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All Journal bit-Tech Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Puan Indonesia Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Ariawan, Angga
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health

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Inovasi AIoT (Artificial Intellegence Internet of Things) untuk Penyiraman Otomatis di RPTRA Abdi Praja Ariawan, Angga; Hendra, Anderson
PUAN INDONESIA Vol. 6 No. 1 (2024): Jurnal Puan Indonesia vol 6 no 1 Juli 2024
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v6i1.285

Abstract

The Abdi Praja RPTRA is a green open space that faces challenges in inefficient watering of plants. This Community Service Program (PkM) aims to overcome this problem by implementing an automatic watering system based on artificial intelligence (AI) and the Internet of Things (IoT). This program aims to improve water use efficiency, plant health and environmental quality as well as supporting reforestation and sustainability of green spaces. Media Nusantara Citra University students will be actively involved in the development and application of this technology, as well as providing education to the public about environmentally friendly technology. This automatic watering system is adjusted to weather conditions and air humidity which will be processed using the Fuzzy Logic algorithm as real-time artificial intelligence, so it can save water and ensure optimal care for plants.
Optimasi Prediksi Gagal Jantung dengan Teknik Ensemble Bagging Pada Neural Network Ariawan, Angga
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.426

Abstract

Prediction of heart failure is an important step in the early management of serious cardiovascular disease. This research uses the Ensemble bagging algorithm with Neural Network. The dataset is taken from Heart Failure Clinical Records available in the UCI Machine Learning Repository. The use of training data in this research was 80% of the total data set, and 20% of the test data. The dataset is divided into two feature models, namely features with categorical data and continuous data. At the data transformation stage, continuous data is subjected to value scaling. several single classifier machine learning algorithms have been tested in this research such as Logistic Regression, Artificial Neural Networks (ANN), Naïve Bayes, SVM. Single classifier Artificial Neural Networks (ANN) produces an accuracy value of 82%. Ensemble learning using the bagging method on Artificial Neural Networks (ANN) was carried out to get a higher accuracy value. Ensemble learning using the bagging method on Artificial Neural Networks (ANN) obtained an accuracy value of 98%. This method is proven to have increased the accuracy value by 16% better than just using a Single Classifier Artificial Neural Networks (ANN) in the case of the Heart Failure Clinical Records dataset.
Smart Sprout: Irigasi Cerdas Berbasis AIoT untuk Pertanian Modern dan Ramah Lingkungan Ariawan, Angga
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1841

Abstract

Pertanian modern menghadapi tantangan dalam memenuhi kebutuhan pangan global sembari menjaga kelestarian lingkungan. Sistem irigasi tradisional sering kali tidak efisien, menyebabkan pemborosan air dan energi. Penelitian ini memperkenalkan SMART SPROUT, sebuah sistem irigasi cerdas berbasis Artificial Intelligence of Things (AIoT) yang dirancang untuk mendukung pertanian modern yang efisien dan ramah lingkungan. Sistem ini mengintegrasikan teknologi sensor IoT untuk memantau parameter lingkungan, seperti kelembapan tanah, suhu, dan curah hujan, serta algoritma kecerdasan buatan untuk mengoptimalkan jadwal irigasi secara real-time. Selain itu, SMART SPROUT memanfaatkan energi terbarukan sebagai sumber daya operasional, sehingga mendukung prinsip keberlanjutan. Hasil pengujian di lapangan menunjukkan bahwa sistem ini mampu mengurangi konsumsi air hingga 30% dibandingkan dengan metode irigasi konvensional, tanpa mengorbankan produktivitas tanaman. Penelitian ini memberikan kontribusi signifikan dalam pengembangan teknologi pertanian pintar yang mendukung efisiensi sumber daya sekaligus melestarikan lingkungan. Sistem ini memastikan bahwa tanaman menerima jumlah air yang optimal untuk pertumbuhannya, terutama di daerah dengan curah hujan yang tidak konsisten atau tidak mencukupi, sekaligus mengoptimalkan waktu dan upaya yang dihabiskan petani untuk irigasi. Ini menggunakan logika fuzzy, algoritma kecerdasan buatan, untuk menentukan kebutuhan air berbagai jenis tanaman berdasarkan data suhu dan kelembaban yang dikumpulkan dari sensor lingkungan. Data ini terintegrasi dengan teknologi IoT menggunakan ESP32 untuk memberikan pembaruan irigasi secara real-time. Dengan mengotomatiskan proses, sistem menghilangkan risiko jadwal irigasi yang terlupakan atau tidak konsisten, yang sering menyebabkan fai tanaman.
Sinergi MNC University, SHARP Class, dan SMK Boedi Luhur dalam Pengembangan UMKM Ariawan, Angga; Rizki, Sestri Novia; Herdadi, Anintyo
PUAN INDONESIA Vol. 6 No. 2 (2025): Jurnal Puan Indonesia Vol 6 No 2 Januari 2025
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v6i2.338

Abstract

The development of Micro, Small and Medium Enterprises (MSMEs) is one of the strategic efforts to encourage local and national economic growth. However, low technological literacy and data analytical capabilities are the main obstacles for MSMEs in facing competition in the digital era. To answer these challenges, MNC University, in collaboration with the SHARP Class Corporate Social Responsibility (CSR) program from PT SHARP Electronics Indonesia, as well as Boedi Luhur Bekasi Vocational School, is implementing a technology-based community service program. This program focuses on providing data analytics skills to vocational school students as young people who have the potential to support MSMEs in their surrounding environment. This activity includes intensive training on data processing using computer science-based tools and methods, designed to improve students' ability to understand, analyze and apply data in making business decisions. A collaborative approach involving academics, industry practitioners and vocational educators ensures that the material presented is relevant to the needs of industry and MSMEs. The results of this program show a significant increase in participants' understanding and skills in data analytics, as well as the real contribution of Boedi Luhur Vocational School students in supporting the development of local MSMEs. This study provides empirical evidence that synergy between educational institutions, industry and vocational schools can be a model of sustainability in developing technology-based human resource capacity.
PENGEMBANGAN SPK SELEKSI PERANGKAT NAGARI BERBASIS METODE SAW DI DESA KUMANGO UTARA Rizki, Sestri Novia; Yunaidi, Andri; Nasution, Vani Maharani; Neli, Mery Ulfa; Fitrianto, Adi; Ariawan, Angga
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 1 (2025): Jurnal Tikomsin
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i1.947

Abstract

The selection of village apparatus is an important process in supporting governance at the village level. However, the selection process carried out manually often causes subjectivity and is less efficient. Therefore, a decision support system (DSS) is needed that is able to assist the selection process objectively and in a structured manner. This study aims to develop a DSS for selecting village apparatus based on the Simple Additive Weighting (SAW) method, which is able to provide assessment results based on several relevant criteria. The criteria used in this system include: leadership, discipline, academic achievement, communication skills, ethics and attitudes, and initiative and creativity. The SAW method was chosen because of its ability to calculate the aggregate value of each alternative based on the weight and value of each criterion. This system was developed using the waterfall approach and implemented in the form of a web-based application. The test results show that the system can help simplify the selection process and provide more objective and transparent results. With this DSS, it is hoped that the village apparatus selection process can be carried out more professionally and accountably.
Co-Authors Fitrianto, Adi Hendra, Anderson Herdadi, Anintyo Nasution, Vani Maharani Neli, Mery Ulfa Rizki, Sestri Novia Yunaidi, Andri