaing dengan perusahaan lain. Perusahaan berupaya untuk memenuhi permintaan konsumen salah satunya dengan cara menyiapkan persediaan yang diperlukan agar tidak terjadi kekurangan atau kelebihan. Tujuan penelitian ini untuk menentukan jumlah pemesanan ekonomis. Metode yang digunakan ialah Economic Order Quantity (EOQ). Berdasarkan hasil perhitungan pada studi kasus dihasilkan jumlah pemesanan ekonomis setiap satu kali pemesanan yaitu iga sebanyak 114 Kg, ayam sebanyak 208 Kg, salmon sebanyak 70,73 Kg, tenderloin sebanyak 135 Kg, dan shortplate sebanyak 108 Kg. Total biaya persediaan dalam satu tahun yaitu iga sebesar Rp238.204.623, ayam sebesar Rp 178.113.289, salmon sebesar Rp 231.303.035, tenderloin sebesar Rp 259.549.288, dan shortplate sebesar Rp 269.652.192. Biaya total persediaan untuk 5 jenis bahan baku selama 1 tahun sebesar Rp 1.175.749.772.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114985986","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 harga Crude Palm OIL (CPO) di Indonesia dengan menggunakan Metode Fuzzy Time Series Markov Chain","authors":"Arlinda Astri Frianti, Respitawulan, Icih Sukarsih","doi":"10.29313/bcsm.v3i1.6821","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6821","url":null,"abstract":"Abstract. The existence of Covid-19 and the feud between Russia and Ukraine which affected CPO Exports and Imports caused a fairly high increase in CPO prices in Indonesia. This study aims to predict the price of CPO in the Indonesian domestic market and its accuracy using the Fuzzy Time Series Markov Chain Method. The data used is data from January 2019 to October 2022. Based on the calculation results, a model with MAPE = 0.084666 is obtained. Using this model, the CPO price prediction in November 2022 is Rp. 17216.7431/kg different Rp. 1327.1769/kg with actual data of Rp. 18543.92/kg. The resulting error value shows that the predicted value using the Fuzzy Time Series Markov Chain is very accurate with an accuracy rate of  99.915334%. \u0000Abstrak. Adanya Covid-19 dan perseturuan antara Rusia dan Ukraina yang mempengaruhi Ekspor Impor CPO menyebabkan kenaikan harga CPO yang cukup tinggi di Indonesia. Penelitian ini bertujuan untuk memprediksi harga CPO di pasar domestic Indonesia dan tingkat akurasinya dengan menggunakan Metode Fuzzy Time Series Markov Chain. Data yang digunakan adalah data bulan Januari 2019 sampai bulan Oktober 2022. Berdasarkan hasil perhitungan diperoleh model dengan      MAPE = 0,084666. Menggunakan model tersebut didapat nilai prediksi harga CPO pada bulan November 2022 sebesar Rp. 17216,7431/kg berbeda Rp 1327,1769/kg dengan data aktual yaitu sebesar Rp. 18543,92/kg. Nilai error yang dihasilkan menunjukkan bahwa nilai prediksi menggunakan Fuzzy Time Series Markov Chain sangat akurat dengan tingkat akurasinya sebesar 99,915334%. \u0000 ","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134144736","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":"Pembentukan Portofolio Optimal dengan Metode Markowitz pada Saham Syariah IDX-MES BUMN 17","authors":"Windy Rianti Kartika, Icih Sukarsih, Eti Kurniati","doi":"10.29313/bcsm.v3i1.6342","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6342","url":null,"abstract":"Abstract. The capital market in Indonesia is an attractive form of investment. One of the most popular capital market instruments is stocks. The growth in the number of stock investors is one sign of the achievement of the Indonesian capital market. This growth also needs to be accompanied by knowledge about portfolio formation when investing. Stocks portfolio is a collection of various stocks that have risks, so analysis is needed in purchasing and diversifying shares. Therefore, the purpose of this study is to determine the risk and expected return results of the optimal portfolio formed by the Markowitz method. This research was conducted on the IDX-MES BUMN 17 sharia stock index for the period April 29 2021 – November 8 2022. The results of this study indicate that the optimal portfolio formed using the Markowitz method produces 4 portfolio-forming stocks, namely ELSA with a proportion of funds of 18.25%, PGAS with a proportion of funds of 11.53%, PTBA with a proportion of funds of 12.80%, and TLKM with a proportion of funds of 57.42%. The optimal portfolio with the proportion of stock funds owned by each stock forming the portfolio produces an expected portfolio return value of 0.0009256959 or 0.09% and a portfolio risk value of 0.01280470 or 1.28% where the portfolio risk value is smaller than the individual stock risk value of the portfolio-forming stocks. \u0000Abstrak. Pasar modal di Indonesia menjadi salah satu bentuk investasi yang menarik. Salah satu instrumen pasar modal yang paling populer adalah saham. Pertumbuhan jumlah investor saham menjadi salah satu tanda pencapaian pasar modal Indonesia. Pertumbuhan tersebut perlu diiringi pula dengan pengetahuan mengenai pembentukan portofolio ketika berinvestasi. Portofolio saham merupakan kumpulan berbagai saham yang memiliki risiko sehingga diperlukan analisis dalam pembelian dan diversifikasi saham. Oleh karena itu, tujuan penelitian ini adalah mengetahui hasil risiko dan expected return dari portofolio optimal yang terbentuk dengan metode Markowitz. Penelitian ini dilakukan pada indeks saham syariah IDX-MES BUMN 17 periode 29 April 2021 – 8 November 2022. Hasil penelitian ini menunjukkan bahwa portofolio optimal yang terbentuk dengan metode Markowitz ini menghasilkan 4 saham pembentuk portofolio, yaitu ELSA dengan proporsi dana 18,25%, PGAS dengan proporsi dana 11,53%, PTBA dengan proporsi dana 12,80%, dan TLKM dengan proporsi dana 57,42%. Portofolio optimal dengan proporsi dana saham yang dimiliki masing-masing saham pembentuk portofolio tersebut menghasilkan nilai expected return portofolio sebesar 0,0009256959 atau 0,09% dan nilai risiko portofolio sebesar 0,01280470 atau 1,28% dimana nilai risiko portofolio tersebut lebih kecil dari nilai risiko saham individual dari saham-saham pembentuk portofolio.