cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Frieyadie
Contact Email
jurnal.inti@nusamandiri.ac.id
Phone
-
Journal Mail Official
jurnal.inti@nusamandiri.ac.id
Editorial Address
-
Location
Kota adm. jakarta pusat,
Dki jakarta
INDONESIA
INTI Nusa Mandiri
Published by PPPM Nusa Mandiri
ISSN : 02166933     EISSN : 2685807X     DOI : -
Core Subject : Science,
Computer Science & IT
The INTI Nusa Mandiri Journal is intended as a media for scientific studies on the results of research, thought and analysis-critical studies on the issues of Computer Science, Information Systems and Information Technology, both nationally and internationally. The scientific article in question is in the form of theoretical review and empirical studies of related sciences, which can be accounted for and disseminated nationally and internationally.
Arjuna Subject : -
Articles 147 Documents
 11   12   13   14   15 
KLASIFIKASI KONDISI BAN KENDARAAN MENGGUNAKAN ARSITEKTUR VGG16 ahmad fudolizaenun nazhirin; Muhammad Rafi Muttaqin; Teguh Iman Hermanto
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4270

Abstract

Tyres are the main component that a vehicle needs to work with reducing vibration due to uneven road surfaces, protecting the wheels from wear to provide stability between the vehicle and the ground helping to improve acceleration to facilitate travel while driving. Wear ensures stability between the vehicle and the ground helps improve acceleration for easy movement and driving. Caused including components that are often used, tires can experience damage such as the appearance of cracks in the tires. Cracks in tires can be triggered by factors such as age or the cause of the road that has been exceeded. Detection of tire cracks at this time is still carried out conventionally, where users see directly the state of the tire whether the tire is in good condition or cracked. Conventional methods are important because they maintain tire quality and rider safety. The Conventional Method certainly has weaknesses because vehicle users must have good vision and the ability to distinguish normal tires or cracked tires, but this method is considered less effective because it still uses human labor, causing the risk of human error (human negligence) which can hinder the process of identifying tire cracks. Based on this problem, this study will develop a deep learning model that can classify cracked tires using the VGG16 architecture. In this study, the model was created using 8 scenarios by changing the value of epochs, to get the best parameters in making the model. The results of the 8 scenarios carried out in this study are the best scenario obtained in scenarios 1,3,4 which get 98% accuracy in model testing
OPTIMASI NAIVE BAYES BERBASIS PSO UNTUK ANALISA SENTIMEN PERKEMBANGAN ARTIFICIAL INTELLIGENCE DI TWITTER Elly Indrayuni; Acmad Nurhadi
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4282

Abstract

At present the development of Artificial Intelligence technology is progressing rapidly. There are many new artificial intelligence technologies available in various fields. Artificial Intelligence is an artificial intelligence program that can study data, perform processes of thinking and acting like humans. The presence of Artificial Intelligence technology has many positive impacts, especially in increasing work effectiveness and efficiency. However, AI is also a threat to human resources because slowly human work is being replaced by Artificial Intelligence. Various opinions about the development of Artificial Intelligence are widely discussed on social media such as Twitter. Sentiment analysis is a computational study to automatically categorize opinions into positive or negative categories. In this study, the Naive Bayes algorithm was used to analyze sentiment or public opinion regarding the development of Artificial Intelligence for Twitter users. The data collection method used is crawling data on Twitter. The results of the sentiment classification test for the development of Artificial Intelligence using Naive Bayes yield an accuracy value of 86.42%. Meanwhile, the results of the sentiment classification test using Naive Bayes based on Particle Swarm Optimization (PSO) increased with an accuracy value of 87.55%. Based on the results of this study, the use of PSO as an optimization technique for the Naive Bayes algorithm is proven to be the best algorithm model in sentiment analysis for the development of Artificial Intelligence for English text.
PENENTUAN KELAYAKAN BANGUNAN CAGAR BUDAYA MENGGUNAKAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE (SMART) Hesti Ratna Setyaningrum; Muhammad Rafi Muttaqin; Mochzen Gito Resmi
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4286

Abstract

Abstract— Nowadays, awareness of the importance of cultural heritage is decreasing among the public, especially among youth who will become leaders and inherit the culture of their region. Law Number 11 of 2010 stipulates the importance of protecting and preserving cultural heritage because it has significant value in history, science, education, religion and culture. Therefore, the existence of cultural heritage must be considered and maintained properly according to applicable regulations. There are several criteria for assessing buildings that will be used as cultural heritage according to Law number 11 of 2010 in Chapter III, article 5, cultural heritage criteria, namely the age of the building, historical value, cultural value and architectural value. This study aims to create a system that can determine the feasibility of a building as a cultural heritage in a precise and accurate way (case study DISPORAPARBUD Purwakarta). In this study, the Simple Multi Attribute Rating Technique (SMART) method was used in the Decision Support System (SPK). The results of this study are to produce recommendations for buildings that are worthy of being cultural heritage in accordance with predetermined criteria, namely the Normal School building with a value of 1 by occupying the first rank, which will then be recommended to the Purwakarta DISPORAPARBUD
KOMPARASI FUNGSI AKTIVASI NEURAL NETWORK PADA DATA TIME SERIES Ibnu Akil
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4288

