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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Aplikasi Statistika & Komputasi Statistik Prosiding Seminar Nasional Official Statistics
Ridho, Farid
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Mathematics Social Sciences

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Pembangunan Sistem Informasi Berbasis Web Direktori Pariwisata Menggunakan Arsitektur REST API di Badan Pusat Statistik Syibli, Muhammad; Ridho, Farid
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1811

Abstract

Indonesia has a large potential tourism industry so the government needs to promote it well through technology-based tourism information management. In addition, there is a need for a forum to disseminate the results of tourism information management to the community by integrating it with the Webentry and Wilkerstat systems. Based on this, it is necessary to build a web-based tourism directory system at BPS. The design of the system interface uses the card sorting method to organize the layout of features based on the principle of visual and information hierarchy. Then, there is the use of Representational State Transfer Application Programming Interface (REST API) to implement public information disclosure. Then, the tourism directory system is built using a three-tier client-server architecture with the CodeIgniter 3 framework and Bootstrap 4. The system development method used is the Software Development Life Cycle (SDLC) waterfall model. After the system development stage is complete, it is necessary to test the features using the black box testing method and the results are as expected. Furthermore, there is a system usability test using the System Usability Scale (SUS) survey with a final score of 80.17 or good category.
Predicting Startup Success Using Machine Learning Approach Ningrum, Icha Wahyu Kusuma; Ridho, Farid; Wijayanto, Arie Wahyu
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8338

Abstract

Predicting startup success is important because it helps investors, entrepreneurs, and stakeholders allocate resources more efficiently, minimize risks, and enhance decision-making in an uncertain and competitive environment. Therefore, investors need to predict whether a startup will succeed or fail. Investors conduct this assessment to determine if a startup is worthy of funding. The company's founders mark success here by receiving a sum of money through the Initial Public Offering (IPO) or Merger and Acquisition (M&A) process. If the startup closes, we will consider it a failure. The data used consists of 923 startup companies in the United States. We carried out the classification using four methods: Random Forest, Support Vector Machines (SVM), Gradient Boosting, and K-Nearest Neighbor (KNN). We then compare the results from the four methods with and without feature selection. We determine the feature selection based on the relative importance of each method. The results of this study indicate that the Random Forest method with feature selection has the best accuracy, precision, recall, and F1 score than the other methods, respectively 81.85%, 80.19%, 87.09%, and 83.44%.
Implementation of a RESTful API-Based Evolutionary Algorithm in a Microservices Architecture for Course Timetabling Zuhdi Ali Hisyam; Ridho, Farid; Setiyawan, Arbi
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 2 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v16i2.796

Abstract

Introduction/Main Objectives: Implement an evolutionary algorithm within a RESTful API for a course timetabling system that employs a microservices architecture. Background Problems: The current course timetabling at Politeknik Statistika STIS uses the third-party application (aSc Timetables), which lacks a generator as a service, resulting in its inefficiency due to the lack of integration with SIPADU NG. Novelty: The evolutionary algorithm is built as a service (RESTful API) within a microservices architecture and supports custom constraints for timetables. Research Methods: One of the evolutionary algorithm families, the (1+1) evolutionary strategy, is implemented and used to create a course timetable 1000 times. Each course timetable created will have its cost calculated to assess the goodness of the algorithm implementation. The developed RESTful API is also evaluated through black box testing. Finding/Results: For the odd semester data, 40.5% of the trials yielded a cost value between 4 and 5, while for the even semester, all trials produced a cost value below 1. The resulting cost value is close to 0, which indicates that the timetable created has minimal violations.  Additionally, black box testing concluded that the service operates as expected, delivering the anticipated output.
Analisis Keamanan Aplikasi Berbasis Web di Lingkungan BPS RI Pandudinata, Maulana; Ridho, Farid
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2109

Abstract

Security is principal factor that matters in Web Applications. Penetration Testing now become the standard for security testing of applications before released to the public. Security analysis of the Functional Position Information System (JAFUNG) web application from BPS RI is conducted because BPS RI has important applications that assist in implementing statistical business processes. Therefore, conducting Grey-Box Penetration Testing is important to assess how resistant that application is. With PTES (Penetration Testing Execution Standard) testing method 2014 version for procedures and OWASP Risk Rating Methodology 2021 version for vulnerability assessment, counting attack scenarios by the BSSN Top 10 Vulnerabilities. Hopefully after conducting security testing, systematic analysis and assessment of vulnerabilities for the application will be obtained, counting a vulnerability category rating that accurately reflects the actual conditions, and hereafter, this research can be a reference for BPS in testing the security of applications to ensure the safety of statistical data.
Multi-Source Data Fusion For Data Extraction and Integration of Scientific Publications in Academic Institution STIS Maulidya, Luthfi; Suadaa, Lya Hulliyyatus; Wijayanto, Arie Wahyu; Ridho, Farid
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.87050

Abstract

Scientific research publication data is one of the most important data required by academic and research institution because it can be used as a reference to measure the performance of lecturers in research activities, to assess study programs and university accreditation, to identify research trends, and to plan research development policies and strategies. However, to fulfill these data needs, research data must be collected and integrated from various data sources due to the diversity of databases. One of the portals that provides scientific research publication data for universities in Indonesia is Sinta (Science and Technology Index). The integrated research databases in Sinta are Scopus, Web of Science (WoS), Garba Rujukan Digital (Garuda), and Google Scholar. However, there are limitations, namely that some scientific research publication metadata in Sinta are still not covered, such as Digital Object Identifier (DOI), abstract, author's full name, publication/journal name, publication type, and number of citations. In addition, each data source has a different data format, which requires data processing so that it can be integrated. Processing and integrating research data from different sources will be very inefficient if it is done manually and not computerized. Therefore, this study proposes a data engineering pipeline framework for the extraction and integration of scientific research publication data from various data sources using the multi-source data fusion method with the Unified Cube methodology approach, which is then implemented by building a web interface. We use Politeknik Statistika STIS, Jakarta as a case study. This framework refers to the data engineering lifecycle and multi-source data fusion method based on abstraction levels for the extraction and integration of scientific research publication data. Then, the transformed data will be classified using rule-based classification. The results show that the accuracy of the framework was more than 90% and the accuracy of the classification results was 87.5%.
Co-Authors Arie Wahyu Wijayanto Maulidya, Luthfi Ningrum, Icha Wahyu Kusuma Pandudinata, Maulana Setiyawan, Arbi Suadaa, Lya Hulliyyatus Syibli, Muhammad Zuhdi Ali Hisyam