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124782365","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":"Karakteristik Lalu Lintas Kendaraan Menggunakan Algoritma YOLOv3 dan Model Antrean M/M/1","authors":"Haris Dhaifullah, E. Harahap, M. Y. Fajar","doi":"10.29313/bcsm.v3i1.5778","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.5778","url":null,"abstract":"Abstract. Congestion is still one of the biggest problems in Indonesia until today, especially in big cities. Congestion can be caused by many things, including the lack of public transportation facilities, the large number of residents who have private vehicles, to the unsystematic traffic system. Congestion often occurs at intersections that are meeting points for vehicles from and to the city center, one of which is the Pasteur intersection in Bandung City. In this study, the process of collecting and processing traffic condition data at the Pasteur intersection will be carried out automatically and systematically to obtain traffic characteristics in the area. The queuing model used in this study is the M/M/1 model. This study uses the YOLOv3 Algorithm to help read and retrieve data on the number of vehicles leaving the queue from available traffic videos. The data obtained will then be processed using the M/M/1 queue model to obtain information about traffic characteristics at the Pasteur intersection, starting from vehicle service average data, vehicle arrival rates, percentage of traffic density levels, and other data. other. The information is expected to assist the authorities in the decision-making process regarding the traffic systematization in the area. \u0000Abstrak. Hingga saat ini, kemacetan masih menjadi salah satu problem terbesar di Indonesia terutama di kota-kota besar. Kemacetan dapat disebabkan oleh banyak hal di antaranya karena kurangnya sarana transportasi umum, banyaknya penduduk yang memiliki kendaraan pribadi, hingga sistem lalu lintas yang belum sistematis. Kemacetan sering kali terjadi di persimpangan-persimpangan yang menjadi titik pertemuan kendaraan dari dan menuju pusat kota, salah satunya pada persimpangan Pasteur di Kota Bandung. Pada penelitian kali ini, akan dilakukan proses pengambilan dan pengolahan data keadaan lalu lintas pada persimpangan Pasteur secara otomatis dan sistematis untuk mendapatkan karakteristik lalu lintas di daerah tersebut. Model antrean yang digunakan pada penelitian kali ini adalah model M/M/1. Penelitian ini menggunakan Algoritma YOLOv3 untuk membantu membaca dan mengambil data jumlah kendaraan yang meninggalkan antrean dari video lalu lintas yang tersedia. Data-data yang diperoleh kemudian akan diolah menggunakan model antrean M/M/1 sehingga didapatkan informasi-informasi mengenai karakteristik lalu lintas di persimpangan Pasteur, mulai dari data rataan pelayanan kendaraan, laju kedatangan kendaraan, persentase tingkat kepadatan lalu lintas, dan data-data lainnya. Informasi tersebut diharapkan dapat membantu pihak-pihak yang berwenang dalam proses pengambilan keputusan mengenai sistematika lalu lintas di daerah tersebut.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"91 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124406552","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":"Diagram Voronoi dalam Penentuan Zonasi Penerimaan Peserta Didik Baru pada Sekolah Negeri","authors":"Azka Azkiyatul Mahmudah, Respitawulan, Yani Ramdani","doi":"10.29313/bcsm.v3i1.6820","DOIUrl":"https://doi.org/10.29313/bcsm.v3i1.6820","url":null,"abstract":"Abstract. Voronoi diagram is a way to divide an area into several parts (cells). Each of these cells has one dot representing one location. The cell is composed of three or more Voronoi lines that intersect at a point and are separated by a Voronoi line. This research was conducted to apply the Voronoi diagram on zoning division for the selection of new student admissions in public schools. To this date, the school zone was determined using certain radius from the intended school, so that overlapping zones can occur. To solve the zoning problem, we construct a Voronoi diagram by selecting the target school as the center point of each cell. The area of school zone division was obtained based on the area that has the closest distance to the intended school point. \u0000Abstrak. Diagram Voronoi merupakan suatu cara untuk membagi suatu wilayah menjadi beberapa bagian (sel). Setiap sel tersebut terdapat satu titik mewakili satu lokasi. Sel tersebut terbentuk dari lebih dari sama dengan tiga garis Voronoi yang bertemu pada satu titik dan dipisahkan oleh sebuah garis Voronoi. Penelitian ini dilakukan untuk memanfaatkan diagram Voronoi pada pembagian zonasi untuk seleksi Penerimaan Peserta Didik Baru di sekolah negeri. Selama ini zonasi hanya dilihat dari jarak ke sekolah yang dituju sehingga dapat terjadi tumpang tindih zona. Salah satu upaya dalam penyelesaian masalah zonasi adalah dengan menggambarkan diagram Voronoi dengan memilih sekolah yang dituju sebagai titik pusat. Berdasarkan diagram Voronoi yang telah dihasilkan, didapatkan pembagian wilayah zonasi yang dilihat berdasarkan wilayah yang memiliki jarak lebih dekat ke titik sekolah yang dituju.","PeriodicalId":243556,"journal":{"name":"Bandung Conference Series: Mathematics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124484624","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}