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Elkom: Jurnal Elektronika dan Komputer
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 19070012     EISSN : 27145417     DOI : https://doi.org/10.51903/elkom.v14i1
Core Subject : Education,
Education
Elkom : Jurnal Elektronika dan Komputer merupakan Jurnal yang diterbitkan oleh SEKOLAH TINGGI ELEKTRONIKA DAN KOMPUTER (STEKOM). Jurnal ini terbit 2 kali dalam setahun yaitu pada bulan Juli dan Desember. Misi dari Jurnal ELKOM adalah untuk menyebarluaskan, mengembangkan dan menfasilitasi hasil penelitian mengenai Ilmu bidang informatika, sebagai media bagi para dosen, guru, peneliti dan para praktisi dalam bidang teknologi informasi dari seluruh Indonesia, dalam melakukan pertukaran informasi tentang hasil-hasil penelitian terbaru yang telah dilakukan.
Arjuna Subject : -
Articles 631 Documents
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Perbandingan Naïve Bayes dan KNN Dalam Klasifikasi Tweet BBM Subsidi Doddy Ircham Pambudi; Sulastri
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.961

Abstract

The government that is running at this time is also not spared from public comments on Twitter, especially regarding the increase in subsidized fuel. There are at least 4 impacts felt by the community when subsidized fuel prices increase, namely a decrease in people's purchasing power, an increase in basic prices, an increase in the unemployment rate and an increase in the poverty rate. This study aims to implement the Naïve Bayes Classifier and KNN algorithms in classifying a tweet of an increase in subsidized fuel so that it can be identified as belonging to a class with positive or negative sentiments. The data used in this research are 560 tweets. The data is divided into 2, namely 500 training data from tweet data and 60 test data from tweet data stored in xlsx format. The results of the accuracy with the Naïve Bayes Classifier algorithm is 85% while the KN algorithm is 86.8% so it can be concluded that the KNN method is better than the Naïve Bayes Classifier method in classifying tweets of increases in subsidized fuel. Keywords: Subsidized BBM, Naive Bayes, KNN
PERANCANGAN SISTEM INFORMASI POKTAN BERBASIS MOBILE (STUDI KASUS DI POKTAN BENO RAHARJO, GLONGGONG, BALEREJO, KABUPATEN MADIUN Mutia Putri, Anggyanisa; Hari Murti
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.963

Abstract

Agriculture is an activity of managing biological natural resources with the help of technology, capital, labor and management to produce agricultural commodities which include food crops, horticulture, plantations and or livestock in an agro-ecosystem. Most of the Indonesian people's livelihoods are as farmers, so the agricultural sector is very important to develop in this country. Poktan Beno Raharjo in Glonggong Village, Madiun Regency has a problem, namely the absence of an information system that is useful for managing agricultural production data, managing farmer data, managing village granary data, recording planting of food crops and horticultural crops, managing subsidized fertilizer assistance. The mobile-based Poktan information system was created using the dart programming language with the flutter framework using the waterfall method and testing using the black box testing method.
PENERAPAN METODE SUPPORT VECTOR MACHINE ANALISIS SENTIMEN TWEET PERGANTIAN LOGO HALAL DI INDONESIA Widi Afandi; Tri Ginanjar Laksana; Nia Annisa Ferani Tanjung
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.964

Abstract

The Halal Product Assurance Agency (BPJPH) is an agency under the auspices of the Ministry of Religion with the task of ensuring the halalness of products in Indonesia. BPJPH has become a public concern after establishing the new halal logo. On February 10, 2022 the new halal logo was ratified by the Head of BPJPH, Muhammad Aqil Irham. This has become a topic of public discussion either directly or through social media, one of which is social media twitter. The number of opinion tweets about the change of the halal logo can be used as a data source to obtain information about public opinion on the change of the halal logo through sentiment analysis. Sentiment analysis can be done by machine learning approach, one of these is the SVM algorithm . In this research, oversampling and undersampling are applied to handle data that has an unbalanced sentiment class. The results showed that the Support Vector Machine (SVM) model using oversampling training data got the highest accuracy, recall, precision, and f1-score, namely 71% accuracy, 67% precision, 61% recall, and 61% f1-score while training using undersampling training data has the lowest performance, namely getting 56% accuracy, 51% precision, 57% recall, and 52% f1-score.
Pemilihan Media Digital Dalam Pemasaran Produk Keripik Di Bekasi Nunu Kustian, Nunu Kustian; Syamsiah; Siti Julaeha
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.986

Abstract

Digital marketing is an important part of promoting a business owned by an individual or an organization. Marketing is essential for startups to stay competitive and sustain their products on the market. For people who are computer novices, this is a challenge. One of them is the proprietor of Keripik Orang Kekinian, a chips company in Bekasi, Indonesia, which has limited sales capabilities for its product. Researchers help firms choose the best social media channels for promoting their products in order to overcome these difficulties. The methods involved are Simple Additive Weighting (SAW) and Analytical Hierarchy Processing (AHP). The results show that Instagram is the best social media platform for advertising products. The result obtained are expected to help business owners increase sales.
Implementasi AHP-WASPAS Untuk Pemilihan Internet Service Provider (ISP) dirgantara krisna gaesa; Setyawan Wibisono
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.992