Abstract

Abstract— The sophistication and success of machine learning in solving problems in various fields of artificial intelligence cannot be separated from the neural networks that form the basis of its algorithms. Meanwhile, the essence of a neural network lies in its activation function. However because so many activation function which are merged lately, it’s needed to search for proper activation function according to the model and it’s dataset used. In this study, the activation functions commonly used in machine learning models will be tested, namely; ReLU, GELU and SELU, for time series data in the form of stock prices. These activation functions are implemented in python and use the TensorFlow library, as well as a model developed based on the Convolutional Neural Network (CNN). From the results of this implementation, the results obtained with the CNN model, that the GELU activation function for time series data has the smallest loss value
SISTEM INFORMASI PENJUALAN TIKET MASUK WISATA JEMBATAN CINTA BERBASIS WEB Jefi Jefi; Muhammad Fahmi; Hendri Hendri; Desiana Nur Kholifah; Suharjanti Suharjanti
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4307

Abstract

Abstract— The use of technology in the tourism industry is becoming increasingly crucial considering changes in consumer behavior that tend to rely on digital platforms to make transactions. To analyze the effectiveness and reliability of facilitating the process of purchasing tickets online. In addition, it also includes an evaluation of the level of user satisfaction with this web-based system and its impact on increasing visits to the Cinta Bridge tourist attraction. Through surveys of tourists using a web-based ticket sales system, interviews with tour managers, and analysis of ticket transaction data documented in the system. Research participants include tourists, managers, and other related parties. The data were obtained and analyzed using statistical methods and qualitative analysis to gain a thorough understanding of the impact of the Web-Based Bridge Tourism Entrance Ticket Sales Information System. Demonstrating that managing ticket stock and arranging visit schedules more efficiently is also a positive result for the development of the technology-based tourism industry by proving the benefits of the Web-Based Bridge of Love Entrance Ticket Sales Information System. The results of this study can be the basis for the development and implementation of similar systems in other tourism destinations. In addition, the research is considered to provide valuable insights for related parties in optimizing the use of technology to improve user experience and operational efficiency in the tourism sector
SISTEM PAKAR DIAGNOSA PENYAKIT PADA DOMBA DENGAN MENGGUNAKAN METODE FUZZY MAMDANI Cucu Kardila; Muhammad Rafi Muttaqin; Mochzen Gito Resmi
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4314

Abstract

Abstract—The decreasing sheep population has raised serious concerns regarding its impact on both the livestock industry and export opportunities. One of the main factors contributing to this decline is the prevalence of diseases among sheep. These illnesses present a significant problem as they can lead to reduced meat production, animal fatalities, and economic losses. The limited knowledge among farmers regarding these diseases and sheep care makes it challenging to diagnose and treat the conditions effectively. To address this issue and aid farmers in easily diagnosing diseases, a web-based expert system utilizing the fuzzy Mamdani method was developed. The selection of the fuzzy Mamdani method was based on its ability to handle uncertainty in disease diagnosis, providing reasonably accurate results by evaluating symptoms, determining disease severity, and recommending appropriate treatments. Through the fuzzy Mamdani method and the web-based platform, this system offers convenient access for farmers to diagnose diseases in their sheep online. According to the analysis results, reproductive health disorders are the primary cause of the decline in the sheep population. Consequently, the expert system for diagnosing sheep diseases serves as an alternative for early prevention and suitable treatment. System testing indicates an accuracy rate of 80%, signifying the system's capability to provide reasonably accurate diagnoses. The main goal of this research is to support the livestock and fisheries department in Purwakarta in diagnosing sheep diseases, preventing epidemic outbreaks, and implementing proper measures to mitigate the negative impacts on the livestock industry while promoting sustainable growth of the sheep population
PENERAPAN ALGORITMA K-MEANS UNTUK KLASTERISASI PENDUDUK MISKIN DI PROVINSI BANTEN Frisma Handayanna
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4399

Abstract

Abstract— People with low incomes are unable to obtain education and other government services. The problem of poverty faced by the government is closely related to people with low incomes who cannot meet their basic needs. The Central Bureau of Statistics describes poverty as the inability to meet basic food and non-food needs as measured by expenditure. This study aims to classify Banten province based on poverty levels, by dividing the number of poor people into high, medium, and low categories. The K-Means clustering method is very fast and easy to use in the K-Means algorithm clustering process. Where the grouping results are formed, namely group one has a moderate number of poor people in three districts/cities, Pandeglang Regency, Lebak Regency, and Tangerang Regency. The second group has the lowest population in one district/city, namely Tangerang City. The third group has the highest number of poor people in the four districts/cities, namely Serang Regency, Cilegon Regency, Serang City, and South Tangerang City. The clustering results show that the Provincial Government of Banten will give priority and special attention to poverty alleviation efforts in the district/city. This will allow for increased revenues and earnings, as well as improved livelihoods and the economy in the area. the K-Means algorithm can classify the poor based on the number of people per district or city in Banten Province.

Page 15 of 15 | Total Record : 147

 11   12   13   14   15 

Filter by Year

2017 2023


Reset
Filter By Issues
All Issue Vol 18 No 1 (2023): INTI Periode Agustus 2023 Vol 17 No 2 (2023): INTI Periode Februari 2023 Vol 17 No 1 (2022): INTI Periode Agustus 2022 Vol 16 No 2 (2022): INTI Periode Februari 2022 Vol 16 No 1 (2021): INTI Periode Agustus 2021 Vol 15 No 2 (2021): INTI Periode Februari 2021 Vol 15 No 1 (2020): INTI Periode Agustus 2020 Vol 14 No 2 (2020): INTI Periode Februari 2020 Vol 14 No 1 (2019): INTI Periode Agustus 2019 Vol 13 No 2 (2019): INTI Periode Februari 2019 Vol 13 No 1 (2018): INTI Periode Agustus 2018 Vol 12 No 2 (2018): INTI Periode Februari 2018 Vol 12 No 1 (2017): INTI Periode Agustus 2017 Vol 11 No 2 (2017): INTI Periode Februari 2017 More Issue