cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alam Rahmatulloh
Contact Email
alam@unsil.ac.id
Phone
+6285223519009
Journal Mail Official
innovatics@unsil.ac.id
Editorial Address
Program Studi Informatika Fakultas Teknik Universitas Siliwangi Jl. Siliwangi No. 24 Tasikmalaya, Jawa Barat
Location
Kota tasikmalaya,
Jawa barat
INDONESIA
Innovation in Research of Informatics (INNOVATICS)
Published by Universitas Siliwangi
ISSN : -     EISSN : 26568993     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Innovation in Research of Informatics (Innovatics) merupakan Jurnal Informatika yang bertujuan untuk mengembangkan penelitian di bidang: Machine Learning Computer Vision Internet of Things Information System and Technology Natural Language Processing Image Processing Network Security Geographic Information System Knowledge based Computer Graphic Cyber Security IT Governance Data Mining Game Development Digital Forensic Business Intelligence Pattern Recognization Virtual & Augmented Reality Virtualization Enterprise Application Self-Adaptive Systems Human Computer Interaction Cloud Computing Mobile Application Innovatics adalah jurnal peer-review yang ditulis dalam bahasa Indonesia yang diterbitkan dua kali dalam setahun mulai dari Vol. 1 No.1 Maret 2019 (Maret, dan September) dengan proses peninjauan menggunakan double-blind review.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 94 Documents
 3   4   5   6   7 
Pengenalan Jenis Ular Berbasis Augmented Reality di Indonesia Menggunakan Metode Markerless Based on Tracking Wijaya, Irvan Akbar
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 1 (2022): Maret 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i1.3030

Abstract

Due to the lack of education and understanding of the types of snakes to the community in Indonesia due to ignorance, it has caused damage to snake habitat and the human environment, for example, damaged rice fields due to high rat populations due to snake extinction due to various arrests and culling. Therefore, in this final project that will be done is to create an Augmented Reality application of Indonesian snakes with a markerless based on tracking method and the use of User Defined Target technology with the aim of being an answer to the problems being faced its benefits In addition to information, insight into knowledge about understanding the types and characteristics snake in Indonesia. The results of the application testing research were carried out using the alpha test method alpha testing was carried out by black-box testing all menus and buttons were running well, the camera distance was 15 cm. very nice.
Implementasi Algoritma Apriori Dalam Menemukan Association Rules Pada Persediaan Sparepart Motor Nurhidayanti, Dina; Kurniawati, Ika
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 2 (2022): September 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i2.5300

Abstract

Saat ini kompetisi bisnis dalam beragam bidang menjadi sangat erat. Selain pada bidang fashion, hidangan, dan elektronik, bidang pelayanan jasa dan perdagangan pun semakin melambung tinggi, seperti halnya bidang otomotif. Honda Tanabang Motor memiliki banyak data transaksi yang tidak dimanfaatkan untuk menganalisa persediaan barang yang laku atau banyak diminati pelanggan, serta tidak dimanfaatkan menjadi informasi yang berguna untuk strategi marketing. Penulis mencoba mengimplementasi algoritma apriori pada persediaan sparepart, karena algoritma apriori adalah metode yang paling tepat dalam mencari aturan asosiasi barang dan frequent-itemset. Hasil dari pengujian algoritma apriori telah ditemukan 3 (tiga) association rules yakni jika membeli Piece Set Slide maka membeli Busi, jika membeli Lampu Belakang maka membeli Kampas Rem Depan, dan jika membeli Lampu Depan maka membeli Kampas Rem Depan, dengan Nilai Confidence 75% dan Nilai Support 25%. Dengan hadirnya Implementasi Algoritma Apriori, diharapkan menjadi salah satu solusi untuk mempermudah perusahaan agar melakukan pengaturan ulang tata letak sparepart secara berdekatan untuk memudahkan dalam mengambil barang yang akan dikeluarkan, melakukan monitoring terhadap persediaan barang, hubungan antar tiap produk yang dibeli secara bersamaan dan penunjang informasi dalam pemesanan stok barang serta dapat membantu merumuskan strategi pemasaran untuk meningkatkan penjualan.   Kata Kunci : Apriori,  Aturan Asosiasi, Data Mining, Persediaan Barang 
Analisa Dan Perancangan Sistem Pendukung Keputusan Penentuan Promosi Jabatan Pada PT. XYZ Menggunakan Metode Profile Matching Sari, Mawar
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 2 (2022): September 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i2.5303

