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INDONESIA
Faktor Exacta
Published by Universitas Indraprasta PGRI
ISSN : 1979276X     EISSN : 2502339X     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Faktor Exacta is a peer review journal in the field of informatics. This journal was published in March (March, June, September, December) by Institute for Research and Community Service, University of Indraprasta PGRI, Indonesia. All newspapers will be read blind. Accepted papers will be available online (free access) and print version.
Arjuna Subject : -
Articles 8 Documents
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Search results for , issue "Vol 16, No 2 (2023)" : 8 Documents clear
APPLICATION OF SOCIAL MEDIA PLATFORM TECHNOLOGY IN PUBLICITY STRATEGY PROSUMPTION OF DIGITAL WORKERS IN THE MARKETPLACE Rayung Wulan; Udi Rusadi
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.17343

Abstract

The existence of social media platforms in the post-covid-19 pandemic era has increased sharply and penetrated various sectors among workers, especially digital workers. Various efforts to apply social media platform technology continue to increase in efforts to publicity strategies for the production of digital workers. platformsSocial media as a form of publicity expression for the production of digital workers has spread to various devices with the help of social media platforms with various applications. Social media platform technology as an effort to improve digital worker production publicity strategies that can increase the current marketplace rating. The purpose of this study is to apply social media platform technology which can be a strategy in publicity for digital workers in the marketplace. The method used in this study with the approachcomparative causal quantitative using surveys from several digital consumers who often use various marketplaces in their daily lives. , by adopting the slovin theory. In the testing phase of 368 respondents, there is a truth hypothesis from 105 digital consumers who are eligible for further testing in the marketplace with a simple linear regression analysis. Generated based on calculations with slovin theoryThe Publicity Strategy for Producing Digital Workers in the dominant Marketplace using the Social Media Platform shows a result of 95.2%, this result shows how high the presentation of these results is.
Implementasi Metode Support Vector Machine Dengan Algoritma Genetika Pada Prediksi Konsumsi Energi Untuk Gedung Beton Bertulang Asep Syaputra; Buhori Muslim; Nanda S. Prawira; Edowinsyah edowinsyah
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.16657

Abstract

Informasi tentang konsumsi energi sangat penting dalam mengukur efisiensi energi dan penghematan energi dalam bangunan. Konsumsi energi ini mengacu pada jumlah energi yang dibutuhkan untuk memberi daya pada bangunan pada waktu tertentu. Dengan mengetahui informasi ini, kita dapat mengevaluasi konsumsi energi yang ada dan membuat perubahan yang diperlukan untuk mengurangi penggunaan energi yang tidak perlu. Dalam jangka panjang, penghematan energi dapat membantu mengurangi biaya dan juga memberikan manfaat bagi lingkungan dengan mengurangi emisi gas rumah kaca yang dihasilkan oleh bangunan. Oleh karena itu, memperoleh informasi konsumsi energi yang akurat sangat penting bagi semua pihak yang terlibat dalam perencanaan, pembangunan, dan pengelolaan bangunan. Selama beberapa dekade terakhir, konsumsi energi di bangunan terus meningkat di seluruh dunia, dan sebagian besar konsumsi energi ini berasal dari Pemanasan, Ventilasi, dan Penyejuk Udara (HVAC) di dalam bangunan. Untuk mengatasi masalah ini, penelitian dilakukan dengan membuat model mesin vektor dukungan yang menggunakan algoritma genetika untuk memprediksi konsumsi energi di bangunan secara akurat. Dalam penelitian ini, dua model mesin vektor dukungan diuji, yaitu support vector machine dan support vector machine yang menggunakan algoritma genetika. Hasil pengujian menunjukkan bahwa model support vector machine memberikan nilai RMSE sebesar 2,6. Selanjutnya, algoritma genetika digunakan untuk mengoptimalkan parameter C dan memilih variabel prediktor yang paling relevan, dan hasilnya adalah nilai RMSE sebesar 1,7 dan hanya 3 variabel prediktor yang dipilih. Pada tahap selanjutnya, optimasi parameter dan pemilihan fungsi dilakukan untuk mencapai nilai RMSE terendah yang mungkin, dan hasilnya adalah RMSE sebesar 1,537. Dengan demikian, algoritma mesin vektor dukungan yang menggunakan algoritma genetika dapat memberikan solusi yang akurat dan efektif dalam memprediksi konsumsi energi di bangunan dengan nilai kesalahan terkecil.
Analisa Perbandingan Penerapan Metode SARIMA dan Prophet dalam Memprediksi Persediaan Barang PT XYZ Wawan Gunawan; Misbah Ramadani
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.13803

