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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sistem Komputer dan Informatika (JSON)
Baihaqi Siregar
Universitas Sumatera Utara
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Klasifikasi Kecerdasan Majemuk pada Anak Berdasarkan Posting Aktivitas di Media Sosial Menggunakan SentiStrength dan Spearman's Rank Correlation Coefficient Baihaqi Siregar; Cindy Aprilia; Filia D Anggaraeni; Ivan Jaya
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1500

Abstract

Intelligence are things related to intelligence, intellectual action, and perfect development of the mind. Every human being has the right to develop himself based on intelligence. A child who is good at playing violin shouldn't let himself feel like he is stupid because he is unable to complete his mathematical tasks. Therefore, the author wants to create a system for determining children's talent based on multiple intelligence as measured by the tendency of posts about their daily activities on social media by using the Sentistrength and Spearman's Correlation Coefficient methods. The purpose of this research is to create a social media application called Juicer, which is able to determine one's talent according to multiple intelligence theory based on data in the form of user posts about their daily activities. Users input their daily activities and opinions about the activities that he is currently undergoing. The system will analyze the data entered a negative or positive opinion. Then determine whether the data entered are musical-rhythmic, visual-spatial, verbal-linguistic, logical-mathematical, bodily-kinesthetic, interpersonal, intrapersonal, naturalistic, and / or spiritual-type using lexicon-based sentiment analysis with the Sentistrength method. After a long period of time, the system will sort the data that has been stored. After the data is classified, user intelligence types will be found based on multiple intelligence theory, as a result of this study. The result of the correlation between intelligence type data obtained through the system compared to intelligence type data obtained through the manual method is 80%, and the deviation value is 0.09.
Securing sensor data transmission with ethernet elliptic curve cryptography secure socket layer on STM32F103 device Seniman Seniman; Baihaqi Siregar; Rani Masyithah Pelle; Fahmi Fahmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp507-515

Abstract

Currently there is no method, feature, or ability in securing data transmission in microcontroller systems and applications with client-server scheme communication, while major modern computer systems using secure socket layer (SSL) for establishing secure communication. However, ESP espressif based microcontroller has supported SSL communication to secure data transmission, but only works on the Wi-Fi network. A single-board computer based embedded system has fully supported SSL communication, but it costs a very high price. On the other hand, STM32F103 microcontrollers with a very affordable price even cheaper than the Arduino board has the opportunity to build secure data communication using SSL protocol based on MbedTLS library. In addition to wiznet W5100/W5500 ethernet shield, an STM32F103 SSL client device has been successfully built in this study. The SSL client device supports ECDHE ECDHA AES128 CBC SHA256 SSL cipher suite. The Apache web server must also be configured to support this cipher suite by generating OpenSSL ECC (elliptic curve cryptography) certificate. The system was tested with the LM35 analog temperature sensor, and as a result, the STM32F103 SSL client has successfully secured the data transmission to the Apache SSL web server. The communication time was 3 seconds for the first connection and 42 ms for the next data transmission.
Pendekatan Augmentasi Data Time Series Untuk Peramalan Kebutuhan Obat Antiretroviral Berbasis Long Short-Term Memory Munazar; Baihaqi Siregar; Amalia
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 4 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i4.9831

Abstract

Perencanaan kebutuhan obat antiretroviral yang akurat diperlukan untuk menjaga kesinambungan terapi HIV, mencegah stock-out, dan meningkatkan efisiensi distribusi obat. Namun, peramalan masih terhambat oleh keterbatasan data historis, dominasi nilai nol, dan fluktuasi permintaan yang menyulitkan model mempelajari pola time series secara stabil. Penelitian ini mengevaluasi enam metode augmentasi data time series - Gaussian noise jittering, time warping, Fast Fourier Transform-based augmentation, MixUp time series, TimeGAN, dan Seasonal-Trend Decomposition using Loess — untuk meningkatkan akurasi peramalan berbasis Long Short-Term Memory. Dua skema diuji: penambahan data sintetis (25%, 50%, 75%, 100%) dan penggantian data asli (10%, 20%, 40%, 60%, 80%), dievaluasi menggunakan Mean Absolute Error non-zero. Hasil menunjukkan bahwa augmentasi moderat (25%–50%) meningkatkan akurasi, skema penambahan lebih stabil daripada penggantian, dan model terbaik menggunakan Seasonal-Trend Decomposition using Loess mencapai MAE non-zero sekitar 66.
Co-Authors Amalia Cindy Aprilia Fahmi Fahmi Filia D Anggaraeni Ivan Jaya Munazar Rani Masyithah Pelle Seniman Seniman