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All Journal Jurnal Ilmiah Universitas Batanghari Jambi Syntax Literate: Jurnal Ilmiah Indonesia JURNAL TEKNOLOGI DAN OPEN SOURCE KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Jurnal Jamu Indonesia JUKI : Jurnal Komputer dan Informatika Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Ekonomi KIAT Journal of Dinda : Data Science, Information Technology, and Data Analytics STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer J-Icon : Jurnal Komputer dan Informatika Kohesi: Jurnal Sains dan Teknologi Jurnal Informatika: Jurnal Pengembangan IT Indonesian Journal of Jamu NJCOM: Community Service Journal
Ary Prabowo
Universitas Esa Unggul, Jakarta, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences Other

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Implementasi Internet of Things (Iot) pada Sistem Penyiraman Otomatis Bibit Alpukat dengan Aplikasi Mobile Adigunawan, Adigunawan; Tjahjono, Budi; Irawan, Bambang; Prabowo, Ary
Jurnal Ilmiah Universitas Batanghari Jambi Vol 25, No 3 (2025): Oktober
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/jiubj.v25i3.6332

Abstract

This research aims to develop an Internet of Things (IoT)-based automatic watering system with real-time monitoring features for soil moisture and pH levels, designed to support the cultivation of avocado seedlings. The system utilizes an ESP32 microcontroller connected to two soil moisture sensors and one pH sensor, and is controlled through a mobile application built with Flutter. Sensor data is transmitted to a backend server using the MQTT protocol, while communication between the application and the backend server is conducted via a REST API. Users can configure watering schedules and durations, as well as set moisture thresholds to trigger automatic watering. Testing results show that the system functions effectively in monitoring soil conditions and performing watering based on the configured settings.
Penggunaan Metode MDLC dalam Pengembangan Game Visual Novel Anastasia Love Story berbasis Ren'Py Pasha, Muhammad Kemal; Prabowo, Ary
JUKI : Jurnal Komputer dan Informatika Vol. 7 No. 2 (2025): JUKI : Jurnal Komputer dan Informatika, Edisi Nopember 2025
Publisher : Yayasan Kita Menulis

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

Abstract

Abstrak Penelitian ini dilaksanakan dengan tujuan untuk mengembangkan game visual novel berjudul Anastasia Love Story sebagai media interaktif yang mampu meningkatkan keterlibatan emosional dan minat baca pengguna. Game ini ditujukan untuk remaja hingga dewasa muda yang menyukai cerita romansa dan narasi bercabang. Pengembangan dilaksanakan dengan mempergunakan metode Multimedia Development Life Cycle (MDLC) yang terbagi menjadi 6 (enam) proses atau tahapan: concept, design, material collecting, assembly, testing, dan distribution. Aplikasi Ren’Py digunakan sebagai platform pengembangan, dengan penambahan fitur interaktif seperti branching storyline, keputusan berbatas waktu, serta mini game untuk memperkaya pengalaman bermain. Hasil yang diperoleh dalam tahapan pengujian memperlihatkan bahwa game mampu berjalan dengan baik, menampilkan cerita yang menarik, visual yang mendukung suasana, serta audio yang memperkuat keterlibatan pemain. Fitur-fitur utama yang dikembangkan dapat digunakan dengan baik oleh pengguna dan mendukung alur cerita sesuai dengan harapan. Game ini juga dinilai relevan sebagai sarana hiburan naratif yang edukatif dan emosional. Anastasia Love Story efektif menjadi media visual novel interaktif yang sesuai dengan karakteristik pengguna sasaran. Kata Kunci: Game, Interaktif, MDLC, Novel Visual, Ren’Py Abstract This research aims to establish a visual novel game titled Anastasia Love Story as an interactive medium that can enhance users' emotional engagement and reading interest. The game targets teenagers to young adults who enjoy romance stories and branching narratives. The development process follows the Multimedia Development Life Cycle (MDLC) method, consisting of 6 (six) steps as follows: concept, design, material collecting, assembly, testing, and distribution. The Ren’Py engine is used as the development platform, with interactive features such as branching storylines, time-limited decision-making, and mini-games to enrich the playing experience. The test results show that the game runs well, presents an engaging story, supportive visuals, and audio that enhances player immersion. The main features developed are accessible to users and support the story flow as intended. This game is also considered relevant as an educational and emotional narrative entertainment medium. Anastasia Love Story proves effective as an interactive visual novel media suited to the target users' characteristics. Keywords: Game, Interactive, MDLC, Visual Novel, Ren’Py
Identification of Java Tea Adulteration by Babadotan and Tekelan using Machine Learning Ary Prabowo; Wisnu Ananta Kusuma; Annisa; Mohamad Rafi
Jurnal Jamu Indonesia Vol. 7 No. 3 (2022): Jurnal Jamu Indonesia
Publisher : Tropical Biopharmaca Research Center, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jji.v7i3.273

