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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Komtika (Komputasi dan Informatika) Jurnal ICT : Information Communication & Technology Aisyah Journal of Informatics and Electrical Engineering Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS)
Rasim Rasim
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Other

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Implementasi Jaringan Syaraf Tiruan Metode Backpropagation untuk Prediksi Penjualan Mobil Bekas Prima Dina Atika; Rasim Rasim
Jurnal ICT : Information Communication & Technology Vol 18, No 2 (2019): JICT-IKMI, Desember 2019
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v18i2.70

Abstract

Increased sales are needed in line with the rapid economic growth in Indonesia. Procurement of goods and services is an activity needed to realize developments in the area. Manually predictive calculations have a high level of risk and hinder the sales performance process. To handle this, a system is needed to be able to calculate the predictions of the number of used cars sold and reduce the risk of very heavy losses. With the application of this prediction system, it is expected to overcome these problems. The method used is the Backpropogation Method, a training method that uses multilayer perceptron to solve complex problems with supervised training methods, namely pairs that use input-output and which will be calculated is the weight, the desired output target. With the method of Backpropagation Artificial Neural Network (ANN) calculation. The results show that the application system created can produce predictive results that are accurate enough to get results that are not much different from actual sales, ie with MSE = 23.84.
Sosialisasi Keamanan Siber untuk Anak-anak di Panti Asuhan Aisiyah Bekasi Kusdarnowo Hantoro; Asep Ramdhani; Khaerudin; Rasim
Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Vol. 1 No. 1 (2020): July 2020
Publisher : Fakultas Teknik Universitas Bhayangkara Jakarta Raya

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Abstract

Anak-anak dan remaja sekarang banyak yang memposting di sosmed seperti Facebook, Twitter, Instagram seringkali menjadi korban kejahatan siber seperti phishing, bullying, social engineering oleh para predator dengan memanfaatkan sosial media, email dan fasilitas siber lainnya. Dengan berbagai macam kasus dan modus kejahatan siber seperti tersebut, maka perlu dibangun kesadaran di kalangan muda untuk memiliki bekal pengetahuan keamanan siber. Kegiatan ini memberikan tip dan tricks serta informasi bagaimana cara berselancar di dunia siber yang aman dalam menghadapi kejahatan siber.
Algoritma Apriori Untuk Pola Penjualan Pada Kedai Kopi Studi Kasus: Kedai Kopioko Aryo Juliano; Rasim; Sugiyatno
Journal of Students‘ Research in Computer Science Vol. 3 No. 1 (2022): Mei 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jsrcs.v3i1.1148

Abstract

Effective promotion can increase sales figures. One way is to identify market conditions, namely about consumer purchasing tastes, which can be observed through consumer purchase transaction data. In recent years, transaction data has been widely used as research material, which aims to build some new information related to sales patterns to help manage future business development. In this study, the a priori algorithm method was used to determine sales patterns. The results obtained from the experiments carried out that the application of data mining using yahoo a priori with the association rule method can run well and produce two association rules, by changing the minimum support and confidence parameters. After the experiment using the apriori algorithm, it was found that the combination of menu items that can be made for sales patterns or the development process uses the racist Kopioko package menu, potatoes with a value of 60.34%, and racist Kopioko, Agung with a value of 54.88 Keywords: Apriori Algorithm, Association Rules, Sales Pattern.   Abstrak Dengan promosi yang efektif dapat meningkatkan angka penjualan. Salah satu cara ialah dengan mengidentifikasi kondisi pasar yaitu tentang selera pembelian konsumen, yang dapat diamati melalui data-data transaksi pembelian konsumen. Dalam beberapa tahun terakhir, data transaksi telah banyak digunakan sebagai bahan penelitian, yang bertujuan untuk membangun beberapa informasi baru terkait pola penjualan untuk membantu mengelola pengembangan bisnis di masa depan. Dalam penelitian ini digunakan metode algoritma apriori untuk  mengetahui pola penjualan.Hasil yang diperoleh dari uji coba yang dilakukan bahwa aplikasi implementasi data mining menggunakan algoritma apriori dengan metode association rule dapat berjalan dengan baik dan menghasilkan dua aturan asosiasi, dengan merubah parameter minimum support dan confidence. Dari setelah dilakukan percobaan menggunakan algoritma apriori dapat disimpulkan bahwa kombinasi menu item yang dapat di buat untuk pola penjualan atau proses pengembangan promosi menggunakan menu paket Kopioko rasis, kentang dengan nilai confidence 60,34%, dan Kopioko rasis, regal dengan nilai confidence 54,88 Kata Kunci: Algoritma Apriori, Aturan Asosiasi, Pola Penjualan.
Analisis Sentimen Mengenai Gangguan Bipolar Pada Twitter Menggunakan Algoritma Naïve Bayes Oriza Sativa Dinauni Silaen; Herlawati Herlawati; Rasim Rasim
Jurnal Komtika (Komputasi dan Informatika) Vol 6 No 2 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v6i2.8198

