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All Journal Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sisfokom (Sistem Informasi dan Komputer) Mulia International Journal in Science and Technical Jurnal Accounting Information System (AIMS) Teknika Inovasi Jurnal Pengabdian Masyarakat (IJPM) Jurnal Accounting Information System (AIMS) BACA: Jurnal Dokumentasi dan Informasi
Jack Febrian Rusdi
Universitas Teknologi Bandung
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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The Development of Smart Campus System in Indonesia Hardi, Richki; Kamalrudin, Massila; Hashim, Ummi Rabah; Yana Hendriana; Gunawan; sumardi; Yustian; Sigit Sigalayan; Jack Febrian Rusdi; Agus Sasmito; Apri Junaidi; Anastasia Lidya Maukar
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dependence on technology is complicated to avoid and very difficult to separate in the digital era. It impacts the education system, especially in Indonesian higher education. Higher education institutions in Indonesia have begun to implement information and communication technology-based systems within the campus environment. Encouraged from all academic communities in higher education who expect comfort so that the importance of the role of technology. Smart Campus comes as a result of a system that uses technology and the internet as an intermediary. Smart Campus is expected to be a campus that can educate students with IT-managed methods. The smart campus is a campus that combines, combines, combines, and implements teaching and learning processes using information technology. So that all systems that support the teaching and learning process also use technology. The smart campus system can be implemented starting from the new student admission system, campus academic system, online examination system, library information system, and tuition payment system. With the smart campus, the system will reduce errors in doing work. Of course, it will also reduce the costs to be incurred by the campus.
Sistem Pelacakan Lokasi Pelaporan Petugas Lapangan Irigasi Provinsi Sumatera Barat Berbasis GPS Smartphone dan WebGIS Budi Sunaryo; Muhammad Ilhamdi Rusydi; Jack Febrian Rusdi; Rifda Suriani; Syafril Daus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 2 (2019): Agustus 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1521.683 KB) | DOI: 10.29207/resti.v3i2.957

Abstract

Tracking the location from the side of the report and the position of the reporter in real-time is very much needed in validating the performance of irrigation field officers. The location tracking system represented in smartphone applications, and digital maps are a practical solution for supervisors in monitoring the performance of field officers. The Global Positioning System (GPS) module on Android smartphones and the Web Geographic Information System (WebGIS) are supporting technologies for the system. Each location coordinate on the report will be sent automatically to the MySQL database server, then each coordinate location of the field officer will be sent to the Firebase Realtime Database, coupled with a database synchronization system to handle reports offline when officers are in areas that do not have internet access. Database synchronization plays a role in handling report data stored in the SQLite database on an Android smartphone with a MySQL database server. This system is useful for supervisors in controlling and monitoring the performance of irrigation field officers and can be used as material for decision making. After being implemented in several Irrigation Areas in West Sumatra Province by 113 users consisting of 13 supervisors and 100 field officers, the supervisors can track the location of the report, follow the position of field officers in real-time and send reports offline.
PERAN TEKNOLOGI INFORMASI PADA PARIWISATA INDONESIA Jack Febrian Rusdi
Jurnal Accounting Information System (AIMS) Vol. 2 No. 2 (2019)
Publisher : Universitas Ma'soem

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (617.855 KB) | DOI: 10.32627/aims.v2i2.78

Abstract

Information and Communication Technology (IT) is a part that is firmly attached to the progress of world tourism. Unfortunately, this research on the role of IT has not received much attention from various studies produced in Indonesia. This article discusses the part of IT that can implement in multiple aspects of tourism. The method used is a literature review sourced from the Garuda portal. The study provides various research areas that can be carried out within the tourism sector, specifically to support the growth of tourism research and information technology in Indonesia.
Enhance Document Contextual Using Attention-LSTM to Eliminate Sparse Data Matrix for E-Commerce Recommender System - Hanafi; Anik Sri Widowati; - Jaeni; Jack Febrian Rusdi
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1233

