Jurnal Informatika Ekonomi Bisnis https://infeb.org/index.php/infeb <p><strong>Jurnal Informatika Ekonomi Bisnis</strong> adalah Jurnal Nasional, yang didedikasikan untuk publikasi hasil penelitian yang berkualitas dalam bidang Informatika Ekonomi dan Bisnis, namun tak terbatas secara implisit serta bebas biaya dalam Proses Submisi.</p> <p><strong>Jurnal Informatika Ekonomi Bisnis</strong> menerbitkan artikel secara berkala 4 (empat) kali setahun yaitu pada bulan Maret, Juni, September, dan Desember. Semua publikasi di jurnal ini bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan.</p> <p>&nbsp;</p> Rektorat Universitas Putra Indonesia YPTK Padang en-US Jurnal Informatika Ekonomi Bisnis 2714-8491 Analisis Text Mining pada Sosial Media Twitter Menggunakan Metode Support Vector Machine (SVM) dan Social Network Analysis (SNA) https://infeb.org/index.php/infeb/article/view/146 <p>Online loans are growing rapidly in Indonesia in the last two years. This is because the online loan administration requirements are easier compared to bank financial service loans. Online loans are financial services that provide online-based services. Along with the development of online loans, many illegal online loans have sprung up and often commit violations, such as leaking customer personal information and abusing data by carrying out extreme actions such as terrorizing customers who make online loan transactions. This certainly gets a lot of comments from the public, especially on social media twitter. This study aims to conduct a sentiment analysis to see what phenomena are happening among the public regarding online loans. The data used are tweets or retweets from Twitter social media with #pinjamanonline #pinjol. Twitter social media was chosen because an incident can become a phenomenon if it gets a lot of attention from the community, especially on Twitter social media. In this study, using text mining techniques by applying the Support Vector Machine algorithm to classify sentiments on twitter users regarding online loans. This study also looks at the interactions that occur on social media Twitter using social network analysis (SNA). the results of research and testing of the Support Vector Machine method to classify online loans with an Accuracy value level of 86.6%, with a positive precision of 86%, neutral of 1.00% and negative of 87%, positive recall of 90%, neutral 87% and negative of 26 % and positive F1-Score of 88% neutral 42% and negative 86%. Then at the Social Network Analysis stage there is the most influential account, namely influencer @alvinline21 with 1402 nodes.</p> Tri Putri Lestari Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-08-30 2022-08-30 65 71 10.37034/infeb.v4i3.146 Klasifikasi Citra Kualitas Bibit dalam Meningkatkan Produksi Kelapa Sawit Menggunakan Metode Convolutional Neural Network (CNN) https://infeb.org/index.php/infeb/article/view/143 <p>Palm oil is one of the plantation commodities that has a strategic role in Indonesia's economic development. Lack of employee knowledge about the types of diseases in oil palm seedlings resulted in errors in handling them. In the selection of seeds to be planted in plantations, sick will cause unstable palm growth and even die. This study aims to find the best solution according to experts when the emergence of pests or diseases is identified through the pattern and color of the leaves. The data used in this study comes from image data of PT.Gatipura Mulya which is conducting a nursery as many as 612 images of oil palm seedlings and can be divided into 4 classes. The method that can be used in this identification is Convolutional Neural Network (CNN) which can study objects in image patterns. The result of this research is that the accuracy of image recognition is very good. So that this research can be recommended in the introduction of oil palm image patterns.