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All Journal SITEKIN: Jurnal Sains, Teknologi dan Industri JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Scientific Journal of Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INDUSTRIAL AND MANUFACTURE ENGINEERING JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA SISTEM INDUSTRI Minda Baharu Jurnal Sistem Teknik Industri Altasia : Jurnal Pariwisata Indonesia Jurnal Optimalisasi SIGMA TEKNIKA Jurnal Manajemen Pendidikan dan Ilmu Sosial (JMPIS) Jurnal Pendidikan Sains dan Komputer Jurnal Manajemen Rekayasa dan Inovasi Bisnis Jurnal Pengabdian Ibnu Sina Journal of Event, Travel and Tour Management JT-IBSI (Jurnal Teknik Ibnu Sina) Jurnal Pengabdian Barelang (JINSENG) Journal of Industrial Innovation and Safety Engineering Scientific Journal of Informatics IESM
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Optimasi Klasifikasi Penjualan Produk Skincare Terlaris di Klinik XYZ Menggunakan Algoritma Decision Tree C4.5 Dermawan, Aulia Agung; Vadilla, Kansa; Leman, A. M.
Jurnal Pendidikan Sains dan Komputer Vol. 5 No. 01 (2025): Call for Papers February 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v5i01.5529

Abstract

Penelitian ini bertujuan untuk mengoptimalkan klasifikasi penjualan produk skincare terlaris di Klinik XYZ menggunakan algoritma Decision Tree C4.5. Dengan meningkatnya persaingan di industri skincare, manajemen penjualan berbasis data menjadi sangat penting bagi perusahaan untuk meningkatkan daya saing dan memenuhi kebutuhan pelanggan. Data penjualan yang digunakan mencakup atribut seperti nama produk, kategori, harga, dan status popularitas (terlaris atau tidak) dari periode Januari hingga April 2024. Melalui metode Decision Tree C4.5, penelitian ini membangun model klasifikasi untuk mengidentifikasi produk terlaris berdasarkan kategori dan harga. Hasil penelitian menunjukkan bahwa kategori produk dan harga merupakan faktor utama yang memengaruhi popularitas produk skincare. Meskipun model ini mencapai akurasi sebesar 68,75%, hasil tersebut menunjukkan bahwa masih diperlukan optimasi lebih lanjut. Berdasarkan temuan ini, disarankan untuk melakukan optimasi model dan mempertimbangkan algoritma lain yang lebih kompleks untuk meningkatkan akurasi prediksi. Hasil penelitian ini diharapkan dapat memberikan wawasan strategis bagi Klinik XYZ dalam menentukan harga dan strategi pemasaran yang lebih efektif.
Penerapan Panel Surya Cerdas untuk Peningkatan Infrastruktur Listrik Di Pulau Putri Candra, Joni Eka; Dermawan, Aulia Agung; Putera, Dimas Akmarul; Roland, Roland; Steve, Jorvick
Jurnal SOLMA Vol. 14 No. 1 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i1.17532

Abstract

Pendahuluan: Keterbatasan infrastruktur listrik membuat masyarakat Pulau Putri bergantung pada sumber energi konvensional yang tidak efisien dan mahal. Oleh karena itu, proyek "Penerapan Panel Surya Cerdas untuk Peningkatan Infrastruktur Listrik di Pulau Putri" dilaksanakan sebagai solusi inovatif untuk mengatasi masalah tersebut. Studi ini bertujuan untuk memasang sistem panel surya cerdas yang memanfaatkan teknologi Internet of Things (IoT) untuk memantau dan mengoptimalkan kinerja sistem secara real-time. Metode: Studi awal, survei lokasi, perencanaan, desain sistem, sosialisasi, pelatihan masyarakat, instalasi, implementasi, monitoring, dan evaluasi. Hasil: Berhasilnya pemasangan sistem panel surya 400Wp di Pulau Putri, teknologi IoT, efisiensi energi dan pengurangan biaya bahan bakar fosil.  Kesimpulan: Kegiatan ini bermanfaat bagi masyarakat karena dapat mengurangi emisi karbon dan menghemat biaya operasional.
Development of an IoT-Based Mobile Plastic Shredder for Optimized Waste Management in Batam Lawi, Ansarullah; Dermawan, Aulia Agung; Kurniawan , Dwi Ely; Yuni Roza; Ardilla, Thania; ., Jaswin
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9208

