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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 TERHADAP MINAT SISWA DALAM MATA PELAJARAN MATEMATIKA DENGAN METODE K-MEANS Sufajar Butsianto; Nurhali Saepudin
Jurnal SIGMA Vol 10 No 2 (2019): Desember 2019
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.974 KB)

Abstract

Kemampuan matematika yang diperlukan untuk menguasai dan menciptakan teknologi di masa depan, menjadikan matematika yang kuat perlu dibina sejak dini.Tujuan penelitian ini adalah Menerapkan metode K-Means untuk mengelompokan minat siswa terhadap mata pelajaran matematika dan untuk mendapatkan akurasi yang tepat dan cepat dalam mengelompokan minat siswa terhadap mata pelajaran matematika menggunakan metode K-Means. Metode yang digunakan yaitu dengan teknik data mining menggunakan algoritma K- Means. Proses ini menghasilkan 2 cluster yaitu ( minat ) Matematika dan ( kurang minat ) matematika, dengan menggunakan teknik data mining menggunakan algoritma K-Means, dan akurasi diukur dengan Davies Bouldin Index. Pengujian menggunakan validasi DBI (Davies Bouldin Index) diperoleh nilai untuk tiap-tiap cluster. Untuk kelas 10 pengujian cluster 1 menghasilkan nilai DBI 0.941 dan cluster 2 nilai DBI 0.335 , kelas 11 pengujian cluster 1 menghasilkan nilai DBI 0.660 dan cluster 2 nilai DBI 0.506, kelas 12 pengujian cluster 1 menghasilkan nilai DBI 0.271 dan cluster 2 nilai DBI 0.111. Dari perhitungan Davies Bouldin Index (DBI) dapat disimpulkan bahwa jika semakin kecil nilai Davies Bouldin Index (DBI) yang diperoleh (non negatif >= 0) maka cluster tersebut semakin baik.
Sistem Informasi Laundry Pada Wawa Laundry Berbasis Web Ahmad Turmudi zy
Jurnal SIGMA Vol 8 No 4 (2017): Desember 2017
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.182 KB) | DOI: 10.37366/sigma.v8i4.199

Abstract

Abstrak Teknologi hadir untuk memberikan kemudahan-kemudahan terhadap suatu permasalahan yang dihadapi oleh masyarakat. Salah satu kemudahan yang diberikan teknologi ini adalah kemudahan dalam proses penyediaan jasa, yaitu pada sistem Online. Yang sudah sering kita jumpai dalam berbagai bentuk toko Online. Pada penulisan ini, dibuatlah suatu sistem informasi laundry yang memudahkan pemilik laundry dalam melakukan pengecekan administrasi, mengingat banyak nya cabang yang dikelola. Dengan menggunakan sistem informasi berbasis web ini, diharapkan manpu menjadi salah satu solusi untuk membantu perusahaan dalam mengembangkan perusahaan dalam menghadapi persaingan bisnis di saat ini. Kata Kunci : Sistem, Informasi, Teknologi, Laundry.
Analisa Metode Hierarchical Clustering Dan K-Mean Dengan Model Lrfmp Pada Segmentasi Pelanggan Asep Muhidin
Jurnal SIGMA Vol 8 No 3 (2017): September 2017
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.984 KB) | DOI: 10.37366/sigma.v8i3.134

