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Repeater: Publikasi Teknik Informatika dan Jaringan
Published by Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia
ISSN : 30467284     EISSN : 30467276     DOI : 10.62951
Core Subject : Science,
Computer Science & IT
Repeater : Publikasi Teknik Informatika dan Jaringan berisikan naskah hasil penelitian di bidang Teknik Informatika dan Jaringan
Arjuna Subject : Ilmu Komputer (semua kategori) - Jaringan Komputer dan Komunikasi
Articles 94 Documents
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Penggunaan Metode Rough Set untuk Menentukan Tingkat Kesiapan Siswa dalam Menghadapi ANBK di SMP Negeri 2 Kuala Harninda Br Keliat; Novriyenni Novriyenni; Tio Ria Pasaribu
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 3 (2025): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i3.619

Abstract

The Computer-Based National Assessment (ANBK) is an essential instrument designed to comprehensively measure student competence, including literacy, numeracy, and character aspects. However, in practice, many students still face various challenges during preparation, such as cognitive limitations, psychological readiness, and technical barriers, which affect their overall readiness to participate in ANBK. This study aims to analyze the readiness level of students at SMP Negeri 2 Kuala by employing the Rough Set method. The variables examined include digital literacy, subject matter understanding, psychological readiness, and school facility support. Data were collected from 250 ninth-grade students through structured questionnaires and subsequently processed using the Rosetta software to perform attribute reduction and generate decision rules. The findings indicate that digital literacy, subject matter understanding, and psychological readiness are the most influential variables in determining student readiness, while facility support serves only as a complementary factor. The extraction process generated seven decision rules with an accuracy level of 100%, which effectively classified students into three readiness categories: highly ready, ready, and less ready. These results confirm that the Rough Set method is highly effective for identifying dominant factors and producing decision rules that can guide schools in developing targeted strategies to enhance student readiness for ANBK.
Implementasi Sistem Penunjang Keputusan untuk Menentukan Trayek Terbaik Shuttle Daytrans Menggunakan Metode Weighted Product (WP) Berbasis Web Rafi Adli Rudianto; Khaerul Ma'mur
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 4 (2025): Oktober: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i4.636

Abstract

The development of information technology has accelerated digitization in various sectors, including in the decision-making process. In the DayTrans Shuttle service, the selection of the best route is still done manually using Microsoft Excel. This process is time-consuming, inefficient, and has the potential to cause errors and subjectivity. The purpose of this study is to design and develop a web-based decision support system by applying the Weighted Product (WP) method to determine the most optimal shuttle route objectively and efficiently. The research data was obtained through interviews, observations, and literature studies, then analyzed according to system requirements. The development was carried out through the stages of requirements analysis, database and interface design, implementation, and testing. The developed system is equipped with features for managing criteria data, alternative routes, weight calculations, and real-time presentation of recommendation results. The research results show that the system functions well, is able to speed up the route selection process, and produces accurate and transparent recommendations. Thus, this system is expected to improve DayTrans' operational efficiency while supporting the quality of inter-city transportation services.
Analisis Sentimen pada Ulasan Aplikasi JakLingko Menggunakan Metode Naïve Bayes Ricardus Mba Dala Pati; Eka Kusuma Pratama; Tuslaela Tuslaela
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 4 (2025): Oktober: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i4.638

Abstract

JakLingko is a digital-based public transportation integration system developed to facilitate access to various transportation modes in Jakarta. Along with the increasing number of users, reviews on the JakLingko application reflect user experiences and perceptions. This study aims to analyze the sentiment of user reviews on the Google Play Store using the Naïve Bayes method. Data collection was conducted through web scraping, resulting in 3,260 reviews. The data were preprocessed, sentiment-labeled, and classified using Orange Data Mining. The research applied a quantitative experimental approach with a machine learning framework. The classification results showed that neutral sentiment dominated user reviews, followed by negative and positive sentiments. The Naïve Bayes model achieved 100% accuracy based on the confusion matrix and other evaluation metrics such as precision, recall, and F1-score. The findings highlight that Naïve Bayes can be a reliable approach for analyzing public opinion and serve as a reference for evaluating and improving digital service applications.
Pengembangan Aplikasi Catatan Keuangan Untuk Usaha Mikro Kecil Menengah (UMKM) Berbasis Flutter Fafions Osama Effendy; Moh. Noor Al Azam; Rr. Prastoeti
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 2 (2025): April: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i2.416

Abstract

This paper aims to overcome the problem of manual financial recording that is still commonly used by MSMEs, which often causes data loss and inefficiency in financial management. To answer this challenge, researchers developed a mobile-based financial recording application using Flutter and a number of available supporting packages. This application is designed to be able to record and store income and expenditure data directly on the user's mobile device, making it easier for MSMEs to monitor their financial condition in real time. The development was carried out using a waterfall model approach, which includes the stages of analysis, design, implementation, and testing. To test the functional performance of the application, the Black Box testing method is used to assess the accuracy and reliability of the features without looking at the internal code structure. The test results show that all features can function as they should and the application is considered effective in supporting digital MSME financial recording.
Analisis Penerapan Business Intelligence dan Knowledge Management dalam Strategi Retensi Pelanggan pada Platform Streaming Netflix Indonesia Anggi Ismiyanti; Diana Puspita Sari; Nauroh Nazhiifah; Tata Sutabri
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 4 (2025): Oktober: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i4.666