Abstract

Plastic waste management has become a critical environmental issue, with its improper handling leading to severe ecological and health impacts. This research addresses the challenge by designing and developing an IoT-based mobile plastic shredding machine aimed at improving waste management efficiency, particularly in Batam City, Indonesia. Utilizing Borg and Gall’s R&D framework, this study integrates IoT technology to enhance the machine’s functionality, enabling real-time data collection and remote monitoring through mobile applications. The machine comprises three functional levels: a storage area for raw plastic bottles, a shredding unit with proximity sensors, and a post-shredding storage compartment. Key innovations include weight sensors for automatic material handling and real-time data transmission via the Blynk IoT platform, controlled by an Arduino microcontroller. The modular design ensures portability, easy maintenance, and adaptability for use in various locations, including coastal areas. Prototyping involved integrating proximity sensors, load cells, relays, and motor control systems to ensure smooth operation. The machine demonstrated consistent performance during testing, with its IoT features enabling remote control and monitoring via smartphones. This facilitates optimized waste collection and contributes to reducing environmental pollution caused by plastic waste. The IoT-based mobile plastic shredding machine not only enhances waste management efficiency but also supports sustainability goals. Its portability and environmentally friendly design make it a practical solution for managing plastic waste in underserved areas. This innovation provides a significant step toward addressing the global plastic waste crisis, aligning with technological advancements to promote sustainable waste management practices.
Scenario-Based Association Rule Mining in Veterinary Services Using FP-Growth: Differentiating Clinical and Customer-Driven Patterns Rafi Dio; Aulia Agung Dermawan; Dwila Sempi Yusiani; Rifaldi Herikson; Andikha, Andikha; Dwi Ely Kurniawan; Adyk Marga Raharja
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9698

Abstract

Veterinary clinics routinely generate transactional data that contain valuable information about both operational workflows and customer preferences. This study aims to differentiate between procedural and customer-driven service patterns by applying the FP-Growth association rule mining algorithm to 1,000 anonymized transactions comprising 94 unique items, collected from a veterinary clinic in West Java, Indonesia, during 2023. Two distinct analytical scenarios were constructed: Scenario 1 includes all services (procedural and customer-driven), while Scenario 2 excludes procedural items such as “Vet” and “Visit Dokter” to focus solely on client-initiated behaviors. Data preprocessing involved aggregating transaction items into a market basket format suitable for frequent pattern mining. The FP-Growth algorithm was employed to extract association rules, evaluated using support, confidence, and lift metrics. Results from Scenario 1 revealed rule patterns reflective of standard clinical protocols and operational dependencies, informing bundled service packages and inventory management. In contrast, Scenario 2 uncovered customer-driven associations, highlighting opportunities for personalized promotions and service innovation. The comparative analysis demonstrates the utility of scenario-based association rule mining for both operational optimization and customer engagement. While the findings provide actionable insights for clinic management, further validation with practitioners and implementation in multi-clinic settings are recommended to confirm real-world applicability and enhance generalizability.
Optimasi Klasifikasi Penjualan Produk Skincare Terlaris di Klinik XYZ Menggunakan Algoritma Decision Tree C4.5 Dermawan, Aulia Agung; Vadilla, Kansa; Leman, A. M.
Jurnal Pendidikan Sains dan Komputer Vol. 5 No. 01 (2025): Artikel Riset February 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v5i01.5529

