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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro Jambura Industrial Review (JIREV) Jurnal Begawe Teknologi Informasi
I Wayan Agus Arimbawa, I Wayan Agus
Departmet of Informatics Engineering, Engineering Faculty, Mataram University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Pemberdayaan Strategis Untuk Meningkatkan Kemampuan Bahasa Korea Dan Bisnis Digital Pada Masyarakat Lombok: Strategic Empowerment for Enhancing Korean Language Proficiency and Digital Business Skills in West Nusa Tenggara Community Arimbawa, I Wayan Agus; Kusuma, P. Permadi; Jayusman, Dirga; Andara, M. Jonathan; Firdaus, Muh.; Saraswati, N.P. Ayu Gita; Yasri, N.J. Alifa
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 1 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i1.1184

Abstract

Kuliah Kerja Nyata (KKN) merupakan pelaksanaan dari tanggung jawab perguruan tinggi dalam pendidikan, pengajaran, penelitian, dan pengabdian masyarakat. Secara khusus, KKN merupakan bentuk pengabdian langsung mahasiswa kepada masyarakat, di mana menerapkan pengetahuan yang diperoleh selama perkuliahan untuk kepentingan langsung masyarakat. Program KKN Universitas Mataram bersama Seoul National University bertujuan mengembangkan keterampilan dan memberdayakan masyarakat Lombok melalui pelatihan produk bisnis digital, bahasa Korea dasar, bahasa Korea untuk bekerja (EPS-Topic), bahasa Korea untuk pariwisata, dan bahasa Korea untuk bisnis. Ini diharapkan dapat memberikan bekal bagi masyarakat Lombok untuk bekerja atau melanjutkan pendidikan di Korea.
OPTIMALISASI POTENSI MASYARAKAT DI PULAU LOMBOK MELALUI PELATIHAN BAHASA KOREA DAN BISNIS DIGITAL: Optimization of Community Potential in Lombok Island through Korean Language and Bisnis Digital Training Annuur, Ali; Salsabila, Raissa Calista; Devianur, Dinda; Suhada, Destia; Aulia, Annisa Fitri; Maulidi, M. Harish; Arimbawa, I Wayan Agus
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 2 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i2.1232

Abstract

Program “2024 SNUSR Summer Corps in Indonesia” merupakan inisiatif kolaboratif antara Universitas Mataram, Universitas Nasional Jakarta, dan Seoul National University, yang bertujuan untuk memberdayakan masyarakat Lombok melalui pelatihan Bahasa Korea dan bisnis digital. Program ini dirancang untuk meningkatkan keterampilan bahasa Korea yang relevan dalam pariwisata dan bisnis, serta untuk memberikan pengetahuan praktis tentang bisnis digital kepada masyarakat. Pelatihan melibatkan pengajaran langsung oleh profesional di bidangnya dan mencakup berbagai topik dari dasar-dasar bahasa hingga strategi bisnis digital. Hasil dari program ini menunjukkan tingkat kepuasan yang tinggi di kalangan peserta, dengan peningkatan signifikan dalam keterampilan bahasa dan pengetahuan bisnis mereka. Evaluasi lebih lanjut menunjukkan keberhasilan program dalam meningkatkan keterampilan peserta, dengan beberapa rekomendasi untuk perbaikan di masa depan guna lebih mengoptimalkan kontribusi asisten pengajar dan pemenuhan harapan peserta. Program ini diharapkan dapat berkontribusi pada peningkatan ekonomi lokal dan hubungan internasional antara Indonesia dan Korea Selatan.
PELATIHAN ROBOTIK DAN PEMROGRAMAN BLOK UNTUK MENINGKATKAN MINAT BELAJAR STEM SEJAK DINI: Robotics and Block Programming Training to Enhance Interest in STEM Learning from an Early Age Arimbawa, I Wayan Agus; Wijayanto, Heri; Jatmika, Andy Hidayat; Huwae, Raphael Bianco; Rizky, Dimas Maulana; Witarsana, I Nengah Dwi Putra; Ramadhani, Rizky Insania; Zahrani, Nurul Qalbi
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 2 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i2.1239

Abstract

Program pengabdian ini bertujuan untuk meningkatkan minat belajar siswa sekolah dasar dalam bidang STEM (Science, Technology, Engineering, and Mathematics) melalui pelatihan robotik dan pemrograman blok. Mengingat rendahnya pencapaian siswa Indonesia dalam studi internasional seperti TIMSS dan PISA, pendekatan ini diharapkan dapat memberikan solusi inovatif yang mampu memotivasi siswa sejak dini. Metode pengabdian meliputi pelatihan praktis dalam dua modul utama: pengenalan robotik dan pemrograman menggunakan Scratch. Pelatihan ini melibatkan 22 siswa dari SDN Model Mataram, yang dilaksanakan dari 31 Juli 2024 hingga 29 Agustus 2024, dengan frekuensi pertemuan dua kali seminggu selama 60 menit setiap sesi, di bawah bimbingan tim mentor. Hasil kegiatan menunjukkan bahwa 59,1% peserta sangat tertarik dan 31,8% tertarik pada pembelajaran robotik, sementara untuk pemrograman blok, 68,2% merasa sangat menarik dan 31,8% tertarik. Secara keseluruhan, 63,6% peserta sangat tertarik dengan kegiatan, meskipun ada 10% yang merasa tidak tertarik. Dalam kegiatan ekstrakurikuler robotik dan coding, 68,2% peserta sangat tertarik dan 22,7% tertarik. Selain itu, terjadi peningkatan pemahaman siswa dengan kenaikan nilai sebesar 26% dari pre-test ke posttest. Kesimpulannya, pelatihan ini efektif dalam meningkatkan minat dan kompetensi STEM siswa, serta berpotensi menjadi model pembelajaran yang inovatif di tingkat dasar.
K-Means-Based Customer Segmentation with Domain-Specific Feature Engineering for Water Payment Arrears Management Akbar, Andi Hary; Wijayanto, Heri; Arimbawa, I Wayan Agus
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i1.5186