Abstract

Abstrak Pelanggan adalah sesuatu yang berharga dan penting, jika semua pelanggan serupa, bisnis akan begitu sederhana. Masalah heteroginitas dan banyaknya jumlah pelanggan menjadi tantangan yang harus dihadapi untuk menentukan segmentasi konsumen yang potensial.Pada penelitian ini proses segmentasi pelanggan dimulai dengan melakukan proses preprocessing, analytic hierarchy process (AHP),pencarian nilai K terbaik dari semua metode Hierarchical Clustering dengan membandingkan nilai Bouldien-Index. Selanjutnya nilai K terpilih dijadikan nilai awal pada K-Mean Clustering. Hasil clustering tersebut digunakan untuk melakukan segmentasi menggunakan model RFM untuk mendapatkan kelas konsumen. Penambahan parameter Payment (LRFMP) dapat meningkatkan nilai loyalitas pelanggan terhadap perusahaan.Berdasarkan hasil penelitian, metode single linkage merupakan metode terbaik untuk mencari nilai K. Segmentasi model k-mean dengan penambahan parameter P (LRFMP) dapat meningkatkan nilai DBI dibandingan dengan model RFM terbobot maupun tidak. Tetapi nilai DBI metode segmentasi single linkage masih lebih bagus dari pada segmentasi k-mean. Kata Kunci: Bouldien-Index, CRM, Data mining, pelanggan, LRFMP, RFM, segmentasi
Sistem Pendukung Keputusan Untuk Menentukan Kualitas Obat Baru Menggunakan Metode Naive Bayes Andri Firmansyah; Taufik Arifiyanto
Jurnal SIGMA Vol 9 No 3 (2019): Maret 2019
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Abstraksi Dalam menentukan jalannya produksi di sebuah pabrik tentuya harus diikuti dengan sistem yang memadai. Dalam tulisan ini akan diangun sebuah Sistem Pendukung Keputusan dalam penentukan kualitas obat baru di perusahaan menggunakan metode Naïve bayes karena metode ini dapat membantu dalam mengambil keputusan untuk menentukan Kualitas yang akan di produksi, akan tetapi perhitungannya hanya menghasilkan nilai terbesar yang akan terpilih sebagai alternatif yang terbaik. Sistem ini dibuat berbasis desktop dan dibangun dengan Bahasa pemrograman VB.net dan SQL Server sebagai databasenya. Kata Kunci: Sistem Pendukung Keputusan, Metode Naïve Bayes, Visual Basic, SQL Server
Transaksi Peminjaman & Pengembalian Buku Pada SMA 3 Cikarang Utara Menggunakan Barcode Dengan Metode Waterfall Suherman Suherman; Ramadhan Tirta
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Application of information technology has now spread almost in all areas is no exception in the library. The need for information technology is closely linked to the role of libraries as a force in the preservation and dissemination of scientific and cultural information. The service and archiving of books data in the library that is manual resulting in slow service and less accurate information of existing book data, toovercome the above problems it requires a library automation system that is able to provide services in library transactions are fast, accurate and efficient. The purpose of this library automation system is to optimize library services in providing services both in lending and return transactions, new book data inputs as well as in book search. The library automation system is created by utilizing barcode scanners as a tool to assist in the process of all transactions in the library. Keywords:Automation, barcode, library
Optimasi Metode Naïve Bayes Particle Swarm Optimization Analisis Sentimen Formula E Jakarta Pada Twitter Donny Maulana; Hasim Budi Jatmiko; Nanang Tedi Kurniadi
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The city of Jakarta plans to hold a Formula E racing event to promote electric cars as the vehicle of the future. The Covid-19 pandemic that hit Jakarta forced the plan to be postponed. The postponement caused a polemic in the community on social media due to the condition of Jakarta being hit by Covid-19 but the Jakarta city government still wants to hold Formula E by paying commitment money to the organizers which is not small. This difference of opinion on social media is used as material for sentiment analysis using the Naive Bayes classification method. The Naive Bayes method, which has a weakness in feature selection, is optimized by applying the Particle Swarm Optimization (PSO) feature selection. The results of the application of PSO optimization on the Naive Bayes method show an increase in performance with an accuracy value of 89.16%, precision 91.10%, recall 86.81% and AUC 0.690. Keywords: Naive Bayes, Particle Swarm Optimization, Sentiment Analysis, Jakarta E-Prix.
Penerapan Data Mining Untuk Analisa Kualitas Produk Welding Dengan Algoritma Naïve Bayes Dan C4.5 Pada PT. Karya Bahana Unigam Ismasari Nawangsih; Junisa Sahar
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

