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All Journal E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) Proceeding of the Electrical Engineering Computer Science and Informatics Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Teknik Komputer AMIK BSI Paradigma JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Sains dan Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Informatika Universitas Pamulang Jurnal Teknoinfo Infoman's: Jurnal Ilmu-Ilmu Manajeman dan Informatika METIK JURNAL Jurnal Pengabdian Masyarakat Tekno

Windu Gata

STMIK Nusa Mandiri

Author-ID : 2438002

Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Mathematics Social Sciences

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Penerapan Algoritma Kriptografi TEA Dan Base64 Untuk Mengamankan Email Data Policy Asuransi Siswanto Siswanto; Muhammad Anif; Windu Gata
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 2 No. 1 (2018)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v2i1.44

Aplikasi pengamanan data ini dirancang untuk mengamankan email data penting pada PT. Dekai Indonesia terutama data policy yang berisi data pribadi para nasabah. Karena banyaknya data penting para nasabah maka keamanan data tersebut menjadi sangat rentan terhadap pencurian dan manipulasi data dari berbagai pihak yang tidak bertanggung jawab mengingat sering juga data tersebut dikirimkan menggunakan fasilitas email. Dengan banyaknya data penting yang sering juga bersifat rahasia tersebut, maka data tersebut menjadi rentan dengan pencurian data, manipulasi data atau penyadapan email. Permasalahan tersebut dapat dihadapi demgan membuat aplikasi untuk mencegah pihak yang tidak bertanggung jawab dapat membaca isi file dari data transaksi. Juga menjamin keaslian data sensitif dan penting hanya dapat diterima dan dibaca oleh orang-orang yang berhak mendapatkan data. Dalam penulisan ini algoritma yang digunakan dalam kriptografi, yaitu algoritma kriptografi TEA (Tiny Encryption Algorithm). Penggunaan sistem kriptografi ini dimaksudkan agar data tersebut tidak mudah dibobol. Bahasa pemrograman yang digunakan dalam membangun aplikasi pengamanan data ini adalah bahasa pemrograman PHP yang berbasis web. Hasil dari pengujian kriptografi ini, data dapat diamankan untuk menghindari serangan cryptanalysis. Rata-rata ukuran file yang telah melalui proses encrypt bertambah sekitar 33,29512 persen dari ukuran asli file sebelum melalui proses encrypt. Rata-rata perubahan ukuran file yang telah melalui proses decrypt akan berkurang sebesar 25.0231 persen.

Penerapan Konsep Finite State Automata Pada Aplikasi Simulasi Vending Machine Jamu Tradisional Erni Erni; Fakihotun Titiani; Sukmawati Anggraeni Putri; Windu Gata
Jurnal Informatika Vol 7, No 2 (2020): September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Otomata adalah mesin abstrak yang dapat mengenali, menerima, atau me’mbangkitkan sebuah kalimat dalam bahasa tertentu yang di dalamnya terdapat sebuah kajian tentang Finite State Automata yang dapat diimplementasikan dalam rancangan sebuah Vending Machine. Vending Machine di Indonesia banyak beroperasi dengan produk seperti makanan ringan, minuman, rokok, tiket, kopi, produk konsumen, bahkan emas. Dalam penelitian ini, akan diuraikan mengenai aplikasi simulasi Vending Machine jamu tradisional, berdasarkan implementasi Finite State Automata. Kesimpulan yang didapat dalam penelitian ini yaitu Finite State Automata dapat dijadikan sebagai logika dasar untuk membuat simulasi Vending Machine. Penelitian ini juga mengusulkan penggunaan state yang lebih sedikit, penggunaan uang kertas sebagai input dan kembalian untuk meningkatkan efisiensi dan biaya desain Vending Machine.

