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Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB
Published by Universitas Pelita Bangsa
ISSN : 24073903     EISSN : 28291891     DOI : https://doi.org/10.37366/sigma.v16i1
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB merupakan jurnal ilmiah yang diterbitkan oleh Program Studi Teknik Informatika Universitas Pelita Bangsa (UPB) Cikarang dengan no p-ISSN 2407-3903 (Media Cetak). Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB adalah sebagai salah satu wadah publikasi bagi dosen-dosen yang memiliki penelitian ilmiah di bidang Teknik Informatika, Ilmu Komputer, Sistim Informasi, Artificial Inteligent, Data Mining, Image Processing, Rekayasa Perangkat Lunak. Setiap artikel yang diterbitkan oleh Jurnal Ilmiah SIGMA: Informatics Engineering of UPB telah melalui proses review dan editorial yang ketat serta menghormati ketentuan hukum hak cipta, privasi, dan etika publikasi ilmiah. Jurnal Ilmiah SIGMA : Information Technology Journal of UPB terbit dua kali dalam setahun, yaitu bulan Maret, Juni, September dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 396 Documents
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Penerapan Data Mining Untuk Menganalisis Data Bencana Gempa Bumi Di Kepulauan Maluku Pada BMKG Menggunakan Naïve Bayes Algorithm Nurhadi Surojudin
Jurnal SIGMA Vol 11 No 3 (2020): September 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Earthquakes are natural phenomena that cannot predict the location, scale, depth of the hypocenter and the place affected by the earthquake. Until now, there is no precise theory that can be used to predict this. The collection of data on earthquake events in the Maluku Islands provides an opportunity for writers to take part in problem problems, namely by applying the big data theorem (data mining) by applying the naïve Bayes algorithm application technique using a tool that can know the level of accuracy in making earthquake predictions. The research phase begins with the earthquake data process. Then the big data is normalized and the training dataset and testing dataset are generated. Then upload the training data set on the tool and do modeling using classification techniques with the application of Hebrew by testing the training data which is then evaluated with the test data set so that the final results of the research are obtained. Based on the research it can be seen that the annual earthquake disaster in 2019-2020 in the Maluku Islands, namely North Maluku Province with the truth of the prediction data of 71.1%, in North Maluku Province there was an earthquake disaster on Ternate Island with the correctness of the prediction data of 78, 6%, In Maluku Province, there was an earthquake on Seram Island with the accuracy of the prediction data of 92%. Based on research, it can be denied that Yahoo Naïve Bayes can be used properly for earthquakes. Keywords: Ring Of Fire, Data Mining, Normalisasi, Data Set, Data training, Data testing, Weka, Classification, Algoritma Naïve Bayes.
Implementasi Sistem Monitoring Absensi Berbasis Rfid Proxymity Muhtajuddin Danny
Jurnal SIGMA Vol 11 No 3 (2020): September 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The fact is that there are still many companies that use manual attendance records, that is, by using an attendance record at the time of entry and completion of work time. Reducing efficiency and company accuracy in optimizing their productivity This final project aims to design a prototype of an RFID attendance system that is integrated with a database to support the employee disciplinary attitude improvement program as the first step in improving the overall work performance of the company. This prototype RFID attendance system consists of several main components, namely tags that will be used as a substitute for ID cards and readers that are used to read information regarding employee attendance, database integration in this system will allow data to be stored automatically into the database. The result of this final project is a prototype of an RFID attendance system that has a function to store employee attendance data, with a maximum reading distance of 2 cm with a chance of success of 1 and a minimum reading interval of 2 seconds to perform its function optimally. Keywords: RFID, absence, otomatically
Penerapan Algoritma Naive Bayes Pada Analisa Penyebab Kurang Dan Lebihnya Penggunaan Cutting Tool (Study Kasus Di PT. Sumiden Sintered Component Indonesia (SSI) Edy Widodo
Jurnal SIGMA Vol 11 No 3 (2020): September 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

PT.Sumiden Sintered Component Indonesia (SSI) Is a company engaged in automotive component parts, and this company is also one of a group of companies from Japan namely Sumitomo Corporation in collaboration with local companies Santini Group. PT.SSI was founded in 2012 in the manufacture of component parts with metallurgical technology. Metallurgical technology with this synthesis is a new technology that has existed in Indonesia. PT.SSI has difficulty in processing data using cutting tools which often results in excess and underuse due to inaccurate data. To support this problem, the authors apply the Naive Bayes method to provide a solution in analyzing the problem of the lack and excess use of cuting tools at PT SSI. The data taken in this study is based on data in 2017 and 2018. This research is expected to help SSI companies in analyzing the problem of less and more use of cutting tools. That way, the application of this method is expected to help the user in doing his work. Naive Bayes Method Is a simple probabilistic classification that calculates a set of probabilities by adding up the frequency and combination of given dataset values. The algorithm uses the Bayes theorem and assumes all the attributes are independent or not interdependent given by the value of the class variable. In the above problem, the choice of using the Naive Bayes algorithm is due to the amount of data used in this study. Because the calculation of Naive Bayes algorithm only requires a small amount of training data to estimate parameters. Keyword : Naive Bayes, Prediction, Cutting Tool.