Abstract

E-commerce has been the most important service in the last two decades. E-commerce services influence the growth of the economic impact worldwide. A recommender system is an essential mechanism for calculating product information for e-commerce users. The successfulness of recommender system adoption influences the target revenue of an e-commerce company. Collaborative filtering (CF) is the most popular algorithm for creating a recommender system. CF applied a matrix factorization mechanism to calculate the relationship between user and product using rating variable as intersection value between user and product. However, the number of ratings is very sparse, where the number of ratings is less than 4%. Product Document is the product side information representation. The document aims to advance the effectiveness of matrix factorization performance. This research considers to the enhancement of document context using LSTM with an attention mechanism to capture a contextual understanding of product review and incorporate matrix factorization based on probabilistic matrix factorization (PMF) to produce rating prediction. This study employs a real dataset using MovieLens dataset ML.1M and Amazon information video (AIV) to observe our ATT-PMF model. Movielens dataset represents of number sparse rating that only contains below 4% (ML.1M). Our experiment report shows that ATT-PMF outperforms more than 2% on average than previous work. Moreover, our model is also suitable to implement on huge datasets. For further research, enhancement of product document context will be a good factor in eliminating sparse data problems in big data problems.
PERAN TEKNOLOGI INFORMASI PADA PARIWISATA INDONESIA Jack Febrian Rusdi
Jurnal Accounting Information System (AIMS) Vol. 2 No. 2 (2019)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v2i2.336

Abstract

Information and Communication Technology (IT) is a part that is firmly attached to the progress of world tourism. Unfortunately, this research on the role of IT has not received much attention from various studies produced in Indonesia. This article discusses the part of IT that can implement in multiple aspects of tourism. The method used is a literature review sourced from the Garuda portal. The study provides various research areas that can be carried out within the tourism sector, specifically to support the growth of tourism research and information technology in Indonesia.
Forecasting Model of Export and Import Value of Oil and Gas Using Gated Recurrent Unit Method Ilham Adji Saputra; Anik Vega Vitianingsih; Yudi Kristyawan; Anastasia Lidya Maukar; Jack Febrian Rusdi
Teknika Vol. 13 No. 2 (2024): Juli 2024
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v13i2.861

Abstract

Indonesia’s natural resources are abundant, including oil and gas. It is one of the countries active in international trade, including exports and imports. Oil and gas exports are a significant source of income for the country, encouraging economic growth. Oil and gas imports are very important to meet domestic energy needs, which continue to increase in demand. Increasing oil and gas imports can increase the trade balance, which can affect the country’s economic stability if the value of imports exceeds the value of exports. Forecasting is a solution to overcome these problems by forecasting the value of oil and gas exports and imports. The gated recurrent unit (GRU) method is used for forecasting in this study because it has a simple computation and fairly high accuracy. The dataset used is monthly time series data from 1993 to 2023 from the website of the Badan Pusat Statistik (BPS). The MAPE results on the GRU model forecast the value of oil and gas exports and imports at 12.19% and 14.30%, respectively. The best average forecasting of export and import values obtained a MAPE of 13.38%.
Sentiment Analysis of Public Responses on Social Media to Satire Joke Using Naive Bayes and KNN Putra Selian, Rasyid Ihsan; Vitianingsih, Anik Vega; Kacung, Slamet; Lidya Maukar, Anastasia; Febrian Rusdi, Jack
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13721

Abstract

This study examines the use of Satire Joke as a humorous communication style in conveying criticism of the government through social media. Satire Joke is often used to depict the government's inability to address important social issues, such as slow bureaucratic processes and unfulfilled political promises. The aim of this research is to analyze public sentiment towards Satire Joke expressed on the YouTube social media platform. The methods used in this study are Naïve Bayes and K-Nearest Neighbors (KNN) due to their effectiveness in data classification. The results of this study are expected to help gain an understanding of social issues for the community and public knowledge. This research is also expected to contribute to the development of sentiment analysis methods in the future. The analysis results show that 400 data have neutral sentiment, 850 data have negative sentiment, and 947 data have positive sentiment. Based on testing, both Naive Bayes and KNN methods show good performance. The Naive Bayes method achieved the best accuracy of 90.29%, while the KNN method achieved an accuracy of 60.75%.
Comparison of Machine Learning Algorithms in Detecting Tea Leaf Diseases Ihsan, Candra Nur; Agustina, Nova; Naseer, Muchammad; Gusdevi, Harya; Rusdi, Jack Febrian; Hadhiwibowo, Ari; Abdullah, Fahmi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5587