Perancangan Sistem Pakar Penentuan Jenis Kulit Wajah Menggunakan Metode Certainty Factor Rangga Pebrianto; Siti Nurhasanah Nugraha; Windu Gata
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 5, No 1 (2020): Mei 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Abstrak - Wajah adalah bagian tubuh terpenting yang harus selalu dijaga dan dirawat. Sehingga banyak cara merawat wajah yang dilakukan untuk mendapatkan wajah putih, bersih, dan terbebas dari jerawat. Pengetahuan analisa kulit wajah sangat diperlukan untuk menentukan jenis kulit serta produk perawatan yang sesuai dengan jenis kulit. Sistem pakar merupakan sistem yang mengadopsi pengetahuan dari seorang pakar dan dapat berperan layaknya seorang pakar dalam menangani proses konsultasi. Tujuan dari penelitian ini yaitu merancang sebuah sistem pakar yang dapat menentukan jenis kulit wajah berbasis android dengan menerapkan metode certainty factor dalam proses penghitungan derajat tingkat keyakinan. Dengan aplikasi sistem pakar berbasis android ini konsultan dapat melakukan pemeriksaan dengan mudah, dan pendiagnosaan sekaligus solusi dapat terselesaikan secara cepat dan tepat berdasarkan data yang diinputkan.Katakunci: Android, Certainty Factor, Perancangan Sistem PakarAbstract - Face is the most important body part that should always be kept and cared for. So many ways of taking care of the face are done to get the face of white, clean, and free of acne. The knowledge of facial skin analysis is necessary to determine the skin type as well as care products that suit the skin type. The expert system is a system that adopts the knowledge of an expert and can play like an expert in handling the consultation process. The purpose of this research is to design an expert system that can determine the type of Android-based facial skin by applying the certainty factor method in the process of counting degrees of confidence. With this Android-based expert System Application consultants can perform inspections with ease, and the solution can be easily resolved quickly and precisely based on the data being inputed.Keywords: Android, Certainty Factor, Expert System Design

CLUSTERING PENCAPAIAN TARGET PENJUALAN RUMAH PARA KARYAWAN MARKETING MENGGUNAKAN RAPID MINER DAN ALGORITMA K-MEANS Muhammad Fahmi Julianto; Sofian Wira Hadi; Setiaji Setiaji; Windu Gata; Rangga Pebrianto
Bianglala Informatika Vol 8, No 2 (2020): Bianglala Informatika 2020
Publisher : LPPM Universitas Bina Sarana Informatika

In the competition of the business world today, we are required to always develop business in order to always be successful in competition. Fachry PropertyLand is one of the business fields engaged in the sale of homes. Everywhere this shop must meet the needs of customers who are currently trending. On Land Fachry Property Around the issue that always appears regarding sales. Where many employees do not meet their sales targets. Based on this, it is expected to facilitate the Land Fachry Property in assessing the appropriateness of its employees in determining employees who have met the target, has not met the target and does not meet the target, in the grouping process, the grouping method will be used using the K-Me Clustering Algorithm as a method of manual replacement and in its implementation the Data Mining software uses RapidMiner Studio version 9.2. With the application of Rapid Miner Studio, it is expected that the owner of Fachry Propertyland can see the results of the grouping that meets the target, does not meet the target and does not meet the target. It is expected that the owner of Fachry Propertyland can take action on these employees.

Adopsi Algoritme Support Vector Machine untuk Analisis Sentimen Larangan Mudik Lebaran 2020 pada Twitter Rangga Pebrianto; Tri Rivanie; Ridan Nurfalah; Windu Gata; Muhammad Fahmi Julianto
JURNAL TEKNIK KOMPUTER Vol 6, No 2 (2020): JTK-Periode Juli 2020
Publisher : Universitas Bina Sarana Informatika

Pemerintah kembali membahas larangan mudik lebaran 2020. Larangan mudik lebaran 2020 ini kembali di bahas karena jumlah kasus corona atau covid 19 di indonesia terus bertambah. Media Sosial Twitter bekerja real-time, memungkinkan pengguna mengekspresikan opini dan perasaan mereka mengenai banyak isu atau permasalahan, Opini tersebut dapat dimanfaatkan sebagai bahan analisis sentimen untuk mengetahui penilaian pelayanan transportasi umum darat apakah positif atau negatif, serta mengetahui faktor opini apa yang sering muncul. Hasil dari analisis sentimen tersebut dapat membantu dalam penilaian dan evaluasi terhadap larangan mudik 2020 ditengah wabah covid19 diharapkan dapat menjadi bahan pertimbangan pemerintah dalam mengambil keputusan terkait larangan mudik 2020 di tengah wabah covid19 . adopsi Metode Support Vector Machine (SVM) untuk analisis sentimen dilakukan dengan pengujian terhadap komposisi data yang bervariasi. Dari hasil pengujian untuk kasus pada penelitian ini didapatkan bahwa SVM dapat diimplementasikan dengan nilai akurasi mencapai 68,89%. Variabel yang berpengaruh terhadap akurasi adalah jumlah data, perbandingan jumlah data latih dan uji, serta perbandingan jumlah data positif dan negatif yang digunakan.

