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All Journal Griya Journal of Mathematics Education and Application JoMMiT : Jurnal Multi Media dan IT Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Jurnal Bisnis Digital dan Enterpreneur (BISENTER) KOMNET : Jurnal Komputer, Jaringan dan Internet
I Made Candra Girinata
Politeknik Negeri Tanah Laut
Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Mathematics Social Sciences Other

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Network Intrusion Detection Using Machine Learning in Network Intrusion Detection Systems (NIDS) Arnoldus Jansen; Dery Yuswanto; Budi Styawan; I Made Candra Girinata
KOMNET : Jurnal Komputer, Jaringan dan Internet 2025: Vol 4 No 1
Publisher : Pusat Penelitian dan Pengabdian Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/yt59ac51

Abstract

Computer network security has become a crucial aspect as dependence on network-based services increases. One important mechanism in maintaining network security is the Network Intrusion Detection System (NIDS), which functions to detect suspicious activity or attacks on network traffic. The traditional signature-based approach has limitations in detecting new attacks (zero-day attacks). Therefore, this study proposes the application of Machine Learning and Deep Learning methods to improve network intrusion detection capabilities. The CIC-IDS2017 dataset was used as the data source because it represents various types of modern network attacks. The research stages included data pre-processing, feature selection, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The models used include Random Forest as a representation of Machine Learning and Long Short-Term Memory (LSTM) as a representation of Deep Learning. The results show that the Deep Learning approach is capable of providing better detection performance on complex attacks compared to conventional Machine Learning methods. This research is expected to serve as a reference in the development of adaptive and accurate network intrusion detection systems.
Analisis Statistik Pengaruh Mata Kuliah Ekonometrika Terhadap Minat Mahasiswa Jurusan Ekonomi dalam Penelitian Kuantitatif Arwin Wahyu Saputra; Liny Mardhiyatirrahmah; Dewi Indra Anggraeni; Dery Yuswanto Jaya; I Made Candra Girinata; Budi Styawan
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.1089

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh penguasaan mata kuliah Ekonometrika terhadap minat mahasiswa dalam melakukan penelitian kuantitatif. Penguasaan metode kuantitatif merupakan kompetensi penting bagi mahasiswa ekonomi dalam menghadapi tantangan penelitian berbasis data. Penelitian ini menggunakan pendekatan kuantitatif dengan desain survei. Data dikumpulkan melalui kuesioner skala Likert dan dokumentasi nilai akhir mata kuliah Ekonometrika. Sampel penelitian terdiri atas mahasiswa Program Studi Ekonomi Syariah STAI Al-Gazali Soppeng yang telah menempuh mata kuliah Ekonometrika. Analisis data dilakukan menggunakan korelasi Pearson dan regresi linear sederhana setelah terlebih dahulu memenuhi uji asumsi klasik. Hasil penelitian menunjukkan bahwa penguasaan mata kuliah Ekonometrika berpengaruh positif dan signifikan terhadap minat mahasiswa dalam penelitian kuantitatif dengan koefisien regresi sebesar 0,654 dan nilai signifikansi . Koefisien determinasi menunjukkan bahwa penguasaan Ekonometrika menjelaskan 39,9% variasi minat penelitian kuantitatif mahasiswa. Temuan ini menegaskan pentingnya pembelajaran Ekonometrika yang aplikatif dan berpusat pada mahasiswa untuk meningkatkan minat dan keterlibatan mahasiswa dalam penelitian kuantitatif.
Rancang Bangun Smart Glove Penerjemah SIBI berbasis ESP32 Terintegrasi Sistem Speech Synthesis Budi Styawan; Handy Hartono Setiawan; I Made Candra Girinata; Arwin Wahyu Saputra; Zaenul Mutaqin
Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Vol 5 No 1 (2026): Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK)
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/jumistik.v5i1.312