Abstract

Penelitian ini bertujuan untuk mengoptimalkan klasifikasi penjualan produk skincare terlaris di Klinik XYZ menggunakan algoritma Decision Tree C4.5. Dengan meningkatnya persaingan di industri skincare, manajemen penjualan berbasis data menjadi sangat penting bagi perusahaan untuk meningkatkan daya saing dan memenuhi kebutuhan pelanggan. Data penjualan yang digunakan mencakup atribut seperti nama produk, kategori, harga, dan status popularitas (terlaris atau tidak) dari periode Januari hingga April 2024. Melalui metode Decision Tree C4.5, penelitian ini membangun model klasifikasi untuk mengidentifikasi produk terlaris berdasarkan kategori dan harga. Hasil penelitian menunjukkan bahwa kategori produk dan harga merupakan faktor utama yang memengaruhi popularitas produk skincare. Meskipun model ini mencapai akurasi sebesar 68,75%, hasil tersebut menunjukkan bahwa masih diperlukan optimasi lebih lanjut. Berdasarkan temuan ini, disarankan untuk melakukan optimasi model dan mempertimbangkan algoritma lain yang lebih kompleks untuk meningkatkan akurasi prediksi. Hasil penelitian ini diharapkan dapat memberikan wawasan strategis bagi Klinik XYZ dalam menentukan harga dan strategi pemasaran yang lebih efektif.
Optimizing Inventory Management: Data-Driven Insights from K-Means Clustering Analysis of Prescription Patterns Dermawan, Aulia Agung; Ansarullah Lawi; Putera, Dimas Akmarul; Kurniawan, Dwi Ely; Ummatin, Kuntum Khoiro; Jorvick Steve
Scientific Journal of Informatics Vol. 11 No. 3: August 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i3.8690

Abstract

Purpose: The goal is to improve how inventory is managed in healthcare by using K-Means clustering to analyze prescription trends. This approach helps ensure better stock availability, streamlines operations, and ultimately increases sales opportunities. Methods: This research applied the K-Means clustering algorithm to analyze a comprehensive dataset of prescription behaviors from XYZ Clinic. By grouping similar prescriptions into clusters, this method highlighted patterns within the data. These insights led to the identification of unique prescription categories, enabling the creation of tailored recommendations for improving inventory management. Result: The analysis showed that Cluster 1 should be prioritized for inventory management due to its high sales potential and consistent prescription patterns. It is recommended to increase stock for the medications in Cluster 1 to improve inventory turnover and streamline clinical operations. These findings underscore the value of K-Means clustering in healthcare, especially for enhancing inventory management and operational efficiency. Novelty: This research presents a novel application of K-Means clustering in healthcare, focusing on prescription patterns and inventory management. While previous studies have primarily used K-Means clustering for areas such as risk assessment and logistics, this study provides valuable data-driven insights to improve inventory management strategies in healthcare. The results highlight how clustering methods can support better decision-making and resource allocation, ultimately leading to greater operational efficiency and improved patient care.
Analisis Pengaruh Komponen Daya Tarik Wisata terhadap Kepuasan dan Minat Kunjungan Ulang Wisatawan di Pantai New Melur, Kota Batam Hari Sandi Atmaja; Wahyudi Ilham; Aulia Agung Dermawan
Jurnal Manajemen Pendidikan dan Ilmu Sosial Vol. 7 No. 1 (2025): Jurnal Manajemen Pendidikan dan Ilmu Sosial (Desember 2025 - Januari 2026)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jmpis.v7i1.6989

Abstract

Penelitian berjudul “Analisis Pengaruh Komponen Daya Tarik Wisata Terhadap Kepuasan dan Minat Kunjungan Ulang Wisatawan di Pantai New Melur, Kota Batam” ini bertujuan menguji pengaruh komponen 4A. Penelitian ini menggunakan metode kuantitatif eksplanatori dengan pendekatan PLS-SEM. Pada 100 responden mengungkap bahwa Aksesibilitas (β= -0,392) dan Layanan Pendukung (β= 0,320) berpengaruh signifikan terhadap kepuasan, sementara Daya Tarik dan Fasilitas tidak signifikan. Kepuasan Wisatawan sendiri berpengaruh kuat dan signifikan (β= -0,624) terhadap Minat Kunjungan Ulang serta terbukti memediasi secara signifikan hubungan dari Aksesibilitas (β= 0,169) dan Layanan Pendukung (β= -0,288). Hasil ini menegaskan bahwa peningkatan aksesibilitas dan layanan pendukung merupakan faktor kunci dalam strategi peningkatan kepuasan dan loyalitas wisatawan.
IoT Application Development for Marine Debris Management in 3T Islands: Supporting a Circular Economy and Community Empowerment Hernando, Luki; Lawi, Ansarullah; Dermawan, Aulia Agung; Aritonang, Mhd Adi Setiawan; Ad, Roni; Kurniawan, Dwi Ely; Manurung, Putriana Carona; Putri, Intan Medisi
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11699