Abstract

Java Tea (Orthosiphon aristatus) is a common herbal medicinal plant that functions as a health treatment and treats various diseases. The high demand for Java Tea causes high prices and a decrease in the amount of medicinal plant raw materials, causing various quality control problems such as the content of various bioactive components and adulteration from babadotan and tekelan. So far, the detection of adulteration has been carried out by various analyzes, including chemical analysis and statistical methods to process data. The data used is of high dimension with a very high-density level, thus causing difficulties in classification. The mixed data of Orthosiphon aristatus consists of 1201 features with a total sample of 216. This study uses a Random Forest (RF) method with a total of 100 trees, and the RF method is combined with the Recursive Feature Elimination (RFE) method. In the RF and RFE that can be produced, the optimum value for the number of features is 244. The experimental evaluation results revealed that the proposed method could achieve a high accuracy of 81.82% in identifying Orthosiphon aristatus.
Algoritma Untuk Tingkatkan Pengalaman Proses Pemesanan Makanan Berbasis Web: (Studi Kasus: Dapur Imut) Suryana, Septiara Pratama; Prabowo, Ary
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i4.57681

Abstract

Aplikasi penjualan online merupakan bagian penting dari sistem aplikasi yang sangat dibutuhkan oleh pelaku bisnis saat ini, terutama dalam menghadapi perkembangan teknologi. Teknologi informasi, khususnya internet, memberikan kemudahan dalam melakukan pembelian dan transaksi dari mana saja dan kapan saja. Namun, Toko Dapur Imut hingga kini belum memiliki aplikasi yang dapat memfasilitasi transaksi pembelian secara daring. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan aplikasi penjualan berbasis web yang mampu meningkatkan pengalaman pemesanan makanan dan transaksi secara fleksibel. Metode yang digunakan dalam pengembangan sistem ini adalah metode Waterfall, yang terdiri dari tahapan analisis, perancangan, implementasi, pengujian, dan pemeliharaan. Setiap tahapan dilakukan secara sistematis guna memastikan sistem berjalan dengan baik dan sesuai kebutuhan pengguna. Hasil dari penelitian ini adalah terciptanya sistem aplikasi penjualan online berbasis web untuk Toko Dapur Imut, yang dilengkapi dengan fitur pencarian menu, pemesanan, serta pembelian produk secara langsung melalui aplikasi. Dengan adanya sistem ini, diharapkan dapat mempermudah pelanggan dalam melakukan transaksi sekaligus meningkatkan efisiensi dan jangkauan pemasaran toko.
Pendekatan Naive Bayes Campuran untuk Klasifikasi Email Spam dengan Metode Machine Learning Lainnya Aditya, Bintang; Kristy Wijaya, Marchello; Prabowo, Ary
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 2 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i2.17166

Abstract

Nowadays, email is a communication media that is often used in the digital era, with various advantages offered by email, accompanied by the rise of email spam which can disrupt the comfort of its users and accessibility on the email service provider platform. Using manual spam filtering techniques has proven to be very time-consuming and labor-intensive, so an alternative technique is needed that can perform sorting automatically using Machine Learning. This research aims to develop a form of spam detection model that uses a mixed Naive Bayes approach that combines various forms of TF-IDF feature representation with various statistical features that can calculate message length, number of capital letters, and various number of links, and compare its performance with various other algorithm approaches consisting of Support Vector Machine, Logistic Regression, and Random Forest, this study uses a public dataset containing examples of 5,572 emails containing important emails and spam emails combined. The evaluation form will be calculated using the metrics Accuracy, Precision, Recall, F1-Score, and Training Time. The results of the experiment explain that Naive Bayes with Mixture is able to produce an accuracy of 96.4% with advantages in calculating computational efficiency, but Random Forest has the highest accuracy level reaching 97.9%. So it shows that this research proves that Naive Bayes with various mixed approaches is worthy of being applied to an Email Spam detection system that requires high speed and efficiency.
The The Use of the K-Means Algorithm in Analyzing E-Commerce Consumer Segmentation: A Case Study of the Online Retail Dataset (UK) Kusdaryanto, Ardo; Wijanarko, Christoporus Dimas; Widyantara Usat, Paskalis Dwi; Prabowo , Ary
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4798

Abstract

This study aims to analyze consumer segmentation on e-commerce platforms by employing the K-Means algorithm as the primary clustering method. Using the Online Retail (UK) dataset, which contains comprehensive transaction records from a UK-based online retail company, the research focuses on identifying behavioral patterns among consumers. Several key variables, including purchase frequency, total transaction value, and recency or visit time, are processed to create meaningful clusters that represent different types of consumer behavior. The K-Means algorithm is applied through a series of preprocessing steps, such as data cleaning, feature selection, and normalization to ensure accurate clustering results. Once the clusters are formed, each consumer group is analyzed to determine its characteristics, purchasing tendencies, and potential value to the business. The segmentation results provide valuable insights for businesses in developing targeted marketing strategies and personalized service offerings. By understanding the unique preferences and behaviors within each cluster, companies can optimize promotional efforts, improve customer retention, and enhance overall user experience. The findings indicate that data-driven segmentation using the K-Means algorithm is a highly effective approach for gaining deeper, actionable insights into consumer behavior, thereby supporting more strategic decision-making in the e-commerce environment.
Klasifikasi kecanduan smartphone mahasiswa universitas esa unggul menggunakan machine learning dan sas-sv Verrel, Anggoro; Maulana, Irfan Zidny; Liu, Vico Andrean; Prabowo, Ary
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.9817

Abstract

The digital era has made smartphones an inseparable part of students' lives, but it also raises the risk of addiction that negatively impacts academic achievement and mental health. This research aims to develop and evaluate machine learning models capable of classifying the level of smartphone addiction among Esa Unggul University students. Data were collected from 32 student respondents through an online questionnaire adopting the validated psychometric instrument, the Smartphone Addiction Scale-Short Version (SAS-SV). Addiction levels were categorