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All Journal Jurnal Simantec SMATIKA Network Engineering Research Operation [NERO] Kurawal - Jurnal Teknologi, Informasi dan Industri
Paulus Lucky Tirma Irawan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Other

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RANCANG BANGUN GAME EDUKASI UNTUK PENGENALAN DASAR LOGIKA ALGORITMA BERBASIS MOBILE Paulus Lucky Tirma Irawan; Felix Tandiono; Hendry Setiawan
Network Engineering Research Operation Vol 3, No 3 (2018): NERO
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v3i3.88

Abstract

IMPLEMENTASI TEXT MINING UNTUK ANALISIS OPINI MASYARAKAT TERHADAP KINERJA LAYANAN TRANSPORTASI ONLINE DENGAN ANALISIS FAKTOR Immanuel Olive DjajaPutra; Kestrilia Rega Prilianti; Paulus Lucky Tirma Irawan
Jurnal Simantec Vol 8, No 2 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v8i2.6764

Abstract

Sistem transportasi umum saat ini berbasis aplikasi yang terhubung dengan koneksi internet sehingga dapat disebut juga dengan transportasi online. Grab dan Gojek merupakan penyedia jasa transportasi online yang ingin memberikan pelayanan kepada pengguna dengan baik. Beberapa pengguna memberikan tanggapan tentang layanan yang diberikan, pengalaman, kritik maupun saran bagi kedua perusahaan tersebut melalui Twitter. Pada penelitian ini dibuat sebuah aplikasi untuk menganalisis opini masyarakat terhadap layanan Grab dan Gojek dengan implementasi text mining menggunakan algoritma Naïve Bayes Classifier yang digunakan untuk mengklasifikasi tweet ke dalam kelas sentimen positif atau sentimen negatif dan Principal Component Analysis (PCA) yang digunakan untuk menentukan faktor dari setiap sentimen yang telah divalidasi. Data diperoleh melalui Twitter dengan kata kunci “grab” Dan “gojek”. Dari hasil penelitian didapatkan hasil akurasi klasifikasi data uji sentimen pada objek Grab adalah 74,34% dengan jumlah data 152 tweet dan data latih 597 tweet, sedangkan hasil akurasi klasifikasi data uji pada objek Gojek adalah 68,84% dengan jumlah data 565 tweet dan data latih 2249 tweet. Hasil akurasi diperoleh dengan menggunakan nilai threshold sebesar 1.1. Setiap kelas sentimen dilakukan analisis faktor yang kemudian pada Grab diperoleh 6 faktor positif dan 5 faktor negatif, sedangkan pada Gojek diperoleh 8 faktor positif dan 6 faktor negatif. Setiap faktor yang diperoleh dilakukan interpretasi dan kemudian dilakukan validasi oleh pakar.
Rancang Bangun Sistem Otomasi Monitoring Level Air Bendungan Untuk Pengendalian Banjir subianto subianto; Paulus Lucky Tirma Irawan; Shenata Hanadam Shienjaya
SMATIKA JURNAL Vol 9 No 01 (2019): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (394.504 KB) | DOI: 10.32664/smatika.v9i01.247

Abstract

Along with the development of technology the problems that have never been separated from Indonesian society in general are floods. Flooding is a natural phenomenon that occurs because of the overflow of water in sewers, rivers or lakes that cannot accommodate water discharge. Floods occur because of the delay in the officers opening the floodgate. The lack of current dam supervisors has resulted in the monitoring of dams not being able to be carried out maximally, this has caused flooding due to the delay in setting the floodgates. In this study the author designed a dam water level monitoring automation system for flood control. The device used is the Raspberry Pi as a device that receives water level height data taken by the HC-SR04 ultrasonic sensor. The results of the ultrasonic sensor test get an average of the calculation of MSE (Mean Square Error) is 0.35 cm which is getting closer to the value of 0 indicates that the results of the accuracy of the ultrasonic sensor can be said to be accurate, the average error of 4,71% the sensor shows accuracy that very good with a deviation of 5.16% which is close to the average error, the range of data from the test results is quite accurate
Rancang Bangun Sistem E-commerce Clothing Store dan Modul Custom Design Lab Terintegrasi paulus lucky tirma irawan; David Rozando
SMATIKA JURNAL Vol 10 No 01 (2020): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v10i02.397

Abstract

The current ease of internet access and convenience in developing website E-commerce is a great alternative for business through The internet. Online clothing stores are one type of E-commerce business that has sprung up in the internet world today. The application of E-commerce in this business can handle the trading process which consists of the order, purchase, payment, and shipping process. Order customization of ordered goods is also one of the added values ​​that can be offered to prospective customers. The existence of a module called the Custom Design Lab can be a solution to this condition. This module in its implementation will be integrated with the existing E-commerce system so that the existing trading process also applies to the preorder system. The development of this E-commerce website uses the PyroCMS framework as a basic application by configuring several modules. The main focus of this research is to produce an E-commerce site that has represented the online business process in general and also has a Custom Design Lab feature for product order customization.
Analisis Fitur-Fitur Yang Mempengaruhi Jumlah Subscribers Youtube Menggunakan Algoritma Naive Bayes Classifier Meliyana Rahayu Yoanita; Hendry Setiawan; Paulus Lucky Tirma Irawan
SMATIKA JURNAL Vol 10 No 01 (2020): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v10i01.446

Abstract

One of them is technology in the field of communication is a social media platform. Social media Youtube is one of the most widely used social media in Indonesia. The benefits gained by Content Creators or Youtubers come from AdSense. Youtube has several features provided such as likes, dislikes, views and comments (comments with negative or positive sentiments). An automatic classification system for YouTube comment sentiment is needed to classify positive comments and negative comments, while analyzing features that affect the number of subscribers so that Content Creators can find out features that can affect the number of subscribers. In this research a comment sentiment classification system will automatically be created using the Naive Bayes (NB) algorithm so that the process of classifying positive and negative comments can be done easily, the data used in the analysis are 53 Youtube channels with vlog video types. In addition, the data used as classification training data were 4166 positive sentiments and 4166 negative sentiments, after which an analysis of features affecting the number of subscribers was performed using chi square. The results of the analysis with chi square found there are 4 features that have an influence on the number of subscribers, namely the number of views with a chi square value of 23,105, dislike with a chi square value of 13,745, the number of positive sentiment comments with a chi square value of 18,123 and the number of likes with a chi square value of 13,745. The accuracy of the automatic classification system using Naive Bayes (NB) is 81%.
RANCANG BANGUN APLIKASI REKOMENDASI PARSEL MENGGUNAKAN DIFFERENTIAL EVOLUTION Fika Handani; Hendry Setiawan; Paulus Lucky Tirma Irawan
Kurawal - Jurnal Teknologi, Informasi dan Industri Vol 2 No 2 (2019): Jurnal Kurawal Volume 2, Nomor 2, Oktober 2019
Publisher : Universitas Ma Chung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33479/kurawal.2019.2.2.171-181

Abstract

Knapsack Problem adalah permasalahan dimana seseorang dihadapkan pada optimasi pemilihan objek yang dimasukan kedalam wadah dengan kapasitas terbatas. Rekomendasi untuk memilih barang berdasarkan kategori dan jenis adalah salah satu hal yang termasuk dalam kategori knapsack problem. Mulia Jaya Minimarket adalah salah satu supermarket yang melayani pesanan parsel. Masalah yang sering terjadi adalah kurangnya variasi untuk menentukan kombinasi item pada parsel. Maka dibutuhkan aplikasi yang dapat membantu memberikan rekomendasi parsel secara otomatis. Aplikasi ini dibuat dengan menerapkan algoritma differential evolution. Solusi untuk rekomendasi diimplementasikan dalam bentuk vector. Setiap vector akan dihitung menggunakan nilai fitness dengan mempertimbangkan kualitas dan budget yang diberikan. Proses ini akan dihentikan ketika telah mendapatkan vector terbaik dengan Batasan iterasi tertentu. Hasil uji coba menunjukan bahwa aplikasi ini memiliki tingkat akurasi budget sebesar 0,99820 dan rata-rata nilai fitness terbaik 0,99501 dengan nilai crossover sebesar 50.
Co-Authors David Rozando Felix Tandiono Fika Handani Hendry Setiawan Immanuel Olive DjajaPutra Kestrilia Rega Prilianti Meliyana Rahayu Yoanita Mochamad Subianto Setiawan, Hendry Shenata Hanadam Shienjaya