Abstract

Marine debris is a serious problem, especially in the outermost, foremost, and least developed (3T) islands of Indonesia, where limited infrastructure and low public awareness are the main obstacles to effective waste management. This study aims to design, develop, and evaluate an Internet of Things (IoT)-based application integrated with a community-based web platform to support circular economy practices and community empowerment in marine debris management. The research method used is Research and Development (R&D) adapted from Borg & Gall, starting from the needs analysis stage to dissemination. An IoT module equipped with ultrasonic and GPS sensors is used to detect container capacity and location in real-time. Performance testing results show a response time of 1.8 seconds, a data transmission success rate of 98.7%, and a capacity detection accuracy of 96.2%, which meets the established technical standards. User acceptance testing using the Technology Acceptance Model (TAM) involving 15 respondents resulted in an average Perceived Usefulness (PU) score of 4.40 and Perceived Ease of Use (PEOU) of 4.23. Pearson's correlation analysis showed an r value of 0.84 (p = 0.0001), indicating a very strong and significant positive relationship between ease of use and perceived usefulness. This finding confirms that the developed system is technically reliable, easy to use, and capable of promoting environmental sustainability and economic opportunities in the 3T island communities.
Design and Implementation of an IoT-Based Low-Emission Mobile Plastic Melting Machine for Sustainable Paving Block Production in Batam City Lawi, Ansarullah; Aranski, Alvendo Wahyu; Burhan, Rifa’atul Mahmudah; Hernando, Luki; Aritonang, Muhammad Adi Setiawan; Dermawan, Aulia Agung; Kurniawan, Dwi Ely; Leman, Abdul Mutalib
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.12044

