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INDONESIA
Journal of Informatics and Information Security
Published by Universitas Bhayangkara Jakarta Raya
ISSN : -     EISSN : 27224058     DOI : https://doi.org/10.31599
Core Subject : Science,
Computer Science & IT
Jurnal ini berisi tentang karya ilmiah hasil penelitian bidang ilmu komputer yang bertemakan: Artificial Intelligence, Blockchain Technology, Business Intelligence, Cloud Computing, Computer Architecture, Computer Vision, Database Systems, Deep Learning, Human Computer Interaction, Digital Forensic, Internet of Things, IT Security, Machine Learning, Networking, Semantic Web, Sistem Terdistribusi, Systems Engineering, Wireless Network.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 106 Documents
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Klasifikasi Algoritma K-Nearest Neigbhor Untuk Memprediksi Barang Pada PT Enesis Group Adi Muhajirin; Sastro Atmojo Sasosno; Truly Wangsalegawa
Journal of Informatic and Information Security Vol. 2 No. 2 (2021): Desember 2021
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/g92qhz24

Abstract

The company's success in maintaining its business is inseparable from the company's role in managing inventory (inventory) of goods so that it can meet the demands of customers as much as possible. During this time at PT. Enesis Group for data collection in warehouses is still carried out by keeping a manual in the book, which causes the accumulation of documents and the risk of loss or damage to documents when the item data is needed to make a report to superiors and also as a performance evaluation aterial. Often there is a lack of goods / reject goods. Do not have a computerized system. In the case of this study, the K-Nearest Neighbor method can be applied to the prediction of goods going out at the warehouse of PT. Enesis Group because it can predict the goods out correctly so that there is no shortage or excess stock of goods in the warehouse. The results of the calculation of the prediction of goods going out with the KNN method with an optimal value of K (9) are for ordering goods with a shipping distance of more than 1000 km and the expiration of goods more than 1 year, as well as for ordering goods with a distance of less than 1000 km and the expiration of goods is less from 1 year, the item is eligible to send.
Metode SAW (Simple Additive Weighting) Untuk Pemilihan Karyawan Terbaik Kusdarnowo Hantoro; Andy Achmad Hendharsetiawan; Ajif Yunizar Pratama Yusuf
Journal of Informatic and Information Security Vol. 2 No. 2 (2021): Desember 2021
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/9jt32f24

Abstract

The purpose of determining the best employees is as an appreciation for employee performance so as to motivate employees to be able to work optimally and be able to survive in the organization for a long time. Although the goal is very simple, however, the process turns out to be very complex, takes quite a long time and costs quite a bit so that this creates the opportunity for errors to occur in determining who is the right person. Especially if the company has employees with abilities that are not much different from other employees, the determination is sometimes very subjective. Actually there are several assessment criteria in the decision-making process for selecting the best employees, namely: an assessment based on the criteria for attendance, loyalty, and tardiness and employee performance. Because it is necessary to build a system that can assist decision making to determine the selection process objectively by using the SAW (Simple Additive Weighting) method.
Penerapan Algoritma K-Means Untuk Pengelompokkan Minat Konsumen Gas LPG Pada Pangkalan Sudiawati Annisa Wulandari; Tri Dharma Putra; Srisulistiowati, Dwi Budi
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/vfx5ae35

Abstract

Pangkalan Sudiawati is one of the shops engaged in the sale of LPG Gas products domiciled in Harapan Indah, North Bekasi. The goods sold at the Sudiawati base are 3 Kg and 12 Kg LPG Gas. These problems can be solved by using one of the techniques in data mining, namely the K-Means Clustering algorithm. This research is intended to assist Pangkalan Sudiawati in selling 3 Kg and 12 Kg LPG gas to consumers, to group sales data in order to maximize stock management. The data is processed by manual calculations using the K-Means algorithm and using Microsoft Excel 2019 Software. These results can be used to improve stock managementand sales strategies at Pangkalan Sudiawati.
Layanan Pengecekan Judul Buku Menggunakan Algoritma Boyer-Moore pada Perpustakaan SDN Sumur Batu 4 Bantargebang Bekasi Isnawati; Dwipa Handayani; Achmad Noeman
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/dwkc9e79

