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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) INFORMAL: Informatics Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Techno Nusa Mandiri : Journal of Computing and Information Technology ILKOM Jurnal Ilmiah INFOKUM Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) jeti TECHSI - Jurnal Teknik Informatika Scientific Journal of Informatics
Novia Hasdyna
Universitas Islam Kebangsaan Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Analisis Matthew Correlation Coefficient pada K-Nearest Neighbor dalam Klasifikasi Ikan Hias Novia Hasdyna; Rozzi Kesuma Dinata
INFORMAL: Informatics Journal Vol 5 No 2 (2020): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v5i2.18907

Abstract

K-Nearest Neighbor (K-NN) is a machine learning algorithm that functions to classify data. This study aims to measure the performance of K-NN algorithm by using Matthew Correlation Coefficient (MCC). The data that used in this study are the ornamental fish which consisting of 3 classes named Premium, Medium, and Low. The analysis results of the Matthew Correlation Coefficient on K-NN using Euclidean Distance obtained the highest MCC value in Medium class which is 0.786542. The second highest MCC value is in Premium class which is 0.567434. The lowest MCC value is in Low class which is 0.435269. Overall, the MCC values is statistically which is 0,596415.
Algoritma Brute Force dalam Sistem Informasi Lowongan Kerja Berbasis Web Di Kota Lhokseumawe Novia Hasdyna, Ikhlasul Amal
Jurnal Elektro dan Informatika Vol 2 No 1 (2021): Maret 2021
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v2i1.163

Abstract

In looking for job vacancies in the city of Lhokseumawe, applicants usually still use conventional methods, namely byvisiting the company to see the bulletin board, or viewing information from newspapers and other print media. In thisstudy, the author discusses the application of technology to be able to help facilitate job seekers in obtaining informationon job vacancies in the web-based city of Lhokseumawe using brute force algorithm.
Weighted Product dalam Sistem Rekomendasi Pemilihan Karyawan Berbasis Web Muazir, Novia Hasdyna, Rahmat
Jurnal Elektro dan Informatika Vol 2 No 2 (2021): September 2021
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v2i2.187

Abstract

An employee selection recommendation system is needed in selecting the best employees. This study uses the Weighted Product method in the recommendation system. The data used is employee data at the Sejahtera Swalayan Lhokseumawe. Based on the analysis carried out, the results of this study show that the ranking of the best employees is Nasir in the first place with a vector V value of 0.081657618, Alfian in second place with a V vector value of 0.077227007 and Muhibuddin in third place with a V vector value of 0.07372706. The system is built based on the web using the PHP programming language.
K-means algorithm for clustering system of plant seeds specialization areas in east Aceh Rozzi Kesuma Dinata; Novia Hasdyna; Sujacka Retno; Muhammad Nurfahmi
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.863.235-243

Abstract

The number of regions and types of plants in East Aceh Regency requires a data clustering process in order to easily find out which areas are most in-demand based on the type of plants. This study applies the k-means algorithm to classify the data. The data used in this study were obtained from the Department of Agriculture, Food Crops and Horticulture, East Aceh Regency. Based on the test results with k-means, the average number of iterations in the 2015-2019 data is 8,7,6,4,3 iterations for each commodity. The test results can show areas of interest for plant seeds with clusters of high demand, attractive, and less desirable. The system in this study was built based on the web using the PHP programming language.
Algoritma K-Nearest Neighbor dengan Euclidean Distance dan Manhattan Distance untuk Klasifikasi Transportasi Bus Rozzi Kesuma Dinata; Hafizal Akbar; Novia Hasdyna
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.539.104-111