Perancangan Aplikasi Untuk Menganalisis Penyakit Menggunakan Pengobatan Tanaman Herbal Dan Cara Mengolahnya Dengan Certainty Factor Berbasis Android A. Yudi Permana
Jurnal SIGMA Vol 11 No 3 (2020): September 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Applications regarding diseases and herbal plants do not have a diagnostic system that can assist the selection process. Most of the processes used have not used disease analysis / diagnosis. Most of them provide information about diseases or about herbal plants directly. So often users have to look for diseases or plants first to find the information. The method used in designing information systems for diseases and herbal plants is a structured programming method using UML diagrams. When building this application, it takes software such as Apache as a web server, MYSQL as a database, Eclipse. The steps taken are analyzing the needs required by the application, designing according to the needs analysis, building an application program in accordance with the previously made designs, and testing the application. The results of this thesis will present that a disease information system and herbal plants can be developed using Eclipse and MYSQL database. This application that has been built can help the process of analyzing / diagnosing diseases and providing information about what herbal plants can be used as medicine and how to process these plants so that they are really easy for the user to consume. Keyword: Disease and Herbal Plants, Android, Eclipse, Apache
Penerapan Algoritma K-Means Dalam Klasterisasi Penjualan Laptop Antika Zahrotul Kamalia; Elvan Aan Pradana; Nurhadi Surojudin
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Laptops are indispensable both for students and for office workers because of their advantages compared to desktop computers. With the development of today's laptop era, there are various brands and specifications that sometimes make people have difficulty and difficulty in finding, choosing or buying the right laptop and according to their needs. Therefore, the purpose of this study is to determine the grouping of laptops that will be purchased by consumers using the K-Means algorithm method and to find out the relationships and clustering that can provide information to determine sales patterns for laptop sellers according to customer needs. Based on the results of the tests that have been carried out in this study, the K-Means algorithm shows a new insight, namely the grouping of laptop sales based on 3 clusters. Cluster 1 is a laptop sales category with low or Low specifications, namely 217 of 1000 laptop sales categories based on the specifications of the laptop being tested, then cluster 2 is a laptop sales category with medium or medium specifications, which is 286 of 1000 laptop sales categories based on the specifications of the laptop being tested, and the last is cluster 3 which is a category of laptop sales with fairly high specifications or High, namely 497 out of 1000 laptop sales categories based on the specifications of the laptop being tested. Keywords: Laptop, Data Mining, The k-Means algorithm.