Abstract

Internet Service Provider (ISP) is a company that provides internet services. The ISP network is a national and international scale network so that customers can be connected globally. There are many factors that must be considered in selecting an ISP, making choosing an ISP a difficult task. Factors that influence ISP selection include cost, bandwidth, coverage area and type of connection. ISP providers offer a variety of advantages that make it difficult for customers to choose the right provider. The method applied in determining ISP providers is the AHP method used for weighting criteria while the WASPAS method is used for evaluating ISP providers with the criteria of cost, bandwidth, coverage area and type of connection. The rating process using the WASPAS method uses four assessment criteria, namely cost with a weight of 0.54, bandwidth with a weight of 0.38, coverage area with a weight of 0.05 and type of connection with a weight of 0.03. The final results of the ranking show that ISPs with low cost, large bandwidth and wide coverage areas will make these ISPs the best choice, this is because the criteria for cost, bandwidth and coverage area have high weight. Conversely, ISPs with high costs and small coverage areas will be the worst choices in the ranking list.
SISTEM PENDUKUNG KEPUTUSAN MENENTUKAN KARYAWAN TERBAIK DITOKO KEAN DENGAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) Tyoso, Bestanto Atijaya; Diartono, Dwi Agus
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.993

Abstract

Selection of the best employees is a semi-structured matter that can be scheduled every month or year. It is not uncommon for companies to determine the best employees not in accordance with the company's assessment. Kean shops still use the manual method and often do not meet the criteria set by the company. By making the best employee decision support system in a grocery store using the simple additive weighting method. assist managers in making the best employee decisions and admins in editing, deleting and adding values in each of the existing criteria and directly connected to the system database. This system was developed using the Visual Studio Code website, PHP, CSS, XAMPP V3.3.0 and MySQL. The method used in this decision support system is simple additive weighting (SAW). With this website, decision making is more structured and value data for each employee can be stored in a database. The results of this decision support system will simplify the process of determining the best employees and this system does not need to use manual calculations and is far more efficient.
Sistem Pendukung Keputusan Pemilihan Teknisi Terbaik Menggunakan Metode Hibrid AHP-COPRAS Pada PT. Telkom Akses Regional 4 Rejani, Haikal Fikri; Agus Prasetyo Utomo
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.994

Abstract

Someone who is referred to as a technician is a person who has expertise in a particular field of technology. Telkom Group is the only state-owned telecommunications company and the largest telecommunications and network service provider in Indonesia. Evaluation of technician performance is important to support the smooth running of the company. Selection of the best technician, will increase the motivation of the technician's performance. Some of the problems encountered were the absence of a technician performance appraisal process, the absence of an appropriate selection method, and the absence of a Decision Support System (DSS) that could make it easier to assess the selection of the best technician. Designing and building a decision support system using the AHP and COPRAS methods on technician assessments at PT. Telkom Access Regional 4 (Semarang) to increase the morale of the technicians and appreciate them. In this study, the AHP-COPRAS method was used to create a web-based DSS, in providing a more objective assessment every month, and creating several reports that convey effective issues, such as rating reports and technician performance appraisal reports according to these criteria.
Rancang Bangun Sistem Persediaan Barang PT. Daya Cipta Karya Sempurna AWALUDDIN, CANDRA KITSI; Edy Supriyanto
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.998

Abstract

Data Processing PT. Daya Cipta Karya Sempurna regarding the entry and exit of goods at PT. Daya Cipta Karya Sempurna still uses a semi-manual system where when the ordered goods arrive, the items will be recorded in the warehouse using Microsoft Excel. Likewise with the items that come out are also recorded in the warehouse using Microsoft Excel. In addition, this information only exists in the warehouse so that when other parts or want to know the inventory of existing goods, other parts cannot access it directly. The section must ask the warehouse to find the state of the desired supply and must wait to get the answer. As a solution to the problems above, it takes an inventory system at PT. Daya Cipta Karya Sempurna Power that can be used to manage goods group data, goods data, user data, incoming goods data and outgoing goods data as well as display reports
INDONESIA Pola Asosiasi Untuk Rekomendasi Penataan Display Barang Menggunakan Algoritma Apriori dan FP-Growth (Study Kasus Gamefantasia Ada Swalayan Pati) MURDIANTO, BEKRI; Arief Jananto
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.999

Abstract

This data mining association processes 1224 Gamefantasia ticket redemption transaction data. The goal is to find a pattern of association between goods as a recommendation for structuring the display of goods at the cashier counter and increasing ticket exchange transactions. Modeling uses a comparison of two algorithms, namely the Apriori algorithm and FP-Growth. The data analysis method with the CRISMP-DM method is then processed by RStudio software. The results of the study with the same parameters support 0.02 and confidence 0.1 FP-Growth algorithm formed 53 rules, the strength of the association rule 6.2%, the accuracy was1245%. Whereas the Apriori algorithm forms only 12 rules, the strength of the association rules is 2.1% and the accuracy is 7.8%. Thus, it can be concluded that the use of the FP-Growth algorithm has better results than the Apriori algorithm because it has the highest accuracy in finding transaction patterns.
ANALISA SENTIMEN APLIKASI PEDULILINDUNGI DENGAN METODE NBC DAN SVM Farras Naufal Majid; Sulastri
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.1000

Abstract

PeduliLindungi is an application from the Government of Indonesia that was made in response to the COVID-19 pandemic. Since its initial release in 2020, this application has received many updates with the goal of improving its overall performance. One of the basics of updating applications is to process the reviews given by users at the Google Play Store using sentiment analysis. The methods used this time are Naive Bayes Classifier (NBC) and Support Vector Machine (SVM). The sample data used were 300 reviews with positive feedback and 300 reviews with negative feedback, for a total of 600 user reviews. The results of the NBC algorithm calculations produce an accuracy of 76%, a precision of 76%, a recall of 82%, and an f1-score of 79%. As for the SVM algorithm, it produces an accuracy rate of 80%, a precision of 83%, a recall of 80%, and an f1-score of 81%.

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