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All Journal Journal of System and Computer Engineering Indonesian Journal of Intellectual Publication (IJI Publication) Madani: Multidisciplinary Scientific Journal Sentra Dedikasi: Jurnal Pengabdian Masyarakat Indonesian Journal of Intellectual Publication (IJI Publication)
Rimalia, Watty
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Implementasi Metode Topsis dan AHP dalam Deteksi Dini Penyakit Demam Berdarah Rimalia, Watty
Indonesian Journal of Intellectual Publication Vol. 3 No. 3 (2023): Juli 2023, IJI Publication
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51577/ijipublication.v3i3.423

Abstract

Demam berdarah, juga dikenal sebagai demam dengue (DBD), adalah penyakit menular yang disebabkan oleh virus dengue yang ditularkan melalui nyamuk Aedes aegypti. Penyakit ini merupakan masalah kesehatan masyarakat serius di berbagai wilayah tropis dan subtropis, termasuk Indonesia. Deteksi dini DBD memiliki peran penting dalam pengendalian penyebaran penyakit ini dan perawatan yang tepat waktu. DBD disebabkan oleh empat jenis virus dengue yang berbeda dan dapat menyebabkan gejala seperti demam tinggi, nyeri sendi dan otot, sakit kepala parah, mual, muntah, ruam, dan perdarahan ringan hingga internal. Deteksi dini melibatkan diagnosis klinis, pemeriksaan laboratorium, dan pemeriksaan imunoserologi. Pengendalian DBD melibatkan penggunaan insektisida, kelambu anti-nyamuk, edukasi masyarakat, dan vaksinasi. Deteksi dini membantu dalam perawatan tepat waktu, mencegah komplikasi, dan mengurangi angka kematian. Sistem pendeteksi dini oleh tenaga kesehatan melibatkan anamnesis, pemeriksaan fisik, tes darah, pemantauan cairan tubuh, perawatan gejala, konseling, pelaporan kasus, dan pencegahan penyebaran. Untuk mendukung deteksi dini, penelitian mengusulkan pengembangan sistem pendukung keputusan dengan menggunakan metode Analytic Hierarchy Process (AHP) dan Technic for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk menentukan persentase kemungkinan penderita terinfeksi virus dengue. Sistem ini dapat digunakan oleh tenaga medis dan masyarakat untuk mendeteksi potensi infeksi DBD.
CNN Modeling for Classification of Bugis Traditional Cakes Iskandar, Imran; Jeffry, Jeffry; Fadliana, Nurul; Rimalia, Watty; Ahyana, Nurul
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1685

Abstract

Abstract This research aims to create a classification system that can recognize traditional Bugis cakes using the Convolutional Neural Network method. (CNN). Traditional Bugis cakes play an important role in Indonesia's culinary heritage, which is rich in diversity and flavor. However, the lack of documentation and sufficient recognition of these cakes could lead to the loss of cultural knowledge. In this study, a collection of images of traditional Bugis cakes was gathered and processed for training a CNN model. This model was created to recognize and classify various types of cakes based on their visual attributes. The evaluation results show that the CNN model can achieve a high level of accuracy in identifying these cakes, making it a useful tool in preserving and promoting traditional Bugis cakes. This research is expected to contribute to the development of image recognition technology and raise public awareness about the richness of local culinary heritage. Keywords : Convolutional Neural Network (CNN), Bugis Cake, Indonesian Cuisine
Pelatihan Panduan Dalam Pengoperasian Microsoft Office Bagi Perangkat Desa Iskandar, Imran; Nur, Nur Hamdani; Rimalia, Watty; Panggabean, Benny Leonard; Tenriana, Nuzul; Herianto, Dedy; Iriany, Rosary
SENTRA DEDIKASI: Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2024): Mei 2024
Publisher : Arlisaka Madani Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59823/dedikasi.v2i2.61

