Article Per Year (5 Year)
p-Index From 2021 - 2026
4.162
P-Index
This Author published in this journals
All Journal Jurnal Algoritma JAIS (Journal of Applied Intelligent System) JMM (Jurnal Masyarakat Mandiri) Jurnal Teknik Informatika (JUTIF) Jurnal Kewarganegaraan Journal of Community Development Jurnal PkM MIFTEK Jurnal Algoritma Integrated : Journal Of Information Technology and Vocational Education
Muhammad Rikza Nashrulloh
Institut Teknologi Garut
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search
Journal : Jurnal Teknik Informatika (JUTIF)

 1 
DESIGNING MICROSERVICES ARCHITECTURE FOR SOFTWARE PRODUCT IN STARTUP Muhammad Rikza Nashrulloh; Ridwan Setiawan; Deni Heryanto; Ade Sutedi; Rickard Elsen
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 1 (2022): JUTIF Volume 3, Number 1, February 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.1.124

Abstract

Digital technologies in the world continue to develop in various sectors. This happens not only in developed countries, but also in developing countries such as Indonesia. A trend that continues to develop in the world of information technology becomes a consideration when starting a start-up company. In order to anticipate changes and developments in this trend, it is not uncommon for problems to arise that can directly affect the quality of service for startups. Therefore, a startup needs to create a dynamic culture and infrastructure for the introduction of new technologies. The problems start when startups mature, with more teams, more complex systems, and more traffic to websites or apps. At this stage, startups usually start thinking about scalability issues. to avoid problems, a startup must develop the right architecture for a software product, and a microservices architecture can be a solution to problems. A microservices architecture is an architectural style that structures an application as a collection of small self-contained services modeled around a business domain. This chapter describes the design of microservices architecture for software product in Startup Using Web Service Implementation Methodology .
ENTERPRISE ARCHITECTURE SYSTEM IN PRIVATE VOCATIONAL SCHOOL USING TOGAF ADM (CASE STUDY OF SMK Al-HIKMAH) Ridwan Setiawan; Muhammad Rikza Nashrulloh; Reski Ramadhani; Ade Sutedi
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 1 (2022): JUTIF Volume 3, Number 1, February 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.1.144

Abstract

Nowadays, the utilization of Information Technology has become the breadwinner or the main power in supporting the business processes of an organization, including educational organizations. The information technology utilization in the education sector, especially at Private Vocational High School (SMK) Al-Hikmah Tarogong Kaler, has not fully followed the current development where the application used in supporting the current activities has not been integrated between one field and another. This case provides the impact on the ineffectiveness of data redundancy because of the difficulty in accessing data and information between fields. Moreover, the use of unplanned systems in the master plan of system development (blueprint) can cause vulnerability to system disassembly which can also be caused by differences in data structure and system platform. The purpose of this study is to design the school's information system enterprise architecture. Besides, this research also aimed to create an enterprise system blueprint for Al-Hikmah Vocational High School. The method used in this study is The Open Group Architecture Framework Architecture Development Method (TOGAF ADM) and it is restricted only into the Migration Planning phase, and the budget for development is not discussed. The study reveals that the information systems and technology blueprints are compiled into the list of system needs and the needs in the form of application candidates for each business process are arranged based on priority needs
COMPARISON OF DATA MINING ALGORITHM FOR FORECASTING BITCOIN CRYPTO CURRENCY TRENDS Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 2 (2022): JUTIF Volume 3, Number 2, April 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.2.194

Abstract

The popularity of cryptocurrencies has been increasing in the approximately 10 years since their emergence in 2008. Bitcoin is the most popular and the most instrumental in the existence of cryptocurrencies. The price of coins in cryptocurrencies is the same as the price of shares in the capital market which always fluctuates and even tends to be more volatile than the stock market. This condition is very influential for actors in cryptocurrencies. This study aims to compare the Algorithm Forecasting so that it can be known the right algorithm in Forecasting the trend of Bitcoin. The algorithm used is Algorithm Supervised Learning that is Neural Network, Linear Regression, Support Vector Machine, Gaussian Process, and polynomial Regression. Accuracy was measured using a 10 Fold Cross-validation model and evaluation is done by Root Mean Square Error (RMSE). The results showed that the Algorithm Neural Network is an Algorithm Forecasting best with RMSE value 277,237 +/- 74,736 (micro: 287,208 +/- 0.000) among other Algorithms so that Neural Network can be used for Forecasting cryptocurrency Bitcoin.
COMPARISON OF CLASSIFICATION ALGORITHM AND FEATURE SELECTION IN BITCOIN SENTIMENT ANALYSIS Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.343