Abstract

Determining the right level of inventory is very important because it relates to the flow of money and can affect the performance of an organization. Too much inventory of goods can cause accumulation of storage space (warehouse) and reduce capital. The research will use data on sales of tires and wheels to be predicted using the SARIMA and Prophet methods, then the results will be compared for accuracy using RMSE. Based on the research results, it can be concluded that SARIMA (0, 0, 0)x(0, 1, 1, 12) with an RMSE evaluation result of 3.61 is superior to Prophet in predicting Dunlop product sales with an RMSE evaluation result of 4.02. SARIMA has the advantage in predicting because in the process there are features to find the best parameters to be implemented in the model.
Algoritma K-Means Untuk Mengetahui Minat Siswa Terhadap Jurusan Teknik Informatika putri dina mardika
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.17067

Abstract

There are already many information technology-based companies in the capital city, many job vacancies may be opened because they require experts with an educational background in informatics engineering. The research was conducted on YMIK 2 Jakarta high school students who concentrated on science and social studies. YMIK 2 High School students are familiar with information technology devices because there is a computer lab as a student facility for conducting computer learning activities. And there is an internet network in the form of free wifi at school. Researchers used data mining techniques with the K-Means algorithm and RapidMiner tools to process data to produce some conclusions about groupings related to whether or not YMIK 2 Jakarta High School students are interested in the Informatics Engineering major. The researcher divided the clusters into 2 groups consisting of cluster_0 which means students who are interested in informatics engineering and cluster_1 which means students who are not interested in informatics engineering. The data set used in this study was 50 data, according to the students participating in SMA YMIK 2 Jakarta. From the results of this study, it is known that students who are interested in majoring in informatics engineering are more numerous than students who are not interested in majoring in informatics engineering based on the k-means clustering algorithm.
Klasifikasi Citra Penyakit Daun Cabai Menggunakan Algoritma Learning Vector Quantization Puji Catur Catur Siswipraptini; Abdul Haris; Winda Novita Sari
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.15900

Abstract

The problem often occurs in chili leaves is organisms that interfere with chili plants which can reduce chili production. There are chili plant diseases that are difficult for farmers to recognize by using their eyes and without using tools. The purpose of this study was to produce a model capable of identifying chili leaf diseases based on leaf colour in order to make it easier for farmers to identify chili leaf diseases, especially  Phytophthora, Anthracnose, and Cercospora diseases, using the Learning Vector Quantization (LVQ) classification algorithm. Data was collected in the form of digital images of 30 chili leaves which were processed by resizing and transforming RGB to HSV which then proceeded to Canny Edge detection process with the aim of getting patterns from images of chili leaves. The result of testing LVQ algorithm using a confusion matrix get an accuracy of 80%, the precision value of 80%, recall value of 82%, and f-1 score of 81%. 
Clustering Indonesian Provinces on Prevalence of Stunting Toddlers Using Agglomerative Hierarchical Clustering Septian Wulandari
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.17186

Abstract

Stunting is a chronic nutritional problem caused by a lack of nutritional intake in toddlers. Indonesia is the 5th country with the highest cases of toddler nutrition experiencing stunting at 30.8% in 2018. The current problem, in Indonesia, is providing complete immunization and fulfilling child nutrition in each province is still low. Data obtained from 2018 to 2022 still toddlers who are malnourished and obese and there is no province grouping based on characteristics such as malnutrition, obesity, short toddlers, and complete basic immunization. Clustering is grouping objects into a group so that one cluster contains objects that are similar and different from other objects in other clusters. The agglomerative hierarchical clustering method can classify provinces based on the characteristics that cause stunting so that it can be used as a basis for early prevention for the Indonesian government to tackle stunting and can reduce stunting growth rates which continue to increase and can experience a decline. The agglomerative hierarchical clustering method used is the Average Linkage and Ward's algorithms with the data used is the prevalence of stunting taken in 34 provinces in Indonesia with 11 data attributes. The results of this study are that there are two clusters, namely Cluster 1 which has a relatively high prevalence of stunting with members of 13 provinces, and Cluster 2 which has a relatively low prevalence of stunting with members of 21 provinces. The highest cophenetic correlation value is in Ward's algorithm with a value of 0.8399978. So, it can be said that Ward's algorithm is better than the Average Linkage algorithm in clustering provinces in Indonesia on the prevalence of stunting toddlers.
Rancang Bangun Sistem Antrian Pintar Klinik Gigi Menggunakan Raspberry Pi Ardi Gunawan; Sasmitoh Rahmad Riady; Ismasari Nawangsih; Rianti Kinasih
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.16512

