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All Journal JIK Jurnal Ilmu Komputer Majalah Ilmiah Matematika Komputer Nuansa Informatika Jurnal Teknologi Informatika dan Komputer Jurnal Pemberdayaan Komunitas MH Thamrin Jurnal Jaring SainTek International Journal of Business, Law, and Education International Journal of Engineering, Science and Information Technology Jurnal Ilmu Ekonomi Manajemen dan Akuntansi Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Jurnal Informatika Dan Tekonologi Komputer (JITEK) Indonesia Journal of Engineering and Education Technology (IJEET) Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Jurnal Informatika Dan Tekonologi Komputer
Yohanes Bowo Widodo
Universitas Mohammad Husni Thamrin
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

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Pengembangan Aplikasi Manajemen Inventaris Berbasis Android Guna Digitalisasi UMKM di Wilayah Jakarta Abu Sopian; Yohanes Bowo Widodo; Mohammad Ikhsan Saputro; Sondang Sibuea; Muhammad Ridwan Effendi
Jurnal Teknologi Informatika dan Komputer Vol. 10 No. 2 (2024): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i2.3581

Abstract

Manajemen inventaris konvensional pada Usaha Mikro, Kecil, dan Menengah (UMKM) retail di wilayah DKI Jakarta masih menghadapi kendala struktural yang masif, seperti tingginya risiko salah hitung stok, selisih data logistik, serta keterlambatan kronis dalam proses pengadaan kembali barang dagangan yang habis akibat ketiadaan sistem pencatatan yang terintegrasi. Penelitian ini bertujuan untuk melakukan rekayasa perangkat lunak guna membangun aplikasi manajemen inventaris mandiri berbasis Android yang andal dan adaptif untuk mengakselerasi digitalisasi operasional internal pelaku UMKM retail. Perangkat lunak ini dikembangkan secara terstruktur menggunakan metodologi pengembangan sistem model Waterfall dengan mengimplementasikan bahasa pemrograman Kotlin pada lapisan antarmuka pengguna, serta memanfaatkan mesin basis data SQLite lokal tertanam sebagai media penyimpanan data utama guna mewujudkan arsitektur offline-first. Hasil penelitian menunjukkan bahwa aplikasi yang dibangun berhasil mengintegrasikan seluruh fungsionalitas utama yang mencakup komponen 'Menu Barang Masuk' untuk melakukan update penambahan jumlah stok secara otomatis (+) dan 'Menu Barang Keluar' untuk melakukan update pengurangan jumlah stok secara real-time (-). Di sisi penyimpanan persisten, basis data SQLite lokal secara otonom mengolah sirkulasi arus logistik tersebut dan sukses memicu fungsi 'Peringatan Stok Kritis (<)' ketika kuantitas barang berada di bawah batas aman, sekaligus menginisiasi fitur 'Generate Laporan Otomatis' dalam format digital. Validasi keabsahan sistem melalui metode Black-box testing memberikan hasil pemenuhan fitur sebesar 100% valid tanpa adanya galat kritis, serta terbukti secara signifikan memangkas waktu stock opname harian para staf dari yang semula memakan waktu hitungan jam menjadi kurang dari 30 menit saja. Rekomendasi operasional dari penelitian ini ditujukan bagi pengembang sistem selanjutnya untuk menambahkan modul sinkronisasi data awan hibrida (hybrid cloud-sync) guna memfasilitasi kebutuhan pemantauan data jarak jauh secara multi-user oleh pemilik usaha tanpa mengorbankan ketahanan fitur luring aplikasi.
Environmental Engineering Urban Environmental Intelligence Framework for Air Quality Prediction Using Multi-Source Mobility and Climate Data Sondang Sibuea; Yohanes Bowo Widodo
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1916