Abstract

Bipolar disorder is one of the world's most common mental health disorders. To find out public sentiment regarding bipolar disorder, sentiment analysis is carried out through social media to analyze positive or negative sentiments with the aim of maintaining positive sentiment towards the problem of bipolar disorder. Twitter is a social media that is often used to exchange information, discuss, and even express emotions. The emotions of Twitter users can be called sentiment. Sentiment analysis is also carried out to see opinions or tendencies towards an opinion. Opinion tendencies can be in the form of positive or negative sentiments. The data used in this study uses the bipolar keyword. There are 2177 tweets data that were successfully obtained in the crawling process using API key access from Twitter developers, after which the data will be processed using preprocessing. The comparison of the presentations obtained is 70.92% expressing a negative opinion and 29.08% expressing a favorable opinion. The analysis results in this study using the nave Bayes algorithm is with an accuracy value of 92.110092%.
Analisis dan Optimalisasi Akses Point To Point Menggunakan Perangkat Power Beam M5 400 Out Dor Sistem (Studi Kasus : Onesnet) Rasim .; Mugiarso
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

Onesnet is a home internet service provider or what is called RT / RW Net so to provide this service Onesnet sends signals or data to remote areas using point-to-point access points and because the client itself is disseminated again, with that we use devices access point Nano Station Power Beam M5. This paper aims to implement point-to-point access and optimize two NanoStation M5 devices without using additional antennas to improve the quality and coverage of a wireless local area network, to obtain further coverage. The design was carried out at Onesnet Housing Mustika Karangsatria Blok EA 18 Number 3A, with a maximum radius of 1000 meters, with received signal strength parameters, ping test, and connection quality, as well as path losses using the Friis propagation model. By using the test results there are no obstacles or line of sight (LOS), it is proven that the access point device can reach a range of up to 1000 meters, and from the site survey test results, it is concluded that the observation location is in good connection quality to very good quality, the average is in a radius of fewer than 1000 meters from the access point. While the observation locations with poor connection quality are on average outside 1000 meters from the access point, and several locations cannot connect at all because the received signal is too weak..
The Weighted Product Method and the Multi-Objective Optimization on the Basis of Ratio Analysis Method for Determining the Best Customer Mugiarso Mugiarso; Rasim Rasim
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.6325

Abstract

The objective of this study is to compare the effectiveness of the Weighted Product (WP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods in determining the best customers. Onesnet, the case study service provider, provides discounts and rewards to eligible customers to support this objective. The problem addressed in this study is how to determine the most relevant method for selecting eligible customers for bonuses. To achieve this, sensitivity testing was conducted by altering the weights of each criterion in both methods and observing the percentage changes of the results. The Weighted Product method multiplies the rating of each connected attribute, which is raised to the appropriate attribute weight, to decide. Data for this study was collected through interviews and observations at Onesnet and processed using the Rank Order Centroid (ROC) method for weighting, and the WP and MOORA methods for evaluating and selecting a decision. The WP and MOORA methods produced different total values and rankings, but the modeling with either method can be used equally for selecting the best customers. While there was a 60% similarity in data between the two methods, the WP method is recommended over MOORA, as it prioritizes customers with high loyalty criteria as the best customers.
PENENTUAN PERINGKAT PELANGGAN TERBAIK MENGGUNAKAN METODE RANK ORDER CENTROID DAN WEIGHTED PRODUCT (STUDI KASUS ONESNET) Mugiarso; Rasim
Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E) Vol. 5 No. 2 (2023): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v5i2.190

Abstract

This study addresses the problem faced by Onesnet in its environment, which is how to provide discounts or rewards to customers who have not received them before. This is due to the increasing competition in the internet installation service industry. The aim of this research is to determine the best customers in order to maintain customer loyalty in the increasingly competitive industry. The Weighted Product method is used as a decision-making technique by multiplying the ratings of each connected attribute, where the ratings of each attribute must be exponentiated with the corresponding attribute weight. The data used in this research comes from interviews and observations at Onesnet, which will be processed using the Rank Order Centroid method for weighting and Weighted Product method to evaluate and make a decision. The result of this study is the most loyal customer who becomes the best customer with a value of 0.14578.
Co-Authors Aryo Juliano Asep Ramdhani Hantoro, Kusdarnowo Herlawati Herlawati Mugiarso Mugiarso Mugiarso Mugiarso Muhammad Khaerudin Oriza Sativa Dinauni Silaen Prima Dina Atika Sugiyatno Sugiyatno