Abstract

Sentiment analysis is a process for extracting data in the form of textual, with the aim of obtaining information about the tendency to evaluate an object under study. Sentiments given by the general public can be used as a reference in making product decisions. Sentiment given can be in the form of positive, negative and neutral sentiments. One of the information technology products that has stolen enough attention in the last decade is Bitcoin. The purpose of this study is to compare several classification algorithms using Feature Selection. There are several classification algorithms that can be used for sentiment analysis, such as Deep Learning, Decission Tree, KNN, Naïve Bayes. Textual sentiment classification has constraints on datasets that have high dimensions. Feature Selection is a solution to reduce the dimensions of a dataset by reducing attributes that are less relevant. Feature Selection used is Information Gain and Chi Square. The method used to perform the comparison is by comparing the four classification algorithms to find the best algorithm, then comparing the Feature Selection to get the best between the two, then integrating the best classification algorithm and the best Feature Selection. The results showed that the best classification algorithm was Deep Learning with an accuracy value of 78.43% and a kappa of 0.625. The results of the comparison of Feature Selection, Information Gain get the best results with an average accuracy value of 63.79% and an average kappa of 0.382. The results of the integration of the best classification algorithm with the best Featrure Selection obtained an accuracy value of 78.63% and a kappa of 0.626 where the value was included in the Fair Classification category.
TWITTER SOCIAL MEDIA SENTIMENT ANALYSIS AGAINST BITCOIN CRYPTOCURRENCY TRENDS USING RAPIDMINER Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.289

Abstract

Cryptocurrency trends, especially Bitcoin, have gained a place in a group of people and there are even countries that already use Bitcoin as a legal transaction tool. The dynamics that occur in this Bitcoin trend make many new users. This lack of understanding of the technology can cast doubt on those who want to get started, so it is necessary to conduct sentiment analysis to increase knowledge of what Bitcoin is and how it works. This study aims to conduct a Sentiment Analysis regarding Bitcoin through Twitter social media, so that their opinion on this technology will be known. The method used is by using Tweet data that has been downloaded on the www.data.world.com website. The data is the result of using the Crawling technique, then sentiment analysis is carried out to classify a tweet into Neutral, Positive, or Negative. The results showed that from the 1998 dataset, 46.69% were classified as Neutral, then Positive, 43.54%, and 9.75% Negative.
THE PREDICTION OF PPA AND KIP-KULIAH SCHOLARSHIP RECIPIENTS USING NAIVE BAYES ALGORITHM Asri Mulyani; Dede Kurniadi; Muhammad Rikza Nashrulloh; Indri Tri Julianto; Meta Regita
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.297

Abstract

The aim of the research is was to predict the scholar recipient for Peningkatan Prestasi Akademik (PPA) and the Kartu Indonesia Pintar Kuliah (KIP-K). The prediction results of scholarship recipients will provide information in the form of the possibility of acceptance and non-acceptance of scholarship applicants. To achieve this goal, this study uses the Naive Bayes algorithm, where this algorithm predicts future opportunities based on past data by going through the stages of reading training data, then calculating the number of probabilities and classifying the values in the mean and probability table. The data analysis includes data collection, data processing, model implementation, and evaluation. The data needed for analysis needs to use data from the applicants for Academic Achievement Improvement (PPA) scholarship and the Indonesia Smart Education Card (KIP-K) scholarship. The data used for training data were 145 student data. The results of the study using the Naive Bayes algorithm have an accuracy of 80% for PPA scholarships and 91% for KIP-K scholarships.
WALLET-BASED AUTHENTICATION ON COLLEGE INFORMATION SYSTEM Rickard Elsen; Muhammad Rikza Nashrulloh; Ade Sutedi
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.473