Abstract

Large-Scale Social Restrictions were imposed in Indonesia in 2020 as a response to the 2019 coronavirus disease (Covid-19), which has become a pandemic, including in Indonesia. The government's appeal regarding social distancing has made many dental clinics move to provide excellent service while still paying attention to social distancing policies. implementation of new policies and ways to overcome challenges by minimizing physical contact while still running business optimally and meeting patient needs. Before the pandemic occurred, patients were required to take a queue number first at the service location and then wait for the number to be called. Under the current conditions, in the midst of the COVID-19 pandemic, you must avoid crowds and maintain physical distance when interacting socially. In the description of the problem, we propose a smart queue as a solution to avoid crowds when going to the dentist's office. Smart Queuing System based on IoT with a Raspberry Pi camera capable of scanning QR codes as validation and a Raspberry Pi serving as a queue validation data server. This system will be used for online queues at dentist clinics. An online registration system determines whether registration is open or closed at the time of registration. With this system, it is hoped that online registration will be more efficient and orderly.
Perencanaan Produksi Menggunakan Metode Algoritma Fuzzy Time Series Average – Based, Strategi Perencanaan Agregat dan Metode Transportasi Sarah Julieta Simanjuntak; Drajat Indrajaya
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.16573

Abstract

Companies often have difficulty determining the right amount of production to meet demand. This is due to fluctuations in consumer demand from time to time. Production planning is related to the future, therefore production planning needs to be prepared on the basis of estimates made based on past data using several assumptions. The Fuzzy Time Series Average-Based Algorithm is a forecasting method with a fairly good level of accuracy because it implements an average system that is able to determine the length of the effective interval. In addition, it is important to determine the right strategy to minimize costs. This research produces forecasts for the next 1 year. The Mean Absolute Percentage Error (MAPE) value is 10.6% and the results are classified as Good. For the Aggregate Planning Strategy for tire products with a Level strategy, a fee of IDR 28,952,251,200 is obtained. While the Chase strategy costs Rp. 5,437,770,000 and for the Mixed strategy, a fee of Rp. 28,945,051,200. Then the alternative method of transportation for permanent workers results in a cost of Rp. 21,575,275,000 while the alternative workforce changed by Rp. 25,613,475,000. Then the calculation of the aggregate planning strategy using the Chase strategy method is the best method that can be used to meet production demands by minimizing production costs.Companies often have difficulty determining the right amount of production to meet demand. This is due to fluctuations in consumer demand from time to time. Production planning is related to the future, therefore production planning needs to be prepared on the basis of estimates made based on past data using several assumptions. The Fuzzy Time Series Average-Based Algorithm is a forecasting method with a fairly good level of accuracy because it implements an average system that is able to determine the length of the effective interval. In addition, it is important to determine the right strategy to minimize costs. This research produces forecasts for the next 1 year. The Mean Absolute Percentage Error (MAPE) value is 10.6% and the results are classified as Good. For the Aggregate Planning Strategy for tire products with a Level strategy, a fee of IDR 28,952,251,200 is obtained. While the Chase strategy costs Rp. 5,437,770,000 and for the Mixed strategy, a fee of Rp. 28,945,051,200. Then the alternative method of transportation for permanent workers results in a cost of Rp. 21,575,275,000 while the alternative workforce changed by Rp. 25,613,475,000. Then the calculation of the aggregate planning strategy using the Chase strategy method is the best method that can be used to meet production demands by minimizing production costs.

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