Abstract

in the library is one part of the processing and utilization of information at SDN Sumur Batu 4 Bantargebang Bekasi is still not computerized, manual searches or searches cause students to have difficulties in searching books and librarian can notcontrol books efficiently from school problems. a system that can solve problems so as to produce the goal of increasing efficiency in book searches, building a book title checking service system using the Boyer-Moore algorithm and providing convenience for all users in utilizing book searches. By implementing the book title checking service using the Boyer-Moore algorithm as the most efficient algorithm and using the rapid application development method starting from planning, design workshops, rapid application development and implementation. The data collection methods are observation, interviews, questionnaires and library studies. It is expected to be able to help speed up the process of searching for books in the library and to increase the satisfaction of library services for library visitors.
Implementasi Algoritma Naïve Bayes Untuk Memprediksi Kerusakan Sepeda Motor Pada Bengkel Citra Djaya Motor Leni Epriliani; Mayadi; R. Wisnu Prio Pamungkas
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/x66wmy53

Abstract

This research is about the implementation of the Naïve Bayes Algorithm for Predicting Motorcycle Damage at the Citra Djaya Motor Workshop. This system aims to make it easier for workshop employees to check customer motorcycle damage when they want to do service. That way this system can improve services at the Citra Djaya Motor Workshop. Currently, the process of checking motorcycle damage at the Citra Djaya Motor Workshop is still using the manual method in analyzing motorcycle damage. The algorithm used in this study uses the Naïve Bayes algorithm. Making this system using the programming language PHP and Codeigniter as aframework and MySQL database. The results of this research can be implemented in the form of a web-based system.
Perancangan ChatBot Pendaftaran Siswa Dengan Telegram BOT Design a Chatbot for Student Registration Using Telegram BOT Harry Priambodo; Adi Muhajirin
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/2d0gqs45

Abstract

The increasing number of Covid-19 victims is making us more and more aware of the importance of health protocols from wearing masks, maintaining distance, always washing hands, avoiding crowds, etc. It was recorded that on May 19, 2022, 6 million Indonesians were confirmed positive for Covid-19, however in the new academic year SDN Sriamur 02 still applies on-site registration, and because of the increasing level of prospective students from year to year, the school admin officers are overwhelmed, from the results of initial observations. the guardians of SDN Sriamur 02, the majority of the application services used are chat services, besides being able to be used anywhere, they are also more efficient in using internet quota, therefore the author has an idea to create a bot that runs on the Telegram Messenger application that can help in the registration of prospective students, where the development model that will be used by the author is Extreme Programming which is a software development model that tries to simplify the various stages in the development process so that it becomes more adaptive and flexible, so that the Extreme Programming (XP) method puts forward adevelopment process that is more responsive to needs. The research carried out resulted in a system that was ready to be used anytime anywhere for 24 hours and succeeded in carrying out one of the protocols in the pandemic era, namely social distancing, and a dataset of prospective students stored in the Googlesheet database.
Implementasi Metode SVM untuk Klasifikasi Bunga dengan Ekstraksi Fitur Histogram of Gradient (HOG) Henny Leidiyana; Warta, Joni
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/f3cgcv61

Abstract

Feature extraction techniques are applied to obtain features that will be useful in classifying and recognizing images. Feature extraction techniques are very helpful in various image processing applications. Many studies show the effectiveness of feature extraction before classification. There is also research showing that a feature extraction method may be good for certain classification approaches but may also be preferable. The impact of the sample and its size can also determine the results of the application of feature extraction techniques in the classification process. In this study, the author aims to prove the effectiveness of the application of the HOG feature extraction technique on the classification with the SVM method on flower images. The experiment was carried out on two groups of images, where the first group was image classes with relatively uniform colors and shapes, both in shape and color. and the second group is image classes with relatively different colors and shapes in the same class. The results showed that image datasets with relatively uniform colors and shapes do not require the application of any feature extraction to produce high accuracy. For classification by performing feature extraction in this study it gives different results for the two interest groups.
Penerapan Algoritma K-Means untuk Mengetahui Pola Persediaan Barang pada Toko Raja Bekasi Intan Safira; Ratna Salkiawati; Priatna, Wowon Priatna
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ykryzk32