Abstract

Plastic waste accumulation poses a severe environmental burden, particularly in urban and archipelagic regions where centralized treatment infrastructure is limited. While thermal processing offers a pathway for volume reduction and material recovery, inadequate temperature control frequently leads to uncontrolled combustion and the formation of hazardous air pollutants. This study addresses this gap by developing and experimentally validating a low-emission, IoT-enabled mobile plastic melting system designed for decentralized paving block production. The proposed system integrates real-time thermal sensing using a K-type thermocouple and an ESP32-based controller with a compact three-nozzle water spray filtration unit. The control architecture maintains the melting process at approximately 270 °C, thereby preserving polymer viscosity for molding while preventing temperature excursions beyond 300 °C that may initiate combustion and toxic by-product formation. The filtration module operates as a simplified wet scrubber, capturing airborne particulates and simultaneously cooling the exhaust stream. Experimental evaluations confirm that the integrated control–filtration framework achieves stable thermal regulation and substantial suppression of visible exhaust emissions. Under these conditions, molten plastic was consistently transformed into dense paving blocks with smooth surface morphology and without evidence of polymer degradation or charring. The results demonstrate that combining IoT-based thermal governance with low-cost water-spray emission control provides an effective and scalable alternative to open burning for community-level plastic waste recycling. This mobile platform enables environmentally safer conversion of plastic waste into value-added construction materials, offering a practical pathway toward decentralized circular-economy implementation in resource-constrained regions.
Klasifikasi Kelayakan Calon Pendonor Darah Di PMI mengunakan Decision Tree Arina Abrilian Pulung; Rebeka Mentari; Taufiq Denny Wicaksono; Enjelika Rosan; Ir. Aulia Agung Dermawan
Industrial Engineering System and Management Journal Vol. 5 No. 2 (2024): Vol 5 No 2 Agustus 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data UDD PMI menunjukkan bahwa banyak pendonor yang wajib memenuhi persyaratan guna dijadikan pendonor darah. Selama ini, calon pendonor dipilih secara manual untuk mendonorkan darah. Sistem informasi sekarang belum menggali lebih banyak informasi dari banyak data guna menjadi pengetahuan. Wajib ada konsolidasi organisasi serta penilaian yang berkelanjutan mengenai kinerja PMI guna menangani permasalahan sosial kemanusiaan. Guna mengidentifikasi individu layak ataupun tidak guna mendonorkan darahnya, pengimplementasian data mining melalui metode klasifikasi mempergunakan Algoritma Decision Tree C4.5 dapat mempergunakan hasil variable yang bernilai kontinu ataupun dikrit, misalnya umur, BB, serta tekanan darah (sistolik serta diastolik). Dengan mempergunakan data mining Algoritma Decision Tree C4.5, calon kelayakan pendonor darah bisa diklasifikasikan berdasar umur, BB, hemoglobin, serta tekanan darah. Variabel yang paling menentukan yaitu hemoglobin dengan nilai gain tertinggi
Co-Authors ., Jaswin Abdiel Khaleil Akmal Abdul Rahim Matondang Ad, Roni Adi, Roni Adinda Juwita Nasution Adyk Marga Raharja Aldi Mulia Alvendo Wahyu Aranski Alvendo Wahyu Aranski Andikha, Andikha Andri Ramadhan Ansarullah Lawi Ardilla, Thania Arina Abrilian Pulung Aritonang, Muhammad Adi Setiawan Arrazy Elba Ridha Bahri, M Irvanni Burhan, Rifa’atul Mahmudah candra, joni eka Diana Syntia Manalu Diana Syntia Manalu Dimas Akmarul Putera Dimas Putera Dio Putra Dwi Ely Kurniawan Dwila Sempi Yusiani Enjelika Rosan Febriani Zainal Fitriyani Fuad Dwi Hanggara Hari Sandi Atmaja Hendri Kremer Hernando, Luki Hutagalung, Deria Moti Ihsan Fadlu Rahman Iing Pamungkas Ilham, Wahyudi Irawan, Heri Tri Irawan, Risnadi Islahhudin Fuadi Islahhudin fuadi Tabrizon Jito Armando Jorvick Steve Jorvick Steve Juliza Hidayati Kansa Vadilla Kremer, Hendri Lawi, Ansarullah Leman, A. M. Leman, Abdul Mutalib Lesmana, Naufal Indra M. Ansyar Bora Maharani Putri Manurung, Putriana Carona Maria Magdalena Sibagariang Maulidina, Siti Nur Meilita Tryana Sembiring, Meilita Tryana Mhd Adi Setiawan Aritonang Mhd Adi Setiawan Aritonang Muhammad Arya Bagaskara Muhammad Arya Bagaskara Muhammad Fiza Lubis Muhammad Fiza Lubis Muhammad Fiza Lubis Muhammad Jufri Muhammad Syahruddin munir, Zainul Munir Muqimuddin Muqimuddin Naufal Indra Lesmana Nigel Abie Rachel Nelwan Oktafanny Rozalia Panangian Mahadi Sihombing Pane, Amirah Nova Khairiyah Pina Alpianita Popi Kasandra Puspita Rini, Rosie Oktavia Putri, Intan Medisi Rafi Dio Rebeka Mentari Rifaldi Herikson Rini Rosie Oktavia Puspita Rini Ririt Dwi Putri Permatasari Riski Arifin Rita sarina siburian Roland, Roland Rosie Oktavia Puspita Rini Rosie Oktavia Puspita Rini Rosie Oktavia Puspita Rini Salwa Azzahra Wenny Sanniyah Delti Rama Saputra, Puji Tri Sari Rahmiati Siti Nurhasanah Sondra Wijaya, I Made Sri Indah Rezkika Steve, Jorvick Suci Dwi Maharani Sunarsono, Hery Taufiq Denny Wicaksono Tirta Mulyadi Tirta Mulyadi Tuti Adi Tama Nasution Ummatin, Kuntum Khoiro Vadilla, Kansa Via Audila Vincencia Medita Vincencia Medita Wahyudi Ilham Wahyudi Ilham Wahyudi Ilham Wenny Ayu Shestia Yuni Roza