Data Mining Implementation On Java North Coast Weather Forecast Dataset Using C4.5 Algorithm Dendy K. Pramudito
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Weather is one of the most influential things in everyday human life. Many activities carried out by humans cannot be separated from the prevailing weather conditions. Lately, there have been frequent irregularities in weather patterns that are not usual or can be said to be extreme. Therefore, observing the weather is very necessary to make predictions about the weather. The northern coastline is one of the most important routes in Java, especially the northern coast route in the Central Java, due to that information about weather forecasts on this route is needed. The purpose of this research was to obtain the most influence factors of weather changes. The data mining approach used in this research is decision tree method and C4.5 algorithm. From the test results of 2,400 weather forecast data taken from the accuweather site and divided into 2, namely training data as much as 1,680 data, the rest of testing data as much as 720 data, the results obtained from a decision tree with the root node is the humidity attribute with an accuracy rate of 81.94% which has been proven through rapid miner 9.10 tools. Keywords: Weather Forecast, Data Mining, C4.5 Algorithm, Decision Tree
Implementasi Smart Farming Dengan Sistem Monitoring Kelembaban Dan Suhu Pada Tanaman Peppermint Berbasis Internet Of Things Muhammad Najamuddin Dwi Miharja; Tyo Repsi Harta Sanjaya
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Technological developments in agriculture are increasingly advanced. all industries are competing to use the technology that characterizes the industrial revolution. To more easily understand Industry 4.0, the key is an internet-based network. One of them is smart farming. namely the use of platforms that are connected to technological devices. The mint plant comes from the European continent. This plant can grow anywhere such as Europe, Asia, Africa, Australia and North America. This plant can grow at an altitude of 100 to 900 m above sea level with a temperature of 20˚C – 30˚C, humidity 80-95% and full light intensity. In the research, the IOT bolting for temperature and humidity control, the results of this monitoring system proved that the sensor error rate was very small, which was 4%. Keywords Internet Of things(IOT), Smart Farming, hydroponics.
Penerapan Data Mining Untuk Prediksi Penerima Bantuan Pangan Non Tunai (BPNT) Di Desa Wanacala Menggunakan Metode Naïve Bayes Edy Widodo; Ahmad Jaelani
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The Non-Cash Food Assistance Program held by the government is often not on target due to many factors, one of which is the number of criteria that must be considered to be a decision of beneficiaries. Of the eleven criteria set requires the right algorithm to perform calculations so that the results given are more accurate. Naïve Bayes algorithm is a method for classification using probability theory that has a high degree of accuracy. Naïve Bayes algorithm testing uses Rapid Miner tools that produce an accuracy rate of 96% of the 50 data provided. This algorithm is right for the selection of recipients of non-cash food assistance. There are 2 classes that are needed, namely Worthy and Not Eligible. Keywords: Classification, Naïve Bayes, Rapid Miner, Non-Cash Food Aid
Aplikasi Pengecekan Alat Pemadam Api Ringan (APAR) Berbasis Android Pada PT. XYZ Di Bekasi Endah Yaodah Kodratillah; Nisa Nurhidayanti; Ana Fitrotun Nisa
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

APAR has a very important effect for handling small / light fires in a place. PT. XYZ in Bekasi is an industry that is engaged in food production, so it takes a lot of fire extinguishers to meet government regulations (PERMENAKER). Due to the large number of fire extinguishers currently available, a system/application is needed to assist during the APAR checking process and data management based on Android based APAR checking results. So that the process can be carried out more quickly, precisely, and will get information on APAR that are nearing expiry/APAR which needs to be replaced with new APAR contents (refill APAR). The methodology used to develop this system uses the waterfall method and the PHP programming language. The result of developing this application is an APAR checking application/system that is useful for minimizing officer errors in writing, searching for data from APAR checking results quickly and accurately, and providing information to officers about APARs that will expire/need to be refilled. The application can be accessed anywhere and anytime via android/smartphone. Keywords: Checking APAR, Android, Waterfall, PHP, Expired APAR.
Analisa Data Mining Untuk Prediksi Penyakit Kanker Paru Dengan Algoritma Regresi Linear Suherman Suherman; Faris Muammar; Irfan Afriantoro
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Lung cancer often causes no symptoms in its early stages. New symptoms appear when the cancer is large enough or has spread to surrounding tissues and organs. So that patients with lung cancer will only feel pain after the cancer spreads to the pleural layer, the thin layer that covers the lungs. This study aims to analyze lung cancer in early prevention. This study uses prediction techniques and stages in data mining to predict data on patients suffering from lung cancer with a linear regression algorithm method using rapidminer tools. training and 10% data testing. The results of the tests that have been carried out show that the variables or attributes used in this study (age, smoking, and test results) have a significant effect on this study, as evidenced by using a linear regression algorithm to provide good results with a Root Mean Squared Error value: 0.379 +/- 0.000 and Squared Error: 0.144 +/- 0.229. The conclusion of the research conducted by applying the linear regression algorithm can be made a prediction based on the functional relationship on the variables or attributes in the data. Keywords: Lung cancer, linear regression algorithm, Rapidminer

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