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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Tekinkom (Teknik Informasi dan Komputer) JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat)
B Herawan Hayadi
Universitas Potensi Utama
Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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IoT Framework Current Trends and Recent Advances to Management Company in The PT.TNC Teddy Surya Gunawan; B Herawan Hayadi; Cindy Paramitha; Muhammad Sadikin
JUDIMAS Vol 1, No 2 (2020): JUDIMAS
Publisher : STMIK Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/jm.v1i2.1104

Abstract

The Internet of Things (IoT) is a fast growing and user-friendly technology that connects everything together. And it can communicate effectively between the people who connect "Things." Internet of Things, also known as Internet of Objects, usually refers to remote systems between projects. Systems will be remote and self-designable. However, the world's largest information technology companies tend to release products in the form of services to avoid disclosing detailed design and implementation knowledge. Hence, the overall trend of academic institutions is to use these mainstream IoT platforms as "black boxes". IoT is something that is useful as a sensor, computer architecture, software, security, packaging, technology selection based on the amount of data, as far as data is needed, whatever power you have. Fundamental way to collect and store data Thing: SQL, noSQL, and time series databases Machine learning algorithms with outputs: regression, classification, anomaly detection. Improve service quality, reduce service costs New models (precision services), Reduce consumption costs of higher quality products or services, Improve health and safety.
PERBANDINGAN AKURASI ALGORITMA NAÏVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI Novendra Adisaputra Sinaga; B Herawan Hayadi; Zakarias Situmorang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.446

Abstract

To supporting academic and non-academic activities, the Polytechnic Business Indonesian (PBI) must be supported by employees with reliable Human Resources (HRD) who have good behavior, good abilities and can complete work professionally and responsibly. Conventional techniques for analyzing existing large amounts of data cannot be handled which is the background for the emergence of a new branch of science to overcome the problem of extracting important information from data sets, which is called Data Mining. Utilizing methods to classify data by utilizing methods including: Naïve Bayes method, K-Nearest Neighbor (K-NN) and Supervise Vector Machine (SVM). From this research, in Predicting Applicants Graduation at PBI, the SVM method is better than Naïve Bayes and K-NN. With 33 test data used, SVM has 84.9% accuracy, 85.1% precision while K-NN has 81.8% accuracy, 84.1% precision and Naïve Bayes has 78.8% accuracy and 80.1% precision.
PENERAPAN METODE K-NEARST NEIGHBOR UNTUK MENGIDENTIFIKASI KELAYAKAN PENERIMA KREDIT INVESTASI Sartika Mandasari; B Herawan Hayadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 3 (2022): October 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i3.1017

Abstract

Sistem pengidentifikassian kelayakan penerima kredit investasi pada BPD Bank Aceh terhadap para penerimanya masih dilakukan secara manual pada setiap prosesnya, yang terdiri dari proses mengajuan, penyeleksian berkas, wawancara, pengobservasian terhadap calon Nasabah masih dilakukan secara manual.Untuk dapat mengatasi permasalahan yang ada, maka dibuatlah suatu sistem pengelompokan pengidentifikasian penerima Kredit Investasi dengan data mining menggunakan metode K-Nearest Neighbor untuk mengidentifikasi objek atau individu yang serupa dengan memperhatikan beberapa kriteria. Dengan demikian hasil pengelompokan yang telah dirancang dapat membantu pihak BPD Bank Aceh dalam proses penidentifikasian penerima Kredit Investasinya berdasarkan kriteria yang sudah ditentukan sehingga pengelompokan dan pengambilan keputusan dapat dilakukan secara lebih cepat,tepat, dan akurat serta terhindar dari kesalahan.
PENGAMANAN DATA PENJUALAN DENGAN KRIPTOGRAFI ALGORITMA RIVEST SHAMIR ADLEMAN (RSA) PAD A TOKO BAJU FAMILY Karina Andriani; B Herawan Hayadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 5, No 3 (2022): October 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v5i3.1018

Abstract

Perkembangan teknologi komputer pada saat ini memberikan dampak yang besar dalam penyampaian informasi, sedangkan keamanan data menjadi salah satu apek yang sangat penting dalam sistem informasi saat ini. Toko baju family menggunakan teknologi komputer dalam melakukan proses transaksi penjualan sehingga setiap transaksi yang dilakukan tersimpan dalam bentuk data penjualan. Pada permasalahan yang dibahas, dengan menerapkan Perancangan Aplikasi Keamanan Data salah satunya dengan menggunakan algoritma RSA (Rivest Shamir Adleman) dalam mengamankan data penjualan. Dengan mengamankan data penjualan bertujuan untuk membantu pegawai dalam mengamankan data penjualannya. Hasil penelitian merupakan terciptanya sebuah aplikasi Pengamanan Data dengan Algoritma RSA (Rivest Shamir Adleman) yang dapat membantu pegawai dalam mengamankan data penjualan yang berada pada Toko Baju Family.
Co-Authors Cindy Paramitha Karina Andriani Muhammad Sadikin Novendra Adisaputra Sinaga Sartika Mandasari Teddy Surya Gunawan Zakarias Situmorang