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bit-Tech
Published by Komunitas Dosen Indonesia
ISSN : 2622271X     EISSN : 26222728     DOI : https://doi.org/10.32877/bt
Core Subject : Science,
Computer Science & IT
The bit-Tech journal was developed with the aim of accommodating the scientific work of Lecturers and Students, both the results of scientific papers and research in the form of literature study results. It is hoped that this journal will increase the knowledge and exchange of scientific information, especially scientific papers and research that will be useful as a reference for the progress of the State together.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 122 Documents
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Perbandingan Metode SAW dan CPI dalam Sistem Pendukung Keputusan untuk Menilai Kinerja Guru Andi Loa; Benny Daniawan; Tugiman Tugiman; Amat Basri
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.141

Abstract

At educational institutions like Junior High School, Human Resources especially teachers determines the quality of the school. To determine Junior High School have good quality teachers, then the best teacher selection is needed to spur the teacher's performance. However, the best teacher selection at Santa Maria 2 Junior High School which in Tangerang still doing direct observation and no method implements the calculation. To overcome those problems, then Decision Support System is needed to do a calculation and rating the teachers at ease and accurate. The proposed Decision Support System is using Simple Additive Weighting and Composite Performance Index methods, where’s the calculation is obtained from each alternatives score and value weight from each criterion. The criteria in best teacher selection are reviewed from the absence aspect, professionalism, solidarity corps, personality, involving in activities from inside or outside school events. The final result from this calculation formed to ranking. The execution time of the SAW method has a faster average time of 0.489005 than the CPI method with an average time of 0.62258 seconds. On Relative Standard Deviation Testing CPI percentage greater than SAW with 3.90% and CPI 6.48%.
Prediction of Water Use Using Backpropagation Neural Network Method and Particle Swarm Optimization Afdhal Rizki Yessa; Mardi Hardjianto
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.158

Abstract

Clean water production has not been well considered between the balance of water use by the community and the production of clean water that is in accordance with the needs of the community. Prediction of water use in meeting the daily needs of the community is very necessary in order to be able to produce efficient water. This research can help PDAM Kota in Kalimantan to be able to produce clean water in accordance with the use of clean water by the community. The Backpropagation Neural Network method focuses on the recapitulation of water use by the community. For better prediction results, optimization is done with Particle Swarm Optimization (PSO). It is expected that the results in this study can predict community water use in daily activities. The test results showed that the Prediction results had RMSE of 0.040 with parameters for training cycle 600 values, learning rate 0.1 and momentum 0.2, and neuron size was 3 and in particle swarm optimization population size 8, max.of gene 100, inertia weight value 0.3, the value of local best weight 1.0 and global value of best weight 1.0
Analisis Penerapan Data Mining Analisa Pola Pembelian Pelanggan Pada Penjualan Cat Menggunakan Algoritma Apriori (Studi Kasus: Pt Indowarna Cemerlang Indonesia) Rino - -; Maman Novian
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.161

Abstract

Sales transaction data is one thing that can be used for making business decisions. Most sales transaction data is not reused, and is only stored as an archive and only used for making a sales report. Paint sales data is one science that can be applied in cases like this. Sales transactions that are not utilized properly can be extracted and reprocessed into useful information using data mining techniques. Using one of the data mining methods, namely the a priori algorithm, sales transaction data can be reprocessed so that it can produce a consumer buying pattern. This consumer buying pattern will later help companies make business decisions. PT Indowarna Cemerlang Indonesia is a company engaged in the paint trade, where the main activity is selling various wall paints, oil / wood paints, NC paints (car paints), epoxy paints (floor paints), depo-proof (anti leaked). PT Indowarna Cemerlang Indonesia does not reuse sales transaction data resulting from its sales activities. This data is only used as a reference for making sales reports and as an archive only, causing accumulation of data and unknown paint brands that are often sold or those that are of interest to customers. Therefore, the author takes the title application of data mining analysis of customer purchase patterns in paint sales using a priori algorithm. By doing this research, it is expected to provide results in the form of information that can be useful for related parties and can design sales strategies to increase company turnover.
Inventory Management with Forecasting Method: Single Moving Average and Trend Projection Amesanggeng Pataropura; Ivan Darmawan Sabatino; Riki Riki
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.162