Abstract

Since the widespread use of cryptocurrency, blockchain technology start to be adapted in various applications. Some businesses are already adopting blockchain technology because of its advantages such as data integrity and privacy. One of them is Web 3.0. Web 3.0 puts forward data decentralization so that users can choose what data will be sent to the server. User data is provided locally with the help of a crypto wallet and the server just receives wallet info. With this mechanism, user privacy can be maintained directly by the user himself. All data will be processed at the users' end first before being sent to the server. With the new mechanism of web 3.0 and the advantages of blockchain, we build an application to authenticate students' login activities and grant roles to them based on their wallets. In this paper, we use the prototyping model as the method to build the application. We managed to utilize students’ wallet addresses as credentials. And with the help of Web3 module, we managed to decentralize the authentication process. And as a result of the successful authentication process, students can access their data based on their roles.
DATA MINING CLUSTERING FOOD EXPENDITURE IN INDONESIA Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 6 (2022): JUTIF Volume 3, Number 6, December 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.6.331

Abstract

The availability of food in a country is determined by a conducive climate. Prolonged droughts, floods, and natural disasters, especially for food crop production areas, will have an impact on the availability of natural disaster conditions faced by all countries including Indonesia is the Covid-19 pandemic, where this will affect food security in Indonesia. Data mining is the process of discovering the hidden meaning of a very large data set. The technique used in this study is Data Mining Clustering and the validity index used is Davies-Bouldin. This study aims to determine the Food Security Strategy in Indonesia through the Data Mining Clustering process based on food expenditure data and the Indonesian people's food expenditure per capita. The methodology used is Cross Industry Standard for Data Mining using the K-Means and K-Medoids Algorithm. The best cluster for the K-Means Algorithm is K=7 with a value of 0.341 and for the K-Medoids Algorithm, it is K=7 with a value of 0.362. This research produces the best algorithm, namely K-Means with a value of 0.341, which has a smaller value than K-Medoids with a value of 0.362. The results showed that the regional. cluster with the highest average expenditure on food was cluster 5 covering the DKI Jakarta area, while the cluster with the lowest expenditure was cluster 6 covering Central Java, East Nusa Tenggara, Southeast Sulawesi, Gorontalo, and West Sulawesi. In cluster 6, it is necessary to implement a strategy to increase food security by increasing production capacity and food reserves in each region.
Co-Authors Ade Sutedi Ade Sutedi Ade Sutedi Ade Sutedi Ai Karlina Akib, Yasir Al Alawiyah, Dini Alhakeem, Reinalgy Azni Alinurdin, Rendi Apriliani, Insani Asgara, Zidan Asri Mulyani Dede Kurniadi Deni Heryanto Deni Heryanto Dewi Tresnawati Dewi Tresnawati Dzulkhomzah, Moh. Rival Eri Satria Eri Satria Faris, Salman Adam Fauzi, Sandi Muhtar Ilham Wahyudi Indri Tri Julianto Jaya, Mochamad Jipar, Muzaki Abdul Kifti, Jalaludin Latifah, Ayu Leni Fitriani Leni Fitriani, Leni M Rizki Nur Jamil Masripah, Ulpah Maulana, Moh. Alvin Apita Maulana, Yusep Meta Regita Mubarok, Muhammad Imam Husni Muh Fauzan Al - Haq Muhammad Azmi, Muhammad Munajat, Ikbal Muttaqin, Iswan Nurul Muttaqin, Moch Riefky Chaerul Muzaky, Rifky Khoerul Nurhakim, Sultan Jabar Nurmahmudi, Raihan Nurodin, Azmi Miftah Oktaviany, Sindi Patria, Dhika Muhamad Putra, Bangbang Hartono Putri Apriyanti Putri, Anisa Devisa Ramadhan, Tasya Shakila Ramdan, Galih Muhammad Reski Ramadhani Rickard Elsen Rickard Elsen Rickard Elsen Ridha, Muhamad Munna Ar Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rina Kurniawati Rina Kurniawati Rinda Cahyana Rinda Cahyana Riyandi, Fachrry Al-Fachrizzy Rizki, Ikbal Sholahudin, Hary Sidik, Ghimnastiar Moch Sri Rahayu SRI RAHAYU Yanti Yanti Yoga Handoko Agustin Yosep Septiana Yusnita Habsari Utami Zulfiansyah, Rezky