Abstract

The development of digital technology has brought about significant transformations in the global entertainment industry, including in Indonesia. One manifestation of this change is evident in the presence of streaming platforms like Netflix, which have altered consumer consumption patterns for audio-visual content. This study aims to analyze how Netflix Indonesia utilizes Business Intelligence (BI) and Knowledge Management (KM) to maintain and increase customer loyalty. This research uses a qualitative descriptive method, collecting data from various scientific literature, industry reports, and relevant online sources. The results show that the implementation of BI enables Netflix to analyze user behavior, understand viewing preferences, and provide more personalized content recommendations. Meanwhile, KM plays a crucial role in internal knowledge management, content development, and service innovation. The synergy between BI and KM has been proven to support Netflix's strategy in improving user experience, retaining existing customers, and attracting new ones in the increasingly competitive Indonesian market.
Analisis Perbandingan Metode ARIMA dan Holt untuk Peramalan Harga Saham PT Telkom Indonesia (TLKM) Azriel Ikmal Choiry Sulaiman
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 1 (2026): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i1.762

Abstract

The dynamic fluctuations in stock prices present a major challenge for investors in making informed decisions. To anticipate such uncertainties, forecasting methods that can provide accurate predictions are required. This study compares two time series forecasting methods Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (Holt) in predicting the stock prices of PT Telkom Indonesia (TLKM). The dataset consists of monthly closing prices from January 2018 to December 2023. The performance of each model is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results show that the ARIMA(1,1,1) model yields higher predictive accuracy than the Holt method, with MAE of 787.71, MSE of 771,844.2, and RMSE of 878.55. In contrast, the Holt method records a MAE of 837.19, MSE of 878,393.4, and RMSE of 937.23. These findings confirm that ARIMA is superior in capturing the complex patterns of stock price movements and is more effective in volatile market conditions such as the stock exchange.
Penerapan Metode Fuzzy Mamdani dalam Menentukan Kelayakan Penerima Bantuan Sosial Juniar Hadianti; Dinda Sri Damayanti; Khairul Saleh
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 1 (2026): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i1.772

Abstract

The process of determining eligibility for social assistance recipients is often constrained by subjective assessments and uncertainty in decision-making criteria. This condition can lead to inaccurate targeting and unfair distribution of aid. Therefore, an appropriate decision support method is required to handle data uncertainty effectively. This study aims to apply the Fuzzy Mamdani method to determine the eligibility of social assistance recipients based on several assessment criteria. The criteria used in this study include monthly income, number of dependents, and housing conditions. The research method consists of data collection, fuzzification, formulation of fuzzy rules, inference using the Mamdani approach, and defuzzification to obtain a crisp output value. The results show that the Fuzzy Mamdani method is able to classify recipients into eligible and non-eligible categories more flexibly compared to conventional methods. The generated eligibility values reflect real conditions more accurately by considering degrees of membership for each criterion. The implementation of this method can assist decision-makers in improving the accuracy, objectivity, and fairness of social assistance distribution. This research is expected to contribute to the development of intelligent decision support systems in the social welfare sector.
Implementasi Metode Fuzzy Mamdani pada Sistem Penentuan Kelayakan Beasiswa Widya Ari Rizki; Raja Syahmuda Siregar; Khairul Saleh
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 1 (2026): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i1.773

Abstract

The process of determining scholarship eligibility often faces challenges related to subjectivity and uncertainty in assessment criteria, which can result in inaccurate and unfair decisions. Scholarship selection generally involves multiple criteria, such as academic achievement, family economic conditions, and supporting factors that are difficult to evaluate using conventional decision-making methods. Therefore, an appropriate decision support approach is required to handle such uncertainty effectively. This study aims to implement the Fuzzy Mamdani method in a decision support system to determine scholarship eligibility more objectively and accurately. The research method consists of data collection, fuzzification of input variables, formulation of fuzzy rules, inference using the Mamdani approach, and defuzzification using the centroid method to obtain a crisp eligibility value. The results show that the Fuzzy Mamdani method is capable of producing flexible eligibility scores by considering the degree of membership of each criterion. The generated output reflects real conditions more comprehensively compared to traditional methods. The implementation of this method can assist decision-makers in improving transparency, consistency, and fairness in scholarship selection. This research is expected to contribute to the development of intelligent decision support systems in the field of educational assessment.
Pengembangan Sistem Informasi Pengaduan Pelayanan Puskesmas Waimangura untuk Meningkatkan Efisiensi dan Akurasi Data Pasien dengan Metode Prototype Yumiana Mema; Gergorius Kopong Pati; Emirensiana Dappa Ege
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 1 (2026): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i1.784

Abstract

Health services at the Puskesmas (Community Health Center) are an important sector directly related to the community. However, there are still various challenges in patient data management and handling complaints that can hinder service efficiency. One of the efforts to improve service quality is by developing a complaint information system that can efficiently manage and record patient complaints. This study aims to develop a complaint information system for services at the Puskesmas Waimangura using the Prototype method. This method was chosen because of its ability to produce system prototypes that can be immediately tested and developed according to user needs. The system is designed to allow patients to submit complaints related to the services received, as well as enabling Puskesmas staff to follow up on and record each complaint systematically. With the implementation of this system, it is expected to increase efficiency in managing complaint data, speed up problem resolution processes, and improve accuracy in recording patient and complaint data. The results of prototype testing show that this system simplifies the complaint process and provides convenience for staff in following up on patient complaints. The implementation of this information system is expected to improve the quality of services at Puskesmas Waimangura and accelerate responses to issues faced by patients.
Optimasi Prediksi Harga Saham BBNI melalui Integrasi Proses ETL dan Algoritma Long Short-Term Memory I Gusti Ngurah Rangga Mahesa; I Wayan Sudiarsa; I Putu Dicky Dharma Suryasa; Putu Agus Aditya Putra; Yulianus Kevin Dharmawa Sagur
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 4 No. 1 (2026): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v4i1.795

Abstract

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.

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