Abstract

Pelatihan Panduan Dalam Pengoperasian Microsoft Office bertujuan untuk meningkatkan keterampilan perangkat desa di Desa Lentu dalam menggunakan aplikasi perkantoran yang esensial. Program pelatihan ini melibatkan 20 peserta, termasuk kepala desa, sekretaris desa, bendahara, dan staf administrasi, yang sebelumnya memiliki keterbatasan dalam penguasaan Microsoft Word, Excel, dan PowerPoint. Metode pelatihan meliputi demonstrasi langsung, praktik individu, dan sesi tanya jawab, dengan fokus pada penerapan keterampilan dalam konteks administratif desa. Hasil evaluasi menunjukkan peningkatan signifikan dalam keterampilan peserta. Sebelum pelatihan, hanya 30% peserta yang memiliki pengetahuan dasar mengenai Microsoft Office. Setelah pelatihan, 85% peserta mampu menggunakan Microsoft Word untuk menyusun dokumen resmi dengan format yang benar, 80% peserta berhasil mengelola data keuangan menggunakan Microsoft Excel, dan 75% peserta dapat membuat presentasi efektif dengan Microsoft Power Point. Umpan balik dari peserta menunjukkan peningkatan kepercayaan diri dan kepuasan kerja, serta penerapan keterampilan yang lebih efisien dalam tugas-tugas administratif sehari-hari. Pelatihan ini juga menghasilkan modul panduan yang dapat digunakan sebagai referensi berkelanjutan bagi perangkat desa dan komunitas lain yang membutuhkan pelatihan serupa. Saran untuk tindak lanjut mencakup perpanjangan durasi pelatihan, pelatihan lanjutan, dan penyediaan dukungan teknis berkelanjutan. Temuan ini diharapkan dapat memberikan kontribusi pada peningkatan efektivitas administrasi desa dan pelayanan publik di masa depan.
Perancangan Sistem Monitoring Kualitas Udara Ruangan Berbasis Internet of Things (IoT) Iskandar, Imran; Rimalia, Watty; jeffry, Jeffry; Panggabean, Benny Leonard Enrico
Journal of System and Computer Engineering Vol 5 No 1 (2024): JSCE: Januari 2024
Publisher : Universitas Pancasakti

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

Abstract

The purpose of the research is to monitor air quality in the room by using MQ2, Microcontroller NodeMCU equipped with ESP8266 wireless module by using MQTT protocol for Data Communication sensor node to server. System testing uses a black box testing approach.The type of research used in this study is experimental research with the approach of PPDIOO methodology. This research is done by conducting trials where mechanical and electronic design for hardware components designed to build tools using this sensor can work according to the objectives and target desired.The results of this research show that when the sensor detects the existence 150 of smoke, gas, carbon monoxide (CO) then the value of the ADC sensor will give a warning notification in the form of an alarm generated from the tone/tone of the alarm will be active when the sensor is actively reading the value of ADC with a tolerance above 150 ppm
Implementasi Metode Topsis dan AHP dalam Deteksi Dini Penyakit Demam Berdarah Rimalia, Watty
Indonesian Journal of Intellectual Publication Vol. 3 No. 3 (2023): Juli 2023, IJI Publication
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51577/ijipublication.v3i3.423