Abstract

Human Resources (HR) is one of the important functions in an organization or company to get the best employees to achieve the goals of the company. The best way how to improve Human resources is by promoting or awarding the best employees. The selection of the best employees is required an objective system. PT. XYZ is one of company who implementing these methods to improve their resources, but the selecting are still conventional methods which final decision still determined under leadership company according to the existing delegation of authority. This research is to analyze and design a decision support system to determining the promotion using Profile Matching Method. the implementation will be two main aspect that will be assessed, they are Performance Aspects and work behavior aspect, each aspect has 5 sub-criteria. The final value of two aspects is calculated with different percentage which are 70% for the performance aspect and 30% for work behavior aspect. The results, there were 3 employees with the highest grades who entitled to be promoted, are the employee with NIK INDO09, INDO07 and INDO06 which score of 4,81, 44,62 and 4,49. Finally the decision support system implemented to the web-based application which expected to assist related parties in determining employee promotions based on specified criteria to get the objective decisions.
Jaringan Syaraf Tiruan Mendeteksi Penyakit Pneumonia Infeksi Saluran Pernafasan Akut Dengan Algoritma Backpropagation Edwar, Yulia; Rendy, Rendy; Sanoto, Jazuli
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 4, No 2 (2022): September 2022
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v4i2.5161

Abstract

Acute Respiratory Infections (ARI) is a health problem that often affects children and adults. For adults, acute respiratory infections are mild or common, but in children under five, this disease is a threat that can cause death. One of the causes of death due to acute respiratory infections is the incorrect diagnosis. This study aims to determine the level of accuracy and optimal neural network architecture in detecting ARI using the backpropagation method. The backpropagation method is a pattern recognition technique that is able to provide decision results based on trained data. This research was implemented using MATLAB software with several forms of network architecture. Symptoms of ARI that were used as input for detection of the disease consisted of 13 variables targeting non-pneumonia and pneumonia ARDs. Based on the research results, the architecture with the best configuration consists of 13 input layer neurons, 20 hidden layer neurons and 2 output layer neurons with a binary sigmoid activation function (logsig), a learning rate value of 0.5, an error tolerance value of 0.001, a maximum of epoch of 216 and MSE 0.000997. Artificial neural networks with the backpropagation method used for weight adjustment can respond to training data and testing data well, marked by the resulting network accuracy 100% in accordance with the desired target.
Multi-Layer Perceptron For Diagnosing Stroke With The SMOTE Method In Overcoming Data Imbalances Ariansyah, M. Hafidz; Winarno, Sri; Nur Fitri, Esmi; Arga Retha, Helynda Mulya
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 1 (2023): Maret 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.6565

Abstract

Stroke is the sudden loss of brain function due to an interruption of the blood supply to the brain. Stroke is a dangerous disease that can even cause death for patients. The diagnosis of stroke must be made quickly and precisely to increase the likelihood that the patient can live a normal life again. In making a diagnosis, several factors can influence the patient to get a stroke diagnosis, including symptoms of hypertension to heart disease. From these problems, the researcher wants to classify the diagnosis of stroke so that stroke can get earlier treatment so that patients do not experience prolonged illness. The data used in this study is a stroke dataset with 4861 data labeled 0 which indicates no stroke, and 249 data labeled 1 which indicates a stroke diagnosis. This study uses the Synthetic Minority Over-sampling (SMOTE) method that will be applied to the Multi-Layer Perceptron algorithm so that researchers can get the performance of the stroke diagnosis classification model. Researchers use the SMOTE method so that the data in the classification model is balanced so that the model can make accurate predictions and avoid overfitting on the Multi-Layer Perceptron so that the accuracy in predicting stroke is better than just using an ordinary Multi-Layer Perceptron. The results of the confusion matrix analysis show that SMOTE can increase the prediction of stroke diagnosis from 12,5% to 84,89% in optimal test.
Forecasting Flood Vulnerability in Pontianak using Multiple Linear Regression and Geospatial Information Systems (GIS) Farhan, Firda Islamaya; Adi, Ahmad Cahyono
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 1 (2023): Maret 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.6567

Abstract

Flood disasters frequently happen in locations with specific geographic characteristics, such as close proximity to rivers and excessive rainfall, especially during the rainy season, making most soil types contain clay and unsuitable for water absorption. One of the Indonesian cities that experiences frequent flooding is Pontianak City. Based on the parameters established in the preceding circumstances, multiple linear regression methods are used to forecast and anticipate the degree of flood risk in Pontianak City. The Quantum GIS application creates a digital map that displays the score attained in each sub-district. This is done to identify the flood-prone locations in Pontianak City and make the mitigation activities more focused and effective.
Security System For Motorcycle Using Raspberry Pi and Fingerprint With Mobile-Based Finite State Machine (FSM) Method Muzawi, Rometdo; Efendi, Yoyon; Rio, Unang; Toresa, Dafwen
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 1 (2023): Maret 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.6698

Abstract

Data from the BPS (Central Statistical Agency) show that private car theft in Indonesia is on the rise year after year, especially for two-wheeled vehicles or motorcycles. According to the BPS Crime Statistics Report, there were around 35,000 motor vehicle theft events in Indonesia in 2017 and 38,000 instances in 2018. People's concerns regarding the security of these two-wheeled vehicles are growing as a result. This study presents a fingerprint- and Raspberry Pi-based motorcycle security system. Bikes may be monitored, and their ignitions can be controlled remotely using a mobile-based Finite State Machine (FSM) technique. The Neo 6 GPS module will send longitude and latitude in real time to the Android smartphone application, which generates a map or location point so that it will send notifications if there is movement on the motorcycle. The voltage sensor connected to the Raspberry Pi circuit can detect the motor voltage. A system that uses the FSM (Finite State Machine) approach to identify changes in location data from designated parking lots and deliver messages to a push bullet is the study's output. Controlling the motorcycle ignition, which may remotely switch off the motorcycle when one is taken, is another way to provide early notice.
Security System For Motorcycle Using Raspberry Pi and Fingerprint With Mobile-Based Finite State Machine (FSM) Method Rometdo Muzawi; Yoyon Efendi; Unang Rio; Dafwen Toresa
Innovation in Research of Informatics (INNOVATICS) Vol 5, No 1 (2023): Maret 2023
Publisher : Informatika Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.6698

Abstract

Data from the BPS (Central Statistical Agency) show that private car theft in Indonesia is on the rise year after year, especially for two-wheeled vehicles or motorcycles. According to the BPS Crime Statistics Report, there were around 35,000 motor vehicle theft events in Indonesia in 2017 and 38,000 instances in 2018. People's concerns regarding the security of these two-wheeled vehicles are growing as a result. This study presents a fingerprint- and Raspberry Pi-based motorcycle security system. Bikes may be monitored, and their ignitions can be controlled remotely using a mobile-based Finite State Machine (FSM) technique. The Neo 6 GPS module will send longitude and latitude in real time to the Android smartphone application, which generates a map or location point so that it will send notifications if there is movement on the motorcycle. The voltage sensor connected to the Raspberry Pi circuit can detect the motor voltage. A system that uses the FSM (Finite State Machine) approach to identify changes in location data from designated parking lots and deliver messages to a push bullet is the study's output. Controlling the motorcycle ignition, which may remotely switch off the motorcycle when one is taken, is another way to provide early notice.
Natural Language Processing for Unstructured Data: Earthquakes Spatial Analysis in Indonesia Using Platform Social Media Twitter Joko Ade Nursiyono; Rasya Khalil Gibran
Innovation in Research of Informatics (INNOVATICS) Vol 5, No 1 (2023): Maret 2023
Publisher : Informatika Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.6678

Abstract

As a country who had a high risk affected by the earthquake, social media have an important role. Besides to serving earthquake information, the spread of information on social media is so wide and fast. However, information on social media has a gap to reach validity and doesn't contain detailed information about spatial information. By leveraging crawling result data on Twitter, then data will be processed with Natural Language Processing (NLP), this research aims to proves about transformation of unstructured data into structured data with NLP for use on spatial analysis in Indonesia using data text on platform social media, Twitter. In addition, this research is also aims to reveal correlation between earthquake magnitude and earthquake frequency. The results proves that NLP can be used for spatial analysis with data text on Twitter related to earthquake. Besides that, the value of maximum magnitude are great significance to the earthquake frequency.
Data Integrity Testing of Digital Evidence Data Capture Results on Private Cloud Computing Services Komarudin, Arif Maulana; Widiyasono, Nur; Aldya, Aldy Putra; Rizal, Randi
Innovation in Research of Informatics (Innovatics) Vol 5, No 2 (2023): September 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i2.8420

Abstract

Private Cloud has better advantages than other cloud services because private cloud is managed and run by the company itself so that cloud needs can be tailored to the company's needs, but allows abuse from within the company itself, as in the case study simulation of a Gojek startup company. This case occurred because of a security weakness in the system so that internal people took advantage of these weaknesses for their own benefit by leaking confidential data, acquisitions were carried out to prove and find evidence of crime, acquisitions used live acquisition techniques, namely acquisitions on an ongoing system, namely monitoring network traffic using Wireshark tools , the method in this case uses the Digital Forensics Investigating Framework (DFIF), data integrity must be properly maintained when acquiring digital evidence because to maintain the authenticity of the digital evidence obtained, then data integrity is tested on the digital evidence obtained, testing is carried out on digital evidence before and after the acquisition to see if there is a change in data integrity, the research results show that there is no change in data integrity.

Page 5 of 10 | Total Record : 94

 3   4   5   6   7 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol 7, No 2 (2025): September 2025 Vol 7, No 1 (2025): March 2025 Vol 6, No 2 (2024): September 2024 Vol 6, No 1 (2024): March 2024 Vol 5, No 2 (2023): September 2023 Vol 5, No 1 (2023): Maret 2023 Vol 4, No 2 (2022): September 2022 Vol 4, No 1 (2022): Maret 2022 Vol 3, No 2 (2021): September 2021 Vol 3, No 1 (2021): Maret 2021 Vol 2, No 2 (2020): September 2020 Vol 2, No 1 (2020): Maret 2020 Vol 1, No 2 (2019): September 2019 Vol 1, No 1 (2019): Maret 2019 More Issue