Perancangan Validasi Permohonan Narasumber Pada Sistem Informasi Permohonan Narasumber Menggunakan Finite State Automata Fadillah Said; Dwi Andriyanto; Retno Sari; Windu Gata
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

The Law and Human Rights Research and Development Agency in carrying out its duties and functions provides services in the form of Providing Resource persons. Managing mail manually requires a long time and allows for document loss. This study aims to reduce the use of time, help minimize the loss of letters, and reduce errors in recording letters by storing them in a database in accordance with the specified format. In the design of the system will check the applicant's input and validate before the data is stored in the database using Finite State Automata (FSA) so that the data stored in accordance with the format specified. The implementation of this research is expected to be able to help the Law and Human Rights Research and Development Agency to reduce the use of time, help minimize the loss of letters, and reduce errors in recording letters in accordance with the specified format.

PENERAPAN ALGORITMA J48 UNTUK DETEKSI PENYAKIT TIROID Sarifah Agustiani; Ali Mustopa; Andi Saryoko; Windu Gata; Siti Khotimatul Wildah
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Impaired thyroid function is often difficult to identify because the symptoms are not specific. The symptoms of thyroid disorder are very similar to various complaints due to modern lifestyles so it is often overlooked. As a result, patients often do not notice a problem and do not have to consult a doctor. Therefore, there is a study that implements methods to predict the disease which will facilitate the patient in diagnosing and early detection of thyroid levels. This research aims to predict against thyroid disease with the data used is the secondary data obtained from the UCI repository, this data is about the patient data affected by thyroid disease, while the method uses the J48 algorithm because in some studies, the J48 algorithm is proven to have good performance in detecting an illness, as well as producing high value of Accuasy and AUC. The stage of data analysis is based on the CRISP-DM method while algorithm testing is done with Weka tools. Results of the test obtained an accuracy value of 99.645%, and a AUC value of 0.992 thus the accuracy has Excellent Classification level.

Algorithm Implementation Of Interest Buy Apriori Data On Consumer Retail Sales In Industry Ahmad Fachrurozi; Mufid Junaedi; Jordy Lasmana Putra; Windu Gata
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

This data processing has the aim to increase the company's turnover, because by being aware of how the interest in buying goods works, the company can buy products other than the main products that it buys. In increasing company revenue can be done using the Data Mining process, one of which uses a priori algorithm and association techniques. With this a priori algorithm found association technique which later can be used as a pattern of purchasing goods by consumers, this study uses a data repository of 958 data consisting of 45 transactions. From the results obtained goods with the name Paper Chain Kit 50's Christmas is a product that is often bought by consumers and it is known that the most frequent combination patterns are the Retro Spot Paper Chain Kit and the Paper Chain Kit 50's Christmas. So that with known buying patterns, the company manager can predict future market needs, and can calculate the stock of goods that must be reproduced, and goods whose stock must be reduced, and also with the results of the association the manager can manage the layout of the product to be better.Keywords: Apriori Algorithm, Sales Data, Retail.

Analisis Sentimen Zoom Cloud Meetings di Play Store Menggunakan Naïve Bayes dan Support Vector Machine Nuraeni Herlinawati; Yuri Yuliani; Siti Faizah; Windu Gata; Samudi Samudi
CESS (Journal of Computer Engineering, System and Science) Vol 5, No 2 (2020): JULI 2020
Publisher : Universitas Negeri Medan

Aplikasi zoom cloud meetings yang mulai booming digunakan sekarang ini karena adanya pandemi virus corona, sehingga membuat semua kegiatan dilakukan secara virtual. Zoom cloud meetings merupakan aplikasi yang memiliki berbagai fitur termasuk video & audio conference. Pada penelitian ini penulis menggunakan metode Naïve Bayes dan Support Vector Machine dalam menganalisa label sentimen positif atau negatif pada ulasan para pengguna aplikasi zoom di Google Play Store. Jumlah dataset setelah prepocessing menjadi 1.007 record. Data hampir seimbang dengan label positif sebanyak 546 dan label negatif 461 ulasan. Evaluasi model menggunakan 10 fold cross validation diperoleh nilai akurasi dan nilai AUC dari masing-masing algoritma yaitu untuk NB nilai akurasi = 74,37% dan nilai AUC = 0,659. Sedangkan untuk algoritma SVM nilai akurasi = 81,22% dan nilai AUC = 0,886. Dalam penelitian ini dapat diketahui bahwa tingkat akurasi yang didapatkan algoritma Support Vector Machine (SVM) lebih unggul 6,85% dibandingkan algoritma Naïve Bayes (NB). Kata Kunci— Zoom Cloud Meetings, Google Play Store, Virus Corona, Naïve Bayes, Support Vector Machine. Abstract— Zoom cloud meetings application that began to boom is used today because of the corona virus pandemic, so that all activities are carried out virtually. Zoom cloud meetings is an application that has various features including video & audio conferencing. In this study the authors used the Naïve Bayes method and Support Vector Machine in analyzing positive or negative sentiment labels on the zoom users' reviews on the Google Play Store. The number of datasets after prepocessing is 1,007 records. The data is almost balanced with 546 positive labels and 461 negative labels. Evaluation of the model using 10 fold cross validation obtained accuracy values and AUC values from each algorithm, namely for NB, the accuracy value = 74.37% and the AUC value = 0.659. As for the SVM algorithm the accuracy value = 81.22% and the AUC value = 0.886. In this study it can be seen that the accuracy obtained by the Support Vector Machine (SVM) algorithm is 6.85% superior to the Naïve Bayes (NB) algorithm.