</p> Ego Oktafanda Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-08-30 2022-08-30 72 77 10.37034/infeb.v4i3.143 Metode Multi Attribute Utility Theory (MAUT) dalam Keputusan Pengendalian Persediaan Obat dan Alat Kesehatan https://infeb.org/index.php/infeb/article/view/148 <p>Medicines and medical devices are one of the most important parts of a health service, so it is necessary to guarantee the availability of drugs and medical devices for treatment so that the process can run effectively and efficiently. The shortage of medicines and medical devices is a significant public health problem, especially for medicines and medical devices associated with life-threatening conditions. Meanwhile, inventory that is too large will increase investment funds and increase risks such as loss, expiration and damage to drugs. For this reason, this study aims to make decisions on controlling the supply of drugs and medical devices so that they can be guaranteed in sufficient quantities by supporting decisions using the MAUT method. The data used in this study is the amount of inventory that runs out per day, per week, per month and a lot of inventory per day, per week, per month. The results of this study are expected that the Multi Attribute Utility Theory (MAUT) method can assist pharmacists in making decisions on controlling drug supplies and medical devices very well. So this research is very appropriate in controlling the supply of drugs and medical devices in pharmacies.</p> Retchi Puspita Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 78 83 10.37034/infeb.v4i3.148 Identifikasi Tingkat Penjualan Produk Herbal HWI Menggunakan Algoritma C4.5 https://infeb.org/index.php/infeb/article/view/141 <p>Herbal stokist HWI Benai has several products that are most in demand by customers, including Vinmory, Habaolive Honey, Slimming Juice etc. However, HWI Benai's great stokist often runs out of stock of these best selling products due to the absence of reguler bookkepping, so customers turn to stockists who have more product. This study aims to make it easier for HWI herbal stockists in Benai to supply more goods based on the products that are most in demand by customers. The data needed is based on variables including product name, product item, unit qty, total, price and subtotal. From this data, Unit wty, total, price and subtotal. From this data, it will help in the processof knowing which products are most in demand based on the accuracy values obtained using the RapidMiner software. The method of the method using a decision tree. The result of the study obtained variables that affect the results in determining the best selling product including the number of orders, product types, purchasing status and customer status. From some if these variables can determine the highest accuracy value and produce a decision tree. The conclusion of this study is that the best method in determining the level of best selling sales is one of them using the C4.5 Algorithm. The C4.5 algorithm is an algorithm in form of a classification in the form of rules thath change the results of complex decision to be simpler and easier to understand</p> Refni Sulastri Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 84 89 10.37034/infeb.v4i3.141 Pemodelan dan Simulasi Monte Carlo dalam Identifikasi Kebutuhan Bahan Bakar Minyak (BBM) https://infeb.org/index.php/infeb/article/view/149 <h1>Abstrak</h1> <p>Saat ini PT Ismadi Salam Batam dalam menjalankan penjualan BBM belum menggunakan simulasi perhitungan kebutuhan persediaan BBM di SPBU untuk pengambilan keputusan pimpinan, hal ini menyebabkan sering terjadi kekosongan stok di masing-masing SPBU. karena itu penulis tertarik membuat sebuah system pemodelan simulasi perhitungan persediaan BBM menggunakan metode Monte Carlo dan Pola LCM. Tujuan dari penelitian ini nantinya untuk mensimulasikan perhitungan penjualan BBM dengan cara membandingkan penjualan BBM pada bulan-bulan sebelumnya untuk memprediksikan ketersediaan BBM dibulan berikutnya agar pihak manajemen tau berapa banyak stok BBM yang harus disediakan di masing-masing SPBU. Metode pengumpulan data yang digunakan pada penelitian ini adalah wawancara, observasi, dan studi pustaka. Metode pengembangan sistem yang digunakan adalah waterfall dengan pemodelan UML (Unified Model Language) yang terdiri dari use case diagram, activity diagram, sequence diagram dan class diagram. Sistem dirancang menggunakan Bahasa Pemrograman JAVA.