Abstract

Inventory management using forecasting methods aims to improve effectiveness and efficiency that facilitate trading businesses in the process of business transactions, improve delivery of information quickly, accurately, and transaction data properly and minimize errors. The system running in the system of selling goods is still manual, that is, it is not well computerized. The method used is forecasting which helps determine the estimated future stock of goods. Single Moving Average and Trend Projection. It can be concluded that the results of implementing this new system can assist trading businesses in recording transactions in the system. We can predict the current flow of goods which has been calculated based on 2 modules that have a connection with the system.
Alleged Bad Credit at Saving Cooperatives Borrow Flamboyant Assistance PPSW Jakarta With Comparasion the Algorithms Naive Bayes and C4.5 Renaldi Renaldi; Yusuf Kurnia
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.163

Abstract

Data mining is often used in the financial sector, one of which is cooperatives. According to Law No. 25 of 1992, what is meant by cooperatives are business entities whose members are individual or cooperative legal entities based on activities based on the principles of cooperatives as well as as a people's economic movement based on the principle of kinship. One of the things that needs to be considered is the provision of credit or borrowing in the Flamboyan cooperative, which in this study there are many bad crediting occurrences that occur in the Flamboyan cooperative. By using a lot of data mining techniques, data can be utilized optimally. From the above problems, it can be overcome by utilizing data mining techniques, namely Predicting Bad Credit at the Flamboyant Savings and Loan Cooperative Fostered by PPSW Jakarta Using Comparative Algorithms Naive Bayes and C4.5. The algorithm used in the system is the best result of the Naive Bayes and C4.5 comparison based on data from the Flamboyan cooperative. The results obtained from the comparative data processing between the Naïve Bayes algorithm and the C4.5 using a dataset of 2282 transaction data obtained the results of the accuracy of the Naïve Bayes algorithm of 69.19% and the C4.5 algorithm of 71.87%, based on the accuracy results state that the C4 algorithm .5 is superior to the Naïve Bayes algorithm. Then the results from the C4.5 decision tree are translated into the bad credit prediction system in the Flamboyan cooperative.
Information System Point of Sales Based Real Time on PT. Buccheri Indonesia Teofilus Sunarsa; Paulus Yayan Christian; Yuki Gunawan
bit-Tech Vol. 3 No. 1 (2020): Distance Learning
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i1.164

Abstract

Buccheri is a retail company that provides quality footwear for men and women since 1980. We begin our history with our first flagship store in a historic business district, "Pasar Baroe." Now Buccheri has been through various challenges and experienced many developments. This of the most prestigious and footwear brand in Indonesia. As the leading formal shoes in Indonesia, Buccheri tends to put their segmentation in the middle-upper class. Established in 1980, the name of this brand is well known among Indonesian consumers. With specialized informal to daily leather-based footwear, and claimed as a handcrafted, stylish yet comfortable footwear brand. Buccheri is committed to providing a high-quality product and post-buying service and maintaining the best craftsmanship in every item that we produce. Innovation is also one of the keys to our future development. With the development of existing technology, Buccheri made changes to its sales system. With the many stores that exist, real-time technology is needed to meet the company's business needs. Therefore, the point of Sale is redeveloped to answer the needs of time-based
The Acceptance Study of e-commerce Customers Based on TAM Rainaldo Diogenes Susilo; Benny Daniawan; Andri Wijaya; Suwitno Suwitno
bit-Tech Vol. 3 No. 3 (2021): Remote Delivery
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i3.165

Abstract

The improvement of information technology and science has grown rapidly. CV. Sukses Mandiri Jaya, which is engaged in the sale of spare parts for motorcycle, does not have a computerize system, making it difficult for buyers to see the products and to make transactions. The work aim to create a web based system with the Technology Acceptance Model (TAM) to measure the usability level of the system. TAM is used to achieve a certain goal by identifying some of the basic variables and by measuring factors that affect system acceptance. TAM positions two beliefs, that are Perceived Usefulness and Perceived Ease of Use as major factors in system acceptance behavior. It was found that the proposed system accepted by customers, which was measured by a questionnaire involving 57 respondents. The results show that Perceived Usefulness and Perceived Ease of Use simultaneously and partially have positive and significant influence on the Behavior Intention. This also shows that result of the relative contribution of perceived usefulness (X1) is 36.75% and the perceived ease of use (X2) is 63.25%. The effective contribution of Perceived Usefulness is 29.44% and the Perceived Ease of Use is 50.66% for Behavior Intention, which means that the effect of Perceived Ease of Use is more dominant than the Perceived Usefulness
Decision Support Systems the Selection of Outstanding Students Using Simple Additive Weighting (SAW) and Weighted Product (WP) Methods Riki Riki; Mimi Yanti
bit-Tech Vol. 3 No. 1 (2020): Distance Learning
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i1.168

Abstract

Appreciation for outstanding students is one of the encouragement for students to continue to maintain and improve their achievements. Generally, the selection of outstanding students in every school still uses the report value as the reference. Currently the selection of outstanding students at SMP Strada Santa Maria 2 still using the report card value (academic) as a reference. In addition, the school does not have a system that helps the selection and processing process based on several criteria considered. Therefore a decision support system is needed in order to help overcome problems and accelerate the selection of outstanding students. In this decision support system uses the SAW method (Simple Additive Weighting) and WP (Weighted Product) and compares the two methods. The criteria used included the value of the average semester 1, the value of the average semester 2, the value of attitudes, absences, and activeness of extracurricular activities. The results of these calculation in the form of the final value of each method and form of ranking that will be recommended to assist the school in determining the outstanding students according to the required criteria. Based on the terms of execution time, the SAW method is slightly faster than the WP method and and in terms of the test results using RSD, the value generated from the WP method calculation is better than the value generated from the SAW method calculation, where the RSD value of the WP method is 14.74% and SAW is 10.46%.
Junior Class Preparedness Classification Faces A National Exam Using A C.45 Algorithm With A Particle Swarm Optimization Approach Asep Suherman; Didi Kurnaedi; Rizqi Darmawan
bit-Tech Vol. 3 No. 1 (2020): Distance Learning
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i1.169

Abstract

These studies are counter to a trend of falling students' graduation rates on the national exam. This is because of the way students prepare their readiness to face national tests is inaccurate. On this study the hybrid method c4 algorithm.5 and the swarm particle optimization to produce a class readiness of students with high and accurate accuracy. This research suggests that by using hybridmethodC4.5 andParticle Swarm Optimizationgenerates accuracy as 97.13 %, Precisionas 96,58 %, andRecallas 100 %. Then implemented through a web-based prototype application using programming javascriptlanguage
Decision Support System for Employee Performance Evaluation with Promethe Method. Case Study: Faculty of Engineering, Pancasila University Sri Rezeki Candra Nursari; Amir Murtako
bit-Tech Vol. 3 No. 1 (2020): Distance Learning
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i1.170

Abstract

High competent human resources can support the level of performance, by conducting performance evaluation assessments it will be known the achievements of each employee. Assessment of employee performance evaluation carried out by the Faculty of Engineering, University of Pancasila uses criteria of diligence, teamwork, sincerity to work, skills, initiative, independence and attendance. In this study, the authors used the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to assist in making employee performance evaluation decisions, so that it can be seen which employees get the reward with good performance. The data used is in the form of employee performance evaluation data using six stages of the PROMETHEE method.

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