The Feasibility of Credit Using C4.5 Algorithm Based on Particle Swarm Optimization Prediction Siswanto Siswanto; Abdussomad Abdussomad; Windu Gata; Nia Kusuma Wardhani; Grace Gata; Basuki Hari Prasetyo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2019

Credit is a belief that one is given to a person or other entity which is concerned in the future will fulfill all the obligations previously agreed. The objective of research is necessary to do credit analysis to determine the feasibility of a credit crunch, through credit analysis results, it can be seen whether the customer is feasible or not. The methods are is used to predict credit worthiness is by using two models, models classification algorithm C4.5 and C4.5 classification algorithm model based Particle Swarm Optimization (PSO). After testing with these two models found that the result C4.5 classification algorithm generates a value of 90.99% accuracy and AUC value of 0.911 to the level diagnostics Classification Excellent, but after the optimization with C4.5 classification algorithm based on Particle Swarm Optimization accuracy values amounted to 91.18% and the AUC value of 0.913 to the level of diagnosis Excellent Classification. These both methods have different accuracy level of 0.18%.

Co-Authors Abdul Hamid Abdul Latif Abdul Latif Abdussomad Abdussomad Achmad Maezar Bayu Aji Achmad Rifai Ade Irma Rizmayanti Agustiani, Sarifah Ahmad Fachrurozi Akrom, Akrom Ali Mustopa, Ali Andi Saryoko Angelina Puput Giovani Ardiansyah Ardiansyah Ardiansyah Arifin Nugroho Atik Budi Paryanti Basri Basri Chintamia Bunga Sari Dewi Cucu Ika Agustyaningrum Dedi Priansyah Deni Anugrah Sahputra Deni Gunawan Didi Rosiyadi Didi Rosiyadi Dwi Andriyanto Erni Erni Fadillah Said Fajar Pramono Fakihotun Titiani Fariszal Nova Arviantino Grace Gata, Grace Hafez Aditya Hiya Nalatissifa Ikin Rojikin Imam Santoso Ipin Sugiyarto Irwan Herliawan Istiqal Hadi Jajang jaya Purnama Jordy Lasmana Putra Kartika Handayani Khoirun Nisa Laela Kurniawati Lilyani Asri Utami, Lilyani Asri M. Anif M. Rangga Ramadhan Saelan Mawadatul Maulidah Mufid Junaedi Muhammad Fahmi Julianto Muhammad Fahmi Julianto Muhammad Iqbal Muhammad Iqbal Muhammad Rifqi Firdaus Muhammad Rifqi Firdaus Nadiyah Hidayati Nia Kusuma Wardhani Nuraeni Herlinawati Nurlaelatul Maulidah Prasetyo, Basuki Hari Rangga Pebrianto Ranu Agastya Nugraha Rendi Septian Retno Sari Rhini Fatmasari Ridan Nurfalah Ridwansyah Ridwansyah Riefky Sungkar Riki Supriyadi Risnandar, Risnandar Rizki Aulianita Safitri Linawati Saifurrachman Chohan Samudi Samudi Saputro, Ari Setiaji Setiaji Sidik Sidik Siswanto Siswanto Siswanto, Siswanto Siti Faizah Siti Khotimatul Wildah Siti Nurhasanah Nugraha Sofian Wira Hadi Sri Diantika Sri Rahayu Subandi Sukmawati Anggraeni Putri Sukri Syafrudin Suwanda Aditya Aaputra Syaifur Rahmatullah Syepry Maulana Husain Tri Rivanie Tuti Haryanti Wawan Kurniawan Widiastuti Widiastuti Yudhistira Yudhistira Yuliani, Yuri Yuliazmi Yusuf Arif Setiawan

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