</p> <p>Kata kunci: BBM, Identifikasi, Simulasi, Optimalisasi, Monte Carlo, PT Ismadi Salam</p> Sherly Agustini Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 90 95 10.37034/infeb.v4i3.149 Optimalisasi Top Down Network Design terhadap Peningkatan Pemberdayaan Pelayanan dalam Menggunaan Mikrotik https://infeb.org/index.php/infeb/article/view/139 <p>The background of this research is about computer network services to students of the Faculty of Social and Political Sciences (FISIP) at Musi Rawas University, Lubuklinggau. The computer network used in FISIP is very slow, and sometimes it doesn't work well. The purpose of this study is to apply the empowerment of network services using Top Down Network Design in optimizing the use of Mikrotik routers for network connection services. The data processed in this study by conducting a field survey at FISIP Lubuklinggau City. The stages of the process start from observing the mechanism and analyzing QoS (Quality of Service). The method applied to optimize the network to improve service empowerment in the use of the Mikrotik network is Top Down Network Design. This method focuses on the application layer, so that it can be estimated the characteristics of the network to be designed and those that already exist before determining the device to be used. This research stage uses network development using the Top Down Network Design method, which consists of problem analysis, logical network design, physical network design, testing, optimization, and network design documentation. The results of data collection and calculation resulted in very good network conditions. There is one condition where when face-to-face lectures are still being conducted, the network conditions are not very good because of the density of data lines.</p> Krisna Dexa Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 96 101 10.37034/infeb.v4i3.139 Manajemen Bandwidth dalam Mengoptimalkan Penggunaan Router Mikrotik terhadap Pelayanan Koneksi Jaringan https://infeb.org/index.php/infeb/article/view/144 <p>The internet with unlimited reach can connect all computers in a connection that makes it easier for users to get information, communicate and establish partnerships. The need for technology is very important to support all existing activities, such as the process of teaching and learning activities, data processing and transactions, administrative needs, exchanging information even in terms of social needs and so on. The problem that often occurs when using the internet is that bandwidth management on the internet is irregular and even wasted, it will even make internet network users experience bandwidth struggles, delays, and lagging. There is a need for bandwidth usage management so that unwanted things don't happen. The purpose of this research will be to apply a Queue Tree method to control clients in providing internet services so that they remain stable and efficient to get test results with QoS (Quality Of Service) parameters in optimizing router use. proxy for network connection services. Where the results obtained from 5 clients and 10 clients by limiting upload and download bandwidth of 50 Mbps on Throughput are 32.08 (%) medium category. The 0.0024 (ms) delay category is very good. Packet Loss 7.4 (%) good category. Jitter of 0.0024 (ms) is very good. And the total result of 10 Client Throughput 17.23 (%) is bad. The delay is 0.0044 (ms) which is great. Packet Loss 4.2 (%) good category. Jitter 0.0044 (ms) is very good by using bandwidth management can optimize internet usage well.</p> Siti Aminah Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 102 106 10.37034/infeb.v4i3.144 End-User Computing Satisfaction dalam Menganalisis Tingkat Kepuasan Pengguna Sistem Informasi Akademik https://infeb.org/index.php/infeb/article/view/150 <p>Universitas Terbuka (UT) merupakan Perguruan Tinggi Negeri dengan Sistem Belajar Jarak Jauh yang berdiri sejak tahun 1984, saat ini jumlah mahasiswa aktif lebih dari 340.000 gabungan dari seluruh Unit Program Belajar Jarak Jauh (UPBJJ) Se-Indonesia, diantaranya lebih dari 8.000 Mahasiswa aktif pada UPBJJ UT Pekanbaru. Sistem informasi akademik (SIA) Universitas Terbuka dengan alamat https://sia.ut.ac.id merupakan salah satu aplikasi yang diperuntukan buat mahasiswa untuk memenuhi kebutuhan layanan akademik dan untuk calon Mahasiswa baru yang ingin mendaftar ke UT. Pada semester 2021/22.2 atau masa registrasi 2022.1 (Des 2021 - Sekarang) SIA UT melakukan pembaharuan platform semula versi 4G bertranformasi ke 5G. Sejak masa pandemi Mahasiswa UT lebih