Abstract

Indonesian water utilities face persistent challenges in managing payment delinquencies due to diverse customer characteristics, geographic limitations, and inadequate analytical capabilities. Addressing this issue is essential to optimizing revenue collection and supporting sustainable operations. This study aims to develop a data-driven customer segmentation framework using K-means clustering to enhance delinquency management. The framework incorporates six engineered features—Debt Efficiency, Payment Behavior Score, Category Risk Score, Geographic Risk Score, Consumption Intensity, and Financial Risk Score—designed to capture customer payment behavior, consumption patterns, and geographic risk. We applied the model to 1,500 anonymized customer records from PT Air Minum Giri Menang, focusing on those with delinquencies exceeding four months. Risk scoring was based on quintile distribution, and optimal clustering was determined through the elbow method combined with silhouette coefficient analysis. The results produced a two-cluster solution (silhouette score = 0.538), showing statistically significant differences across features (p ¡ 0.001) and medium-to-large effect sizes (Cohen’s d = 0.52–2.12). The segmentation identified medium-risk customers (86.7%) who require preventive management and high-risk customers (13.3%) who need billing intervention. Urban areas exhibited higher delinquency risk (18.4%) than rural areas (2.5%), indicating the need for geographically targeted strategies. All customer data was anonymized following Indonesian data protection protocols. In conclusion, the proposed framework transforms manual billing supervision into an adaptive, data-driven management system, contributing to segmentation research by introducing utility-specific engineered features for Indonesian water utilities.
Text Classification Using Genetic Programming with Implementation of Map Reduce and Scraping Wedashwara, Wirarama; Irmawati, Budi; Wijayanto, Heri; Arimbawa, I Wayan Agus; Widartha, Vandha Pradwiyasma
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1813

Abstract

Classification of text documents on online media is a big data problem and requires automation. Text classification accuracy can decrease if there are many ambiguous terms between classes. Hadoop Map Reduce is a parallel processing framework for big data that has been widely used for text processing on big data. The study presented text classification using genetic programming by pre-processing text using Hadoop map-reduce and collecting data using web scraping. Genetic programming is used to perform association rule mining (ARM) before text classification to analyze big data patterns. The data used are articles from science-direct with the three keywords. This study aims to perform text classification with ARM-based data pattern analysis and data collection system through web-scraping, pre-processing using map-reduce, and text classification using genetic programming. Through web scraping, data has been collected by reducing duplicates as much as 17718. Map-reduce has tokenized and stopped-word removal with 36639 terms with 5189 unique terms and 31450 common terms. Evaluation of ARM with different amounts of multi-tree data can produce more and longer rules and better support. The multi-tree also produces more specific rules and better ARM performance than a single tree. Text classification evaluation shows that a single tree produces better accuracy (0.7042) than a decision tree (0.6892), and the lowest is a multi-tree(0.6754). The evaluation also shows that the ARM results are not in line with the classification results, where a multi-tree shows the best result (0.3904) from the decision tree (0.3588), and the lowest is a single tree (0.356).
Solar Powered Vibration Propagation Analysis System using nRF24l01 based WSN and FRBR Wedashwara, Wirarama; Yadnya, Made Sutha; Sudiarta, I Wayan; Arimbawa, I Wayan Agus; Mulyana, Tatang
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1592

Abstract

Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.
Co-Authors Abdul Rasyid Afwani, Royana Akbar, Andi Hary Albar, Moh. Ali Andara, M. Jonathan Annuur, Ali Ario Yudo Husodo, Ario Yudo Aulia, Annisa Fitri Budi Irmawati Dennaya, R. Muhammad Gerald Devianur, Dinda Diharja, Sasmita Prawira Fatimah, Sabrina Firdaus, Muh. Fitri Bimantoro Hanina, Salma Etqia Hasanuddin . Heri Wijayanto Huwae, Raphael Bianco I B K Widiartha I Gede Pasek Suta Wijaya I Wayan Sudiarta Irfan Akbar, Lalu A. Syamsul Jatmika, Andy Hidayat Jayusman, Dirga Kencana, Ida Bagus Adi Kusuma, P. Permadi Made Sutha Yadnya Maulidi, M. Harish Murpratiwi, Santi Ika Putra, Budi Pratama Rahman, Lalu Zhafran Farras Ramadhan, Hifric Aldar Ramadhani, Rizky Insania Rizky, Dimas Maulana Salsabila, Raissa Calista Saputra, Muhammad Harpan Teguh Saraswati, N.P. Ayu Gita Suhada, Destia Sunardi . Syahid, Muhammad Arya Maula Tatang Mulyana Utami, Tania Paramita Vandha Pradwiyasma Widartha Wedashwara, I Gde Putu Wirarama W Wedashwara, Wirarama Witarsana, I Nengah Dwi Putra Yasri, N.J. Alifa Yusril Ihza, Yusril Zahrani, Nurul Qalbi Zubaidi, Ariyan