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Hidra Amnur
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hidra@pnp.ac.id
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admjitsi@gmail.com
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Kampus Politeknik Negeri Padang, Jurusan Teknologi Informasi. Gedung E. Limau Manis, Pauh. Padang - Sumatera Barat. Indonesia
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JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Published by Society of Visual Informatics
ISSN : 27224619     EISSN : 27224600     DOI : 10.30630/jitsi
Core Subject : Science,
Computer Science & IT
The journal scopes include (but not limited to) the followings: Computer Science : Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering : Computer Architecture, Computer Network, Computer Security, Embedded system, Coud Computing, Internet of Thing, Robotics, Computer Hardware Information Technology : Information System, Internet & Mobile Computing, Geographical Information System Visualization : Virtual Reality, Augmented Reality, Multimedia, Computer Vision, Computer Graphics, Pattern & Speech Recognition, image processing Social Informatics: ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT education
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 5 Documents
 1 
Search results for , issue "Vol 3 No 4 (2022)" : 5 Documents clear
Perancangan dan Implementasi ERP (Enterprise Resource Planning) Modul Sales Pada PT Kanefusa Indonesia eko prabowo; Kusnadi Suparman; Nika Rediyan; Marianus Bryan S; Irama Harefa
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 4 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.4.52

Abstract

ERP (Enterprise Resource Planning) is a business process management software that allows companies to use integrated applications to support and facilitate the running of business operational activities in a company and is computerized. The company PT Kanefusa Indonesia is a company engaged in the manufacturing sector. This company is starting to develop and wants to switch to a computerized system, therefore an ERP system will be applied to the company PT Kanefusa Indonesian. The author will design and implement an ERP Sales module for the sales department as a means to convey information related to sales and delivery activities. The Open Source ERP used is Odoo. This Odoo Open Source ERP application is compatible with business processes with various efficiency features available. Then the feasibility of the program will be analyzed through a questionnaire form.
Human Activity Recognition Berdasarkan Tangkapan Webcam Menggunakan Metode Convolutional Neural Network (CNN) Dengan Arsitektur MobileNet Fauzan Akmal Hariz; Intan Nurma Yulita; Ino Suryana
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 4 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.4.97

Abstract

Manusia tidak bisa terlepas dari aktivitas sehari-hari yang mana merupakan bagian dari kehidupan manusia. Human activity recognition atau pengenalan aktivitas manusia saat ini merupakan salah satu topik yang sedang banyak diteliti seiring dengan pesatnya kemajuan di bidang teknologi yang berkembang saat ini. Hampir semua bidang terdampak dari pandemi COVID-19 yang memengaruhi aktivitas manusia sehingga menjadi lebih terbatas. Salah satu bidang yang paling terdampak yaitu pendidikan, di mana kampus menerapkan sistem pembelajaran daring, yang membuat dosen lebih sulit untuk mengawasi pembelajaran maupun ujian yang dilakukan secara daring karena tidak dapat mengawasi aktivitas yang dilakukan mahasiswa secara langsung. Penelitian ini bertujuan untuk membuat model yang dapat mengenali aktivitas seseorang saat ujian daring berdasarkan tangkapan webcam dengan memanfaatkan model deep learning dengan metode Convolution Neural Network (CNN) menggunakan arsitektur MobileNetV2. Pengujian hyperparameter dilakukan untuk menghasilkan model optimal yang dilakukan pada batch size sebesar 16, 32, dan 64 serta dense layer sebanyak 1, 3, 5, dan 7. Pengujian tersebut menghasilkan model optimal dengan hyperparameter berupa max epoch sebanyak 20, early stopping dengan patience sebesar 10, learning rate sebesar 0,0001, batch size sebesar 16, dan dense layer sebanyak 5. Model tersebut dievaluasi menggunakan cross validation dan confusion matrix yang berhasil memberikan performa F1-score akhir sebesar 84,52%.
Penentuan Status Penularan COVID-19 di Jawa Timur Menggunakan Metode Fuzzy Tsukamoto Ishaq Agastyan Maulana Pratama; Suryo Atmojo
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 4 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.4.98

