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All Journal Jurnal Buana Informatika Jurnal Transformatika Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Sistem Informasi dan Aplikasi Indonesian Journal of Computing and Modeling J-SAKTI (Jurnal Sains Komputer dan Informatika) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JIKA (Jurnal Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Malcom: Indonesian Journal of Machine Learning and Computer Science IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Abdimas
Yerymia Alfa Susetyo
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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IMPLEMENTATION OF TEXT INDEXING SYSTEM IN WEB-BASED DOCUMENT SEARCH APPLICATION USING MONGODB Frankie, Frankie; Susetyo, Yeremia Alfa
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.959

Abstract

The rapid growth of information technology has led to an increase in the amount of data stored in databases every day. Relational databases (SQL) that have been in use for a long time are now being developed with the emergence of NoSQL databases such as MongoDB. MongoDB stores data in BSON format and has a Text Indexes feature that is useful for speeding up text search on string content. This feature is particularly useful in searching for data in the form of texts or strings in large quantities. MongoDB's Text Indexes have a flexible schema that does not require a strict schema structure to index text data, unlike SQL databases that require columns with the appropriate data type to perform indexing. MongoDB's Text Indexes support more languages than SQL because they use an open-source text search engine called Apache Lucene. In this study, the researcher will implement Text Indexing on document data (PDF) that has been converted into text, then inserted into MongoDB before indexing. Afterward, the researcher will compare the performance of search queries between indexed and non-indexed data in MongoDB in terms of speed. The comparison results will be presented in tables and graphs to facilitate understanding. Based on the research conducted, it can be concluded that the use of the text indexing feature in MongoDB can speed up keyword or string search time. In the experiment conducted using 5000 data records, the results showed that the use of text indexing for searching 1 keyword resulted in a search speed improvement of 11705,88%, for searching 2 keywords it was 60833,33%, and for searching 3 keywords it was 44320%.
Pembangunan Stock Monitoring Application untuk Pembuatan Laporan Goods in Transit Menggunakan Flask Putra, Muhammad Al Frizal Deva Syach; Susetyo, Yeremia Alfa
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 2 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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Abstract

PT XYZ is the largest retail company in Indonesia. PT XYZ is definitely inseparable from problems regarding stock items. The problem is generally about the difference in stock of goods that can occur due to the condition of goods in transit from the warehouse to the store or vice versa (Goods in Transit), goods lost on the way, or the store has not made a goods receipt report. One strategy to overcome this problem is to build a Stock Monitoring application for web-based Goods in Transit (GIT) report generation using the Flask Framework. The application is built using the Python programming language and the Waterfall method. The application of the MVC (Model, View, Controller) architecture of the Flask Framework and the Waterfall method can support the development of the Stock Monitoring application because the code settings are easy to manage and each process is carried out systematically so that the workflow becomes structured and easy. The result of this research is the application of the Flask Framework and the Waterfall method in the Stock Monitoring application which is used to generate GIT reports to overcome the problem of missing stock.
Implementasi Algoritma LSTM pada Aplikasi Optical Character Recognition Berbasis Website Menggunakan Tesseract OCR Setyadi, Alpha Fausta Ikrar; Susetyo, Yeremia Alfa
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 2 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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Abstract

The practicality of digital document processing has made various companies and organizations switch physical documents to digital. However, the process of extracting data from physical documents manually requires effort and is prone to input errors due to human error. Optical Character Recognition (OCR) technology can be a solution to this problem. OCR is used to recognize letters or characters in an image, and then stored into text data on a computer. In this research, the implementation of OCR technology on a web-based application with Long Short-Term Memory method. Based on accuracy testing, the average error value at the character level is 6.56% and at the word level is 9.98%. From the results obtained, it shows that the application of OCR technology with Long Short-Term Memory method on web applications can be the right solution in the process of extracting data from physical document.
Geospatial API Architecture with Laravel for Agricultural Land Suitability Detection System Susetyo, Yerymia Alfa
Sistemasi: Jurnal Sistem Informasi Vol 12, No 3 (2023): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v12i3.2844