Abstract

K-Nearest Neighbor is a data mining algorithm that can be used to classify data. K-Nearest Neighbor works based on the closest distance. This research using the Euclidean and Manhattan distances to calculate the distance of Lhokseumawe-Medan bus transportation. Data that used in this research was obtained from the Organisasi Angkutan Darat Kota Lhokseumawe. The results of the test with k = 3 has obtained the percentage of 44.94% for Precision, 37.06% Recall, and 81.96% Accuracy for the performance of K-NN with Euclidean Distance. Whereas by using Manhattan Distance the result obtained was 45.49% for Precision, 36.39% Recall, and 84.00% Accuracy. The result shown that Manhattan Distance obtained the highest accuracy, with the difference of 2.04% higher than Euclidean Distance. It indicates that Manhattan Distance is more accurate than Euclidean Distance to classify the bus transportation.
ANALISIS KINERJA ALGORITMA HONEY ENCRYPTION DAN ALGORITMA BLOWFISH PADA PROSES ENKRIPSI DAN DEKRIPSI Sujacka Retno; Novia Hasdyna
TECHSI - Jurnal Teknik Informatika Vol 10, No 2 (2018)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v10i2.858

Abstract

Algoritma Honey Encryption dan algoritma Blowfish merupakan dua buah algoritma kriptografi yang dapat digunakan dalam proses enkripsi dan dekripsi. Honey Encryption merupakan salah satu algoritma yang masih baru  dalam ilmu kriptografi, untuk itu perlu dilakukan analisis  kinerja algoritma tersebut pada proses enkripsi dan dekripsi. Berdasarkan studi perbandingan yang telah dilakukan diperoleh hasil bahwa jika ditinjau proses enkripsi dan dekripsinya, algoritma Honey Encryption jauh lebih efektif dan efisien dibandingkan dengan algoritma Blowfish dari segi keamanan dan tingkat kompleksitas enkripsi dan dekripsinya. 
IMPLEMENTASI METODE CUSUM (CUMMULATIVE SUMMARY) UNTUK MENENTUKAN DAERAH RAWAN KECELAKAAN BERBASIS WEB DI KOTA LHOKSEUMAWE Novia Hasdina; Rizal Rizal
TECHSI - Jurnal Teknik Informatika Vol 8, No 1 (2016)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v8i1.129

Abstract

Pada Unit Laka Lantas Polres Lhokseumawe penentuan daerah rawan kecelakaan pada ruas jalan di Kota Lhokseumawe masih menggunakan sistem manual. Penentuan daerah rawan kecelakaan kurang efektif dikarenakan polisi bagian  Unit Laka Lantas Polres Lhokseumawe  hanya menggunakan data satu tahun terakhir dan harus berulang kali menghitung secara manual daerah rawan kecelakaan berdasarkan jumlah korban manusia. Dalam penelitian ini sistem Implementasi Metode Cusum (Cummulative Summary) untuk menentukan daerah rawan kecelakaan dirancang berbasis web dengan menggunakan bahasa pemrograman PHP.  Pada sistem ini terdapat tiga proses untuk menentukan daerah rawan kecelakaan, yaitu perhitungan angka kecelakaan berdasarkan pembobotan tingkat keparahan, perhitungan  blacksite dengan menggunakan metode Z-Score untuk menentukan daerah rawan kecelakaan dan perhitungan blackspot dengan menggunakan metode Cusum untuk menentukan titik rawan kecelakaan. Data yang digunakan adalah data sekunder yang diperoleh dari Unit Laka Lantas Polres Lhokseumawe tahun 2009-2013.Berdasarkan perhitungan metode Z-Score dan metode Cusum diperoleh daerah yang memiliki tingkat kerawanan kecelakaan tertinggi adalah Jl. Medan –Banda Aceh Desa Panggoi Kecamatan Muara Dua pada Sta 266 – Sta 267 (km 266,00 – km 267,00) dengan persentase kecelakaan 64%. Sedangkan daerah yang memiliki tingkat kerawanan kecelakaan terendah adalah Jl. Bukit Indah Desa Padang Sakti Kecamatan Muara Satu  pada Sta 0 – Sta 1 (km 00,00 – km 00,01) dengan persentase kecelakaan -1%.
PURITY & PROFILE MATCHING APPROACH TO DETERMINE THE GOVERNMENT AID RECIPIENT IN ACEH UTARA, INDONESIA Sujacka Retno; Novia Hasdyna
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.045 KB)