Abstract

The COVID-19 pandemic is not over, the Coronavirus Disease 19 Pandemic due to the SARS-CoV-2 virus is spreading very quickly in almost every country in the world because of its human-to-human nature. The COVID-19 pandemic in Indonesia was detected in Depok, West Java on March 2, 2020. To deal with this, the government must decide on an efficient policy by observing the atmosphere and situation in each region. The way is through determining the risk status of COVID-19 transmission in an area in order to break the chain of transmission of COVID-19. In Indonesia, it is up to each local government to determine the risk status of Covid-19 transmission at the regional level. This has led to subjective evaluations by local leaders and introduced many unclear definitions and boundaries when determining the risk status of COVID-19 transmission. This is the reason behind this research, where the Tsukamoto Algorithm mathematical calculation form is based on the official variables and regulations in the area concerned in determining the risk status of COVID-19 transmission. The data used is the daily data for COVID-19 districts or cities in East Java. The data used are 38 district or city data groups consisting of 4 variables. The input variables are COVID-19 positive cases, Supek cases, and Probabe cases, and each variable is defined as 3 fuzzy sets, namely Low, Medium, and High. The output variables are defined in 4 fuzzy sets regarding the Risk Status for COVID-19 Transmission, such as the East Java Government regulations, namely the status of green, yellow, orange, and red. All variables use membership function of triangular curve representation. How to analyze data using the SPK-COVID application using the Codeigniter Framework. The success of the estimation form of the percentage of conformity status generated by comparing the results of the Tsukamoto Algorithm analysis with real COVID-19 transmission risk status data. After doing 4 repetitions of the analysis, in which each analysis tries to change the area in the fuzzy set, we get a structure with a percentage of status conformity that is usually 95.51%, on data from 38 districts or cities in East Java.
Clustering Data Evaluasi Standar Sistem Penjamin Mutu Internal (Studi Kasus: Jurusan Teknologi Informasi Politeknik Negeri Padang) Hanif Aulia Sabri; Yulherniwati; Fazrol Rozi
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 4 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.4.99

Abstract

Undang-undang Nomor 12 Tahun 2012 tentang Pendidikan Tinggi mengatur kebijakan otonomi perguruan tinggi dalam meningkatkan mutu pendidikan perguruan adalah Sistem Penjamin Mutu Perguruan Tinggi (SPM-PT). Dalam SPM-PT terdapat struktur dan mekanisme yang terdiri atas Sistem Penjamin MutuInternal (SPMI), Sistem Penjamin Mutu Eksternal (SPME) dan Pangkalan Data (PD Dikti). Evaluasi pada jurusan Teknologi Informasi dilaksanakan setiap tahunnya. Pada siklus SPMI terdapat beberapa tahap yaitu Penetapan, Pelaksanaan, Evaluasi, Pengendalian dan Peningkatan (P-P-E-P-P). Peninjauan mutu pendidikan dilakukan pada siklus ketiga dari P-P-E-P-P yaitu tahap evaluasi. Dalam pengolahan data hasil penilaian evaluasi auditor masih menghabiskan banyak waktu serta sering ditemukan kesalahan. Serta dari hasil penilaian auditor yang meliputi sejumlah butir standar, jurusan perlu memprioritaskan butir standar mana yang akan diperbaiki atau ditingkat terlebih dahulu. Dalam hal evaluasi oleh auditor diperlukan mekanisme penginputan yang lebih memudahkan auditor. Oleh sebab itu dalam penelitian ini dikembangkan aplikasi berbasis android untuk memudahkan input data evaluasi butir standar SPMI oleh auditor. Di samping itu juga dilakukan pengelompokkan butir standar yang punya pengaruh yang sama terhadap mutu prodi. Metode pengelompokkan yang dilakukan menggunakan salah satu algoritma Clustering yaitu Hierarchical Clustering yang akan menghasilkan Cluster yang telah dikelompokkan berdasarkan pengaruh antar butir mutu lainnya. Sehingga dari sekian banyak butir standar, dapat ditentukan butir yang bisa diprioritaskan untuk ditingkatkan.
Implementasi Metode Least Square untuk Peramalan Persediaan Barang Pada Sistem Inventori CV. Tre Jaya Perkasa Tulsi Yasmi Tulsi; Aldo Erianda; Rita Afyenni
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 4 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.4.100

Abstract

Entering the era of society 5.0 has brought many changes in various sectors, one of which is in the business sector. Competition in the business world and the rapid development of information technology, requires companies to make changes in business processes, one of which is CV. Tre Jaya Perkasa which is engaged in the distribution of goods such as snacks, drinks and daily needs. CV. Tre Jaya Perkasa is located in Solok, West Sumatra, Indonesia. CV. Tre Jaya Perkasa already has more than 1000 customers who take goods for resale. The number of sales transactions will affect the inventory in the warehouse. Inventory control is important for distributor companies to reduce stockouts for certain products. With this, a system is needed that is able to predict inventory for the future. For forecasting inventory, the Least Squares method can be applied. The Least Square method is a method used to determine trend equation data including Time Series analysis with two cases, namely even and odd case data. To measure forecast errors using this study the Mean Absolute Percentage Error (MAPE) method was used. This system is built using the Yii2 framework and the testing system uses Black Box Testing.

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