Abstract

Komunikasi antara penyandang disabilitas tunarungu dan tunawicara dengan masyarakat umum kerap terhambat akibat minimnya pemahaman terhadap Sistem Isyarat Bahasa Indonesia (SIBI). Penelitian ini merancang dan mengimplementasikan purwarupa sarung tangan pintar (smart glove) satu tangan berbasis mikrokontroler ESP32 yang mampu mengenali isyarat huruf vokal SIBI (A, I, U, E, O) secara waktu nyata. Akuisisi data dilakukan melalui fusi lima flex sensor berkonfigurasi pull-up dan modul sensor inersia MPU6050. Pemrosesan sinyal dilakukan secara lokal menggunakan filter Exponential Moving Average (EMA) diikuti metode klasifikasi thresholding deterministik. Data telemetri dikirimkan nirkabel melalui protokol MQTT ke antarmuka web Laravel untuk divisualisasikan sebagai teks dan dikonversi menjadi luaran suara (speech synthesis). Pengujian Confusion Matrix terhadap 500 sampel menghasilkan akurasi rata-rata 94,2% dengan rata-rata latensi end-to-end 2.216,4 milidetik. Hasil ini memvalidasi keandalan purwarupa sebagai fondasi pengembangan sistem penerjemah SIBI yang lebih komprehensif.
Analysis of 433 MHz LoRa Communication Quality Based on RSSI and SNR Parameters in A Solar-Powered IoT Chili Irrigation System in Hilly Forest Farmland Huktah Dwi Pradana; Puan Gusti Halida Lutfiah; Akhmad Minannor Rahman; Rizky Yandri; I Made Candra Girinata
JoMMiT Vol 10 No 1 (2026): Artikel Jurnal Volume 10 Issue 1, Juni 2026
Publisher : Politeknik Negeri Media Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46961/jommit.v10i1.2208

Abstract

Agricultural areas in tropical hilly regions generally face challenges due to dense vegetation and uneven topography, which can cause signal attenuation and unstable communication performance. Therefore, this study analyzed the communication quality of a 433 MHz LoRa network based on the parameters of Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), and Packet Delivery Ratio (PDR) in an Internet of Things (IoT)-based chili irrigation system implemented in a tropical hilly agricultural area at an altitude of 210 meters above sea level. This study employed a quantitative experimental method through direct field measurements and descriptive analysis to evaluate wireless communication performance under Non-Line-of-Sight (NLOS) conditions. The system utilized an ESP32 microcontroller and a LoRa SX1278 module operating at 433 MHz to evaluate the reliability and effectiveness of wireless data transmission. Over a continuous monitoring period of approximately 2 hours and 27 minutes, 303 LoRa packets were transmitted, of which 186 were successfully received, yielding a Packet Delivery Ratio of 61.4% and a packet loss rate of 38.6%. RSSI values fluctuated between −92 dBm and −97 dBm, with an average of approximately −93 to −94 dBm, while SNR values ranged from 6.7 dB to 10.8 dB, with most communication sessions maintaining values of approximately 8 dB. Two distinct communication gaps, lasting approximately 8.5 and 33 minutes, respectively, were observed during the monitoring period. The results demonstrate that the 433 MHz LoRa network was able to maintain wireless communication under the tested tropical hilly NLOS conditions, although the relatively low PDR indicates that communication reliability remains a challenge. Further optimization of antenna placement, network configuration, and error-correction mechanisms is recommended to improve communication reliability for more demanding IoT irrigation applications.
Integrasi Computational Thinking dan Teori Graf untuk Pemecahan Masalah Mahasiswa Teknologi Rekayasa Komputer Jaringan Arwin Wahyu Saputra; Dewi Indra Anggraeni; Liny Mardhiyatirrahmah; Arnoldus Janssen Dahur; Dery Yuswanto Jaya; I Made Candra Girinata
Jurnal Bisnis Digital dan Enterpreneur (BISENTER) Vol. 4 No. 2 (2026): Jurnal Bisnis Digital dan Enterpreneur
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/bisenter.v4i2.357

Abstract

Problem-solving skills are essential competencies for Network Computer Engineering Technology students, particularly in Discrete Mathematics. This study examines the application of Computational Thinking (CT) and Graph Theory to support students’ problem-solving skills in Discrete Mathematics. Utilizing a systematic literature review, this research synthesizes findings from empirical and conceptual studies regarding CT integration in mathematics. The review indicates that CT's four pillars, decomposition, pattern recognition, abstraction, and algorithm design coherently align with Graph Theory elements such as vertex-edge representation, adjacency matrices, and routing algorithms. The reviewed empirical studies indicate that several CT-based learning interventions are associated with improvements in mathematical problem-solving, although their effectiveness varies according to instructional design and learning context. The study also identifies common conceptual difficulties in graph theory, which can be mitigated through a structured CT approach. Integrating CT and Graph Theory not only strengthens conceptual understanding but also prepares students for technical networking challenges. Descriptive data on students' learning achievements is presented as a contextual baseline, reinforcing the urgency of implementing this framework.
Co-Authors Akhmad Minannor Rahman Arnoldus Jansen Arnoldus Janssen Dahur Arwin Wahyu Saputra Budi Styawan Dery Yuswanto Dery Yuswanto Jaya Dewi Indra Anggraeni Handy Hartono Setiawan Huktah Dwi Pradana Liny Mardhiyatirrahmah Puan Gusti Halida Lutfiah Rizky Yandri Zaenul Mutaqin