Abstract

Tea is one of the top ten export products sent from Indonesia to foreign countries. However, in recent years, the amount of tea leaf exports from Indonesia has decreased, although the value of the export impacts the country’s economic structure. In addition to market competition, Indonesia must maintain tea leaf production so that the increase in export decline is not significant or even increases tea leaf export production. To improve production quality and reduce production costs, early detection of tea leaf diseases is necessary. This study aims to classify tea leaf images for early detection of tea leaf disease so that appropriate treatment can be carried out early. This study compares machine learning algorithms to determine the best algorithm for detecting tea leaf diseases. The algorithms tested as performance comparisons in classifying tea leaf diseases are random forest (RF), support vector classifier (SVC), extra tree classifier (ETC), decision tree (DT), XGBoost classifier (XGB), and convolutional neural algorithms. Network (CNN). As a result, the average accuracy performance generated by ETC produces a higher value than other algorithms, i.e., getting an average accuracy performance of 77.47%. Another algorithm, SVC, has an average accuracy of 76.57%, RF of 76.12%, DT of 65.31%, XGB of 71.62%, and the lowest is CNN of 59.08%. ETC has been proven to be the most superior machine learning algorithm for detecting tea leaf diseases in this study.
KOLABORASI PENELITI DI ERA TEKNOLOGI INFORMASI DAN KOMUNIKASI Febrian Rusdi, Jack; Gurat Baktina, Tedja; Gumilar Hadiningrat, R.; Sunaryo, Budi; Laurenty, Fretycia
BACA: Jurnal Dokumentasi dan Informasi Vol. 41 No. 1 (2020): BACA: Jurnal Dokumentasi dan Informasi (Juni)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.baca.v41i1.585

Abstract

Advances in information and communication technology have an impact on increasing the number ofscientific publications in the world. Scientific papers are an indicator of a country's progress in theacademic field. One strategy used to improve the quality of scientific publications is throughcollaboration between researchers. From various study result searches, there are not many studies thatdiscuss the collaboration of researchers. The purpose of this study is to produce one of the fundamentalstudies on research development in Indonesia. The method used in this study is the study of literature.This article contributes to the collaboration picture of researchers, including the background ofcollaboration and aspects that affect collaboration, as well as the contribution of Indonesian research interms of information technology to support research for researcher.
Sentiment Analysis on Ajaib App Using the SVM Method Minggow, Lingua Franca Septha; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Rusdi, Jack Febrian
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 4 (2025): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i4.2402

Abstract

The rapid growth of investment applications has transformed trading accessibility, yet user dissatisfaction persists, particularly regarding transaction delays, technical issues, and inadequate customer support. This study addresses a research gap in sentiment analysis, specifically in the context of the Ajaib investment application, by employing a Support Vector Machine (SVM) model combined with lexicon-based labelling. The objective is to classify user-generated Google Play reviews into positive, negative, and neutral sentiments, providing actionable insights for service improvement. The research follows a structured methodology comprising data crawling, text pre-processing (cleaning, case folding, tokenization, stopword removal, and stemming), TF-IDF feature extraction, and supervised classification with SVM. Model validation utilises a 3×3 confusion matrix to calculate accuracy, precision, and recall, thereby ensuring a robust performance evaluation. Experimental results demonstrate that the SVM classifier achieves high accuracy in sentiment polarity classification, highlighting its suitability for text-based sentiment analysis in the financial domain. The distinct contribution of this research is its implementation of SVM for sentiment classification for Ajaib, offering a replicable framework for leveraging user feedback to enhance digital investment platforms. These findings contribute to the development of automated sentiment analysis systems that support data-driven decision-making for improving customer satisfaction.
Co-Authors - Jaeni Agus Sasmito Ai Nurhayati Anastasia Lidya Maukar Anastasia Lidya Maukar Anik Sri Widowati Anik Vega Vitianingsih Anik Vega Vitianingsih Apri Junaidi, Apri Budi Sunaryo Efendi, Kacung Emaliana Kasmuri Fahmi Abdullah, Fahmi Fannya, Puteri Fretycia Laurenty Gumilar Hadiningrat, R. Gunawan Gurat Baktina, Tedja Hadhiwibowo, Ari Hanafi Hanafi Harya Gusdevi Hashim, Ummi Rabah Ihsan, Candra Nur Ilham Adji Saputra Kamalrudin, Massila Laurenty, Fretycia Lidya Maukar, Anastasia Minggow, Lingua Franca Septha Muchammad Naseer Norazlina Shafie Nova Agustina Nurazlina Shafei Putra Selian, Rasyid Ihsan R Gumilar Hadiningrat Richki Hardi Rifda Suriani Rusydi, Muhammad Ilhamdi Saepudin Saepudin Sazilah Salam Sigit Sigalayan Siti Feirusz Ahmad Fesol Slamet Winardi Suci Tresna Dewi Handayani SUMARDI Sunaryo, Budi Sunaryo, Budi Syafril Daus Tedja Gurat Baktina Yana Hendriana Yudi Kristyawan Yustian