Abstract

Rising urban mobility, intensive anthropogenic activity, and limitations in conventional monitoring systems capable of delivering continuous spatial coverage have turned urban air pollution into a pressing environmental concern. Existing air-quality prediction approaches tend to depend on single-source observations or are built primarily for large metropolitan areas, which limits how well they apply to secondary cities with localized pollution dynamics. To address this, the study introduces an Urban Environmental Intelligence Framework that brings together multi-source air quality, climate, spatial, temporal, and air-quality information for urban air-quality prediction. Evaluation of the framework was conducted using hourly observations of pollutant concentrations (PM2.5, NO2, and CO), mobility indicators (traffic volume, vehicle count, average speed, and congestion index), meteorological variables, and urban spatial attributes, collected from Lhokseumawe, Indonesia. A multi-source XGBoost model was benchmarked against Single-Source XGBoost, Random Forest, and LSTM models using a chronological data partition and multiple evaluation metrics, including MAE, RMSE, MAPE, and R². The proposed framework achieved the strongest predictive performance across all target variables evaluated, attaining an R² of 0.912 and an RMSE of 5.84 µg/m³ for PM2.5 prediction. Ablation analysis confirmed that temporal and mobility information contributed most substantially to prediction accuracy, while climate and spatial variables provided complementary contextual value. Feature interpretation further revealed that traffic intensity, historical pollutant levels, and meteorological conditions were the dominant drivers of urban pollution outcomes. Overall, the proposed framework offers an effective environmental approach for supporting short-term air-quality forecasting, pollution hotspot identification, and evidence-based urban environmental management in secondary cities
Retrieval-Augmented Large Language Model for Institutional Knowledge Management and Decision Assistance in Public Organizations Yohanes Bowo Widodo; Sondang Sibuea
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1904

Abstract

The increasing volume and complexity of institutional documents in public organizations create challenges in accessing reliable knowledge for administrative processes and evidence-based decision-making. Conventional knowledge management systems often rely on keyword-based retrieval, while standalone Large Language Models (LLMs) may generate inaccurate responses when processing domain-specific institutional information. This study proposes a domain-specific Retrieval-Augmented Generation (RAG) framework to enhance institutional knowledge management and AI-assisted decision support in public-sector organizations. The framework was developed using a Design Science Research approach with Universitas Malikussaleh as a case study. The proposed architecture integrates institutional knowledge base construction, semantic retrieval, grounded language generation, and source attribution mechanisms. A knowledge base comprising 416 official institutional documents was developed through document preprocessing, semantic chunking, embedding generation, and vector database indexing. The framework was evaluated using 200 institutional queries based on retrieval performance, response quality, explainability, and system efficiency metrics. The results demonstrate effective retrieval capability, achieving Precision@5 of 0.884, Recall@5 of 0.921, and Mean Reciprocal Rank of 0.895. Generated responses achieved 94.6% factual accuracy, 91.8% contextual relevance, and 96.5% source attribution accuracy, while the hallucination rate was reduced to 3.2%. Furthermore, the framework achieved an average response latency of 1.18 seconds, indicating practical feasibility for institutional applications. These findings demonstrate that integrating semantic retrieval with grounded LLM generation can improve knowledge accessibility, transparency, and reliability for AI-assisted decision support in public organizations. The proposed framework provides a practical foundation for trustworthy institutional knowledge services and supports more efficient, explainable, and evidence-based administrative decision-making across diverse institutional contexts
PERANCANGAN ROBOT PEMADAM API DENGAN PENGONTROLAN GERAK METODE PROPORTIONAL INTEGRAL DERIVATIVE (PID) MENGGUNAKAN SENSOR SONAR BERBASIS MIKROKONTROLLER Sondang Sibuea; Agung Rahmaddoni; Yohanes Bowo Widodo
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 1 No. 3 (2021): November : Jurnal Informatika dan Teknologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v1i3.83