PT Karya Bahana Unigam is an automotive seat company, based on the results of testing the C.45 and Naïve Bayes algorithms which are used to produce classifications from data testing. The results of research or observations using different data with the same amount of data but having different attributes, labels and classes, the Naïve Bayes algorithm has optimal classification results because the levels of accuracy, precision and recall have an average of above 70% to 90%, because data in general can be categorized as good data because data has a complete number of attributes and classes and has information on each attribute, label and class in the data used so that it can provide information in improving quality at the testing stage of the C.45 algorithm. 96.00%, Precision 95.00% and Recall 79.17% while the Naïve Bayes accuracy algorithm is 99.33%, Precision 96.00% and Recall 100.00%. Keywords: Data Mining, C.45, Naïve Bayes
Sistem Informasi Rekam Medis Berbasis Web Dengan Framework Laravel Pada Klinik Restu Sehat Serang Baru Sanudin Sanudin; Agung Rahmawan; Arif Siswandi
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Restu Sehat Clinic is an institution that participates in providing comprehensive and integrated health services to the community in the South Serang Baru area. There are limitations in processing patient data and medical records. Medical record is a file that contains records and documents about the patient's identity, examination, treatment, actions, and services that have been provided to patients. The process of processing patient information at the Restu Sehat Clinic is still manual, which is recorded in a book which causes several obstacles to overcome this, result of this analysis is the need for an electronic medical record information system. The method used to build an electronic medical record information system is by using the prototype method, the design is carried out using UML (Unified Modeling Language) and coding the system using the PHP (Hypertext Preprocessor) programming language with the Laravel 8 Framework. With the existence of an electronic medical record information system, will make it easier to manage patient medical record data and reduce the risk of losing patient data. Keyword: Clinic, Medical Record, Prototype, UML, PHP, Laravel 8.
Prediksi Pengangkatan Karyawan Dengan Metode Klasifikasi Algoritma C5.0 (Studi Kasus CV. T-Pico Jaya Mandiri) Suprapto Suprapto; Fahrul Fahrezi J.T; Edora Edora
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

In the decision to appoint permanent employees that can be made at the company is determined in terms of attendance and good discipline. Determination of the appointment of permanent employees at CV. T-PICO JAYA MANDIRI still looks imprecise and takes a long time. Then a study was conducted that aims to determine the prediction information on permanent employee appointments by looking at the criteria set by the company using the C5.0 classification algorithm with the decision tree method. The data used in this study are employee data owned by CV. T-PICO JAYA MANDIRI as many as 403 data, the process of testing the method using Rapid Miner9.5. Based on the results of testing on research in predicting employee appointments at CV. T-PICO JAYA MANDIRI, obtained the result from the C5.0 algorithm or decision tree, which is an accuracy of 90.00%. So it can be concluded that the C5.0 algorithm technique with the decision tree method is considered successful in predicting employee appointments at CV. T- PICO JAYA MANDIRI. Keywords: Employee Recruitment, Classification, C5.0 Algorithm.
Penerapan Internet of Things (IoT) Pada Sistem Pengaman Pintu Menggunakan Modul Nodemcu ESP8266 Berbasis Telegram Endah Yaodah Kodratilah; Nur Sodik; U. Darmanto Soer
Jurnal SIGMA Vol 13 No 1 (2022): Maret 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Technological developments are carried out to support human needs to be more practical in life, one of which is in the household sector. This is the basis of this research. By using NodeMCU and Arduino Uno as microcontrollers for Smart Home systems with the IoT concept. With the creation of a Smart Home system with the IoT concept, it is hoped that the value of efficiency and security can be achieved at home. In this research, NodeMCU is implemented as a microcontroller in Smart Home system with IOT concept. This system is designed by using Telegram Messenger and keypad as input or notification media on this system. When inputting chat, the chat input data is read by the program for verification. If the verification is not successful then the system does not respond followed by reprogramming the chat input, if the verification is successful then the BOT will respond then send an input signal to the microcontroller for processing, after processing the microcontroller will send an output signal (On/Off) to be sent to the relay which will be forwarded to the output components (Solenoid Door lock, magnetic sensor, Buzzer). By implementing a Smart Home system with the IoT concept, we can take advantage of existing technology. The Smart Home system with the IoT concept is also safe because only people who have certain access can control the house such as unlocking the door and turning on the magnetic sensor remotely. Keywords: NodeMCU ESP8266, Arduino Uno, magnetic sensor, door solenoid, relay, power supply, buzzer, telegram and arduinoIDE

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