Abstract

This study aims to determine how much the results of grouping goods affect the needs of consumers. Excess inventory will greatly fill the warehouse and be inefficient because of the expiration date on food products, beverages, etc. Currently Toko Raja still manages goods manually so it is not time efficient. To solve this problem, a technique is needed, namely data mining. The data mining technique that will be used in this research is the K-Means Clustering method. K-Means is one of the most popular algorithms because it is easy and simple to implement. However, the results of the clustering of K-Means are very dependent on theselection of the initial cluster center point. Calculation of accuracy in this study using the test results of the K-Means clustering method using the Davies-Bouldin Index (DBI) is 1.856 where the DBI value close to zero cluster is good enough. From the resulting accuracy, it can be concluded that the K-Means Clustering method can support the system well.
Sistem Informasi Pengarsipan Surat Masuk dan Keluar dengan Algoritma Sequential Search di Kelurahan Bahagia Mugiarso; Tri Furkan Sarjono Aji; Khairunnisa Fadhilla Ramdhania
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/6peysq52

Abstract

In Kelurahan Bahagia, there are problems in managing archives, especially archiving incoming and outgoing letters, precisely in the search and presentation of mail information, often experiencing delays and difficulties in finding the archives of the letters. This study aims to assist Kelurahan Bahagia in overcoming the problem of mail archives, by designing and developing an information system for archiving incoming and outgoing mail using the Rapid Applciation Development (RAD) method and using a sequential search algorithm to help find mail information faster and easier. The result of this research is an information system for archiving incoming and outgoing mail that can help overcome the problem of filing letters in Kelurahan Bahagia.
Metode Certainty Factor pada Sistem Pakar Identifikasi Penyakit Mental: Certainty Factor, Expert System, Mental Disorder Ahmad Wildan; Rafika Sari
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/1n4z9070

Abstract

Di Indonesia, orang dengan gangguan mental diidentifikasi sebagai 'sakit jiwa', dan sering mengalami perlakuan yang tidak menyenangkan. Ada banyak faktor yang dapat memicu gangguan mental, mulai dari menderita penyakit tertentu hingga mengalami stres akibat peristiwa traumatis. Untuk meminimalisir munculnya gangguan mental, menjaga kesehatan mental sangatlah penting. Kesehatan mental adalah tentang meningkatkan kompetensi individu dan masyarakat dan memungkinkan mereka untuk mencapai tujuan yang ditentukan sendiri. Salah satu sarana untuk memudahkan masyarakat peduli terhadap kesehatan mental, dalam penelitian ini akan dirancang sistem pakar untuk identifikasi masalah mental berdasarkan website sehingga mudah diakses oleh kebanyakan orang saat ini. Dengan menggunakan metode Faktor Kepastian , sistem pakar ini akan mampu menghasilkan diagnosa dengan persentase beberapa kemungkinan penyakit, sehingga dapat menghasilkan informasi yang dibutuhkan lebih detail. Data gejala umum dan gejala klinis yang sering dialami diperoleh dari instansi mitra yang bergerak di bidang layanan Psikologi. Dari 16 test case yang telah dilakukan dengan menggunakan black box testing, menunjukkan bahwa nilai valid sistem pakar untuk mendiagnosis gangguan mental adalah100%, yang menandakan fungsionalitas sistem berjalan sesuai dengan daftar persyaratan sistem . Hasil dari aplikasi sistem pakar ini dapat memberikan beberapa informasi mengenai gangguan mental beserta tips untuk mengatasinya.

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