Abstract

Demam berdarah, juga dikenal sebagai demam dengue (DBD), adalah penyakit menular yang disebabkan oleh virus dengue yang ditularkan melalui nyamuk Aedes aegypti. Penyakit ini merupakan masalah kesehatan masyarakat serius di berbagai wilayah tropis dan subtropis, termasuk Indonesia. Deteksi dini DBD memiliki peran penting dalam pengendalian penyebaran penyakit ini dan perawatan yang tepat waktu. DBD disebabkan oleh empat jenis virus dengue yang berbeda dan dapat menyebabkan gejala seperti demam tinggi, nyeri sendi dan otot, sakit kepala parah, mual, muntah, ruam, dan perdarahan ringan hingga internal. Deteksi dini melibatkan diagnosis klinis, pemeriksaan laboratorium, dan pemeriksaan imunoserologi. Pengendalian DBD melibatkan penggunaan insektisida, kelambu anti-nyamuk, edukasi masyarakat, dan vaksinasi. Deteksi dini membantu dalam perawatan tepat waktu, mencegah komplikasi, dan mengurangi angka kematian. Sistem pendeteksi dini oleh tenaga kesehatan melibatkan anamnesis, pemeriksaan fisik, tes darah, pemantauan cairan tubuh, perawatan gejala, konseling, pelaporan kasus, dan pencegahan penyebaran. Untuk mendukung deteksi dini, penelitian mengusulkan pengembangan sistem pendukung keputusan dengan menggunakan metode Analytic Hierarchy Process (AHP) dan Technic for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk menentukan persentase kemungkinan penderita terinfeksi virus dengue. Sistem ini dapat digunakan oleh tenaga medis dan masyarakat untuk mendeteksi potensi infeksi DBD.
Implementasi Algoritma Machine Learning untuk Forecasting Demand Pada Usaha Kerupuk Sehat Krusawi Wijaya, Neti Septi; Usman, Syahrul; Iskandar, Imran; Rimalia, Watty; Syam, Rahmat Fuady
Madani: Jurnal Ilmiah Multidisiplin Vol 4, No 1 (2026): February 2026
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18358038

Abstract

The rapid development of information technology has encouraged business actors to utilize data analysis to improve efficiency and competitiveness, one of which is through demand forecasting. This study aims to implement machine learning algorithms to forecast product demand in the Krusawi Healthy Crackers business. The method employed is Prophet, which was selected due to its capability to handle time series data with nonlinear trends and seasonal patterns. The data used consist of historical daily sales data from April to July 2024, which were subsequently aggregated into weekly data. The research stages include data collection, data preprocessing (data aggregation, handling missing values, and Box-Cox transformation), Prophet model design with logistic growth and custom bi-monthly seasonality, model training, and performance evaluation. The results indicate that the Prophet model provides excellent forecasting performance, achieving a Mean Absolute Percentage Error (MAPE) of 6.57% or an accuracy level of 93.43%. The model successfully captures trend and seasonal patterns in Krusawi product sales. Therefore, the implementation of machine learning algorithms using the Prophet method proves to be a reliable solution for supporting production planning and inventory management in the Krusawi healthy crackers business, and has the potential to improve operational efficiency and business decision-making.
Implementasi Aplikasi Monitoring Suhu dan PH Air Akuarium Berbasis IoT Menggunakan ESP32 Nurfajry, Muh. Awal; Leonard, Benny; Iskandar, Imran; Rimalia, Watty; Suwardoyo, Untung
Madani: Jurnal Ilmiah Multidisiplin Vol 4, No 1 (2026): February 2026
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18358467

Abstract

Water quality is an important factor in maintaining the health and survival of ornamental fish in an aquarium. The main parameters that affect water quality are temperature and acidity level (pH). Manual monitoring of these parameters has limitations; therefore, a monitoring system capable of operating in real time and continuously is required. This study aims to design and implement an Internet of Things (IoT)–based aquarium water temperature and pH monitoring application using an ESP32 microcontroller. The system utilizes a DS18B20 temperature sensor and a pH sensor to measure aquarium water conditions, after which the collected data are transmitted to a Firebase database and displayed on a web-based monitoring dashboard in real time. The research methodology includes system design, hardware and software implementation, and system functionality testing. The results show that the developed system is able to monitor aquarium water temperature and pH accurately and in real time, thereby facilitating users in monitoring water quality. With the implementation of this system, aquarium management is expected to become more effective and to optimally support fish health.
Co-Authors Fadliana, Nurul Herianto, Dedy Iriany, Rosary Iskandar, Imran Jeffry Jeffry Leonard, Benny Nur Hamdani Nur Nurfajry, Muh. Awal Nurul Ahyana Panggabean, Benny Leonard Panggabean, Benny Leonard Enrico Syahrul Usman Syam, Rahmat Fuady Tenriana, Nuzul Untung Suwardoyo Wijaya, Neti Septi