Abstract

Purity algorithm is a new algorithm in the field of informatics that used to measure the pure value of a number of data. Profile Matching algorithm is an algorithm that used in making a decision, such as determining the criteria for receiving aid from the government. This research aims to apply the two algorithms, Purity & Profile Matching in determining the criteria of recipients for government aid funds for citizens in Aceh Utara in 2022, where it is hoped that the funds will be accurately given to people in need. The criterias used in this research include name, occupation, income, assets, and number of dependents. The data that has been collected then analyzed by applying the Purity & Profile Matching algorithm. As for this research, two methods will be applied namely Purity & Profile Matching. It used as a comparison in determining the criteria needed in determining the acceptance of the aid funds. This research applied to a Web-based system using the PHP programming language and MySQL database.
Sistem Informasi Komoditi Nelayan Desa Pusong Lama Kota Lhokseumawe Amrullah, Novia Hasdyna, Rahmat, Putri Nahrisa
Jurnal Elektronika dan Teknologi Informasi Vol 3 No 2 (2022): September 2022
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v3i2.314

Abstract

Data on fishery resources and the environment in Lhokseumawe City, Desa Pusong Lama have not been processed and compiled properly which results in less or slow information received by actors in the fisheries system, as well as the use of technology that has not been maximized in data processing. This study builds an information system for fishery products in Pusong Lama Village, Lhokseumawe City so that the delivery of information is better and can be accessed quickly by all actors. The fishery system can make it easier to make a decision to build a business in the fisheries sector. With this information system, it can provide convenience to users in processing and searching fishery resource data, the environment and fisheries technology in Pusong Lama Village. The web-based information system is built using the PHP programming language.
Evaluasi model data chatbot dalam natural language processing menggunakan k-nearest neighbor Sujacka Retno; Rozzi Kesuma Dinata; Novia Hasdyna
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4690

Abstract

Chatbot merupakan sebuah aplikasi yang terdapat pada rumpun ilmu Natural Language Processing (NLP) berbasis Artificial Intelligence (AI) atau juga dikenal dengan Kecerdasan Buatan yang dapat mensimulasikan sebuah percakapan antar pengguna layaknya melalui aplikasi SMS, situs website, private chatroom, ataupun melalui aplikasi seluler. Penelitian ini dilakukan di Kota Lhokseumawe dengan membuat sebuah aplikasi chatbot dengan pemodelan data yang diperoleh dari Pemerintah Kota Lhokseumawe. Penelitian ini bertujuan untuk memudahkan para wisatawan ataupun penduduk setempat dalam mencari informasi terkait dengan Kota Lhokseumawe. Pemodelan data yang dibangun dievaluasi dengan menggunakan algoritma K-Nearest Neighbor. Pemodelan data di dalam penelitian ini adalah sebanyak 600 model data yang dievaluasi sebanyak 400 kali pengujian untuk menemukan model terbaik dalam pengunaan model data dari chatbot yang dibangun. Hasil penelitian menunjukkan tingkat akurasi pada pengujian ke 400 adalah sebesar 100% dengan loss rate sebesar 0,0352
Co-Authors Akbar Arafat Akbar, Hafizal Fajriana, Fajriana Hafizal Akbar Haried Novriando Hendra A Mizan Maulana Muhammad Alif Muhammad Jabar Muhammad Nurfahmi Mustaqim Mustaqim Mutasar Muttaqin Muttaqin Nur Azizah Rizal S.Si., M.IT, Rizal Rozzi Kesuma Dinata Safwandi Safwandi Safwandi Safwandi Sujacka Retno T. Irfan Fajri Yustizar Yustizar Zulfa Zulfa