Abstract

Identification of agricultural land suitability involves a variety of variables that are heterogeneous. The heterogeneity of spatially-based climate and physiographic data is in fact quite complex to solve. Therefore, a spatial-based system architecture that meets the criteria of inclusiveness, collaboration, capacity development, and quick request-response is needed. The research aims to build an API geospatial architecture with Laravel for Agricultural Land Suitability Detection Systems. The geospatial API architecture in this study was built using RESTFul Web services on the Laravel Framework. Simulation architecture involves five nodes as a server and one node as a client. Six main API were produced in this study. Four services are derived from four severs, where services are services related to spatial data (area, altitude, slope, and rainfall). Meanwhile, two other services, relating to conventional information zoning of agricultural land suitability generated by Server 5. The service generated by the last server was successfully implemented on the client-based web-based interactive map application.
Digital Transformation in Religious Organizations: The Application of Data Management for Church in Magelang Fibriani, Charitas; Kristiyani, Dian Novita; Susetyo, Yeremia Alfa; Yulia, Hanita
Jurnal Abdimas Vol. 28 No. 2 (2024): December 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/8mjbj740

Abstract

The Plengkung Javanese Christian Church Synod (GKJP) is one of the Protestant church groups located in several areas on the island of Java. The condition of data recording in GKJP is still done by recording using book media. This causes data inconsistency or redundancy. GKJP also requires data management that can be used to obtain classes for congregation groups according to several needs. This Community Service aims to build the GKJP Magelang City Congregation Information System, where this system will focus on recording congregation data so that it is hoped that the problems of inconsistency and redundancy can be resolved and can utilize the congregation data to obtain certain criteria groups using the classification analysis menu.
Predict Airline Customer Satisfaction using a Machine Learning Model Suwito, Yoel Dinata; Susetyo, Yeremia Alfa
SISTEMASI Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5868

Abstract

Customer satisfaction is a strategic factor for the sustainability of airline businesses amid increasingly intense competition in the aviation industry. This study aims to predict airline customer satisfaction using an Artificial Neural Network (ANN) approach by leveraging a publicly available Kaggle dataset containing 22 airline service features. Two ANN architectures were developed, differing primarily in the number of hidden layers, the number of neurons, and the application of Batch Normalization and LeakyReLU in the second model. The experimental results show that the first ANN model achieves an accuracy of 92.31%, while the second model attains significantly higher performance, with an accuracy of 95.75% on the test dataset. The second model also demonstrates a strong balance between precision and recall (0.94–0.97), with an average F1-score of 0.95–0.96 and a minimal number of misclassifications. These results confirm that employing a more complex ANN architecture can deliver highly accurate predictions of customer satisfaction. The implementation of ANN-based predictive models not only enhances passenger experience quality but also strengthens customer loyalty and helps airlines maintain long-term competitiveness.
Co-Authors Adisattrio, Yefta Adiyoso, Wibisono Ajeng Febriana Rahmawati Alpha Adarrani Wibowo Putri Anggraeni, Martina Meita Aryanto, Muhamad Rizky Dhean Audric Tjhoernandes Avrylya, Tessalonica Putry Brian Pratama Putra Cahyo Nugroho Calvin Ravelino Candra Wijayanto Cantika, Berliana Nala Charitas Fibriani Daniswara, Bayu Andy Delfini Tinma Pandoi Dian Novita Kristiyani Dinata, Dimas Ridho Dwi Hosanna Bangkalang Elsie Naresvari Farid Arya Nugraha Fatich, Steven Arycena Firmandicky, Alief Yuwastika Frankie Frankie, Frankie Hanita Yulia Hanusia Manuel Oktrivania Zamili Ivan Andika Surya Josua Ade Saputra Karolus Thias Widagdo Kejora, Cahyo Bintang Laksono Trisnantoro Maulana, Irvan Dhimas Muhammad Fahmi Haryono Adi Nina Setiyawati Oky Dwi Arianto Paseleng, Fatricius Pradipta, Rafael Deandra Pratama, Raka Arya Pratyaksa Ocsa Nugraha Saian Priwidika Lingga Maheswara Purbaningtyas, Mikha Kurnia Anggi Putra, Muhammad Al Frizal Deva Syach Ramos Somya Rizky Nandang Pratama Santoso, Wahyu Aji Setyadi, Alpha Fausta Ikrar Suwito, Yoel Dinata Syahren Aulia Achsan Tania Rachel Teguh Indra Bayu Valentino, Jonathan Wibisono Adiyoso Wibowo, Andrean Vini Bimo Arya Wicaksono, David Aryo Wijaya, Ricky Arindra Yuichi, Michael Yulius