Abstract

This research designs and implements a control algorithm on a wheeled wall follower robot that uses a PID controller (Proportional, Integral, Differential) as a navigation system for a wall follower fire fighting robot. The task of this robot is to walk along the walls of the area. The PID controller aims to smooth the movement of the robot when tracing the track space. With the help of the PID controller, the wall follower robot is able to navigate safely, smoothly, responsively and quickly. Fire fighting robots require a variety of sensors to run properly, one of which is using sonar sensors that are used for robot navigation. This sensor works based on the principle of wave reflection, where in this case the variable measured is the time of reflection since the wave was emitted. The sonar sensor detects an obstruction. The robot will turn and walk again without hitting obstacles or objects in the vicinity. To detect fire, fire sensor is used. This sensor also find hotspots by assessing the intensity of the light. Arduino ATMega328 microcontroller functions as a robot control. The output of the microcontroller will produce logic 1 to activate the motor driver to activate the right and left wheel motors. The DC motor is used as a driving force for the robot, and the battery here functions as a power supply for the robot. The result is, this robot can detect the fire point of the candle and extinguish the candle flame.
APLIKASI MOBILE COLLECTION BERBASIS ANDROID PADA PT. SUZUKI FINANCE INDONESIA Sondang Sibuea; Mohammad Ikhsan Saputro; Agie Annan; Yohanes Bowo Widodo
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 2 No. 1 (2022): Maret : Jurnal Informatika dan Teknologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v2i1.185

Abstract

Mobile collection application is a system to facilitate the process of monitoring and billing debtors at PT. Suzuki Finance Indonesia. Problems that often occur when billing is done by the ARO (Account Receiveble Officer) cannot be quickly monitored by the branch head. Also not known visit information quickly when billing. Therefore, in this research, an android-based mobile collection application will be built. So that monitoring and visit information can be obtained very quickly so that it can maximize the work of the branch head and ARO. The data collection method, the author uses field study techniques, interviews and uses library research methods with secondary data as the data source.
Co-Authors Achmad Rivaldi Ade Muhammad Ichsan Adrie Oktavio Agie Annan Agung Rahmaddoni Agus Wiyatno Ahmad Gunawan Ajeng Tias Endarti Akbar, Khoironi Fanana Amin Sakaria, Muhammad Andika Dirsa Andrian, Feri Anggraeini, Silvia Ayu Anindya, Aulia Arie Bayu Untoro Arie Bayu Untoro Aulia Anindya Budi Harsono Budi Harsono Dedi Setiadi Dedi Setiadi Ependi Erent Dany Pratama Erent Dany Pratama Febrianti Widyahastuti Febrianti, Reni Febrianto Febrianto Febrianto Febrianto, Febrianto Fenty Tristanti Julfia Fenty Tristanti Julfia Feri Andrian Fius Bryan Nigel M. Sinaga Gatot Hery Djatmika Gatot Hery Djatmika Gustiawan, Handa Gusvarizon, Muhammad Handa Gustiawan Handa Gustiawan Hasan Basri Ibrahim Aziz Indira Meilita Istifadah Istifadah Julfia, Fenty Tristanti Khaliq, Muhammad Nur Kiki Kurniawan Kiki Kurniawan Leo Faturahman Lily Nabilah Lingga Hanggada Adi Saputra Miftachul Amri Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro, Mohammad Ikhsan Muhammad Amin Sakaria Muhammad Bahrul Lutfianto Muhammad Gusvarizon Muhammad Gusvarizon Muhammad Nur Khaliq Muhammad Ridwan Effendi Nadia Lutfiana Sari Narji, Mohammad Ni Desak Made Santi Dwyarthi Ningsih, Putu Tirta Sari Nur Asniati Djaali Nur Fadilla Nur Fadilla Purnomo Purnomo Putu Tirta Sari Ningsih Rahman, Taslim Idris Rano Agustino Reni Febrianti Reni Febrianti RIO ANDRIYAT KRISDIAWAN Rosidah Rosidah Rosidah Rosidah S Sutrisno Sakaria, Muhammad Amin Silvia Ayu Anggraeini Simaibang, Frenta Helena Sinaga, Fius Bryan Nigel M. Sondang Sibuea Sopian, Abu Sutanto Priyo Hastono Sutrisno, Sutrisno Taslim Idris Rahman Tata Sutabri Tri Octavianto Untoro, Arie Bayu Via Yustitia Vidi Lampah Widyahastuti, Febrianti Wiwit Wijayanti, Wiwit Yudhazaldi Nuki Putrasandi Yustinus Tri Handoyo