aktif dalam menggunakan SIA UT dan Calon mahasiswa UT wajib mendaftar secara online tanpa harus datang ke kantor UPBJJ UT, dimana biasanya Mahasiswa banyak datang ke kantor UPBJJ UT untuk melakukkan registrasi matakuliah, lihat nilai serta layanan akademik lain dibantu oleh staf UT. Tujuan Penelitian ini dilakukkan untuk mengukur tingkat kepuasan pengguna pada SIA UT. Metode End User Computing Satisfation&nbsp; (EUCS) merupakan&nbsp; metode yang digunakan&nbsp; pada penelitian ini, untuk mengukur tingkat kepuasan pengguna pada atribut diantaranya Content, Accurary, Format, Ease of Use, dan Timeliness., berdasarkan data analisis didapatkan dari penilaian atribut Content 53%, Accurary 50%, Format 50%, Ease of Use 50%, dan Timeliness 51%. Hasil dari data analisis bisa disimpulkan bahwa persentase tertinggi pengguna SIA UT menyatakan puas pada atribut <em>content</em> dan ada beberapa atribut yang lain masih dalam kategori Bagus</p> Irwanzar Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 107 112 10.37034/infeb.v4i3.150 Pengendalian Persediaan Darah untuk Pasien dengan Hemoglobin Rendah Menggunakan Metode Backpropagation https://infeb.org/index.php/infeb/article/view/153 <p>The Blood Transfusion Unit (UTD) of the Rokan Hulu Regional General Hospital (RSUD) has an important role to fulfill the demand for blood from patients. Patients who need blood donation are patients with low hemoglobin levels. The problem faced by the UTD-RS is that they have not been able to meet the needs of each patient's blood request optimally. The reason is because it is not able to predict the need for blood that will come. To see the pattern of blood demand and then determine the appropriate inventory control method to assist the planning process for the fulfillment of blood supply at UTD in the next period. Materials (data) and Methods: The data processed in this study were patient data and blood demand data from January 2020 to January 2021. The data were sourced from the Laboratory Installation and UTD at the Rokan Hulu Hospital. The data is divided into training data and testing data. Then the blood demand data is processed by normalizing it first and then the prediction process is carried out using the Backpropagation method. Then analyzed and tested with the help of Matlab software. This study uses the best network architecture pattern produced is 5-5-1 with an accuracy rate of 68% and a Mean Squared Error value of 0.198. The backpropagation method used is able to help UTD Rokan Hulu Hospital to find out the blood needs that must be met so that the blood supply can be controlled. So that every blood request from patients with low hemoglobin can be met quickly.</p> Elyandri Prasiwiningrum Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 113 118 10.37034/infeb.v4i3.153 Data Mining Dengan Metode Naïves Bayes Classifer dalam Memprediksi Tingkat Kepuasan Pelayanan Dokumen Kependudukan https://infeb.org/index.php/infeb/article/view/155 <p>Kepuasan masyarakat terhadap layanan dokumen kependudukan merupakan hal yang sangat penting dalam peningkatan kualitas layanan sesuai yang diinginkan oleh masyarakat pada Dinas Kependudukan dan Pencatatan Sipil. Tujuan dari Penelitian ini adalah untuk memprediksi tingkat kepuasan masyarakat terhadap kualitas layanan dan untuk mengetahui hasil dari akurasi yang telah didapatkan dengan menggunakan algoritma Naïve Bayes. Data yang diolah merupakan data layanan kependudukan Tahun 2022. Dari hasil data yang diolah, bisa digunakan untuk meningkatkan kualitas dalam pelayanan dokumen kependudukan dan juga bisa digunakan untuk mengevaluasi kinerja pelayanannya. Hal ini dilakukan untuk mengetahui sejauh mana nilai dan kualitas dari pelayanan yang diberikan oleh Dinas Kependudukan dan Pencatatan Sipil Kota Pariaman kepada Masyarakat. Metode Naïve Bayes yang digunakan dalam penelitian ini untuk mencoba memprediksi kepuasan masyarakat terhadap kualitas pelayanan pada Dinas Kependudukan dan Pencatatan Sipil. Hasil dari indeks kepuasan terhadap pelayanan dokumen kependudukan pada Dinas Kependudukan dan Pencatatan Sipil menggunakan metode Naïve Bayes mendapatkan hasil yang baik.</p> Susi Wirma Copyright (c) 2022 Jurnal Informatika Ekonomi Bisnis https://creativecommons.org/licenses/by/4.0 2022-09-05 2022-09-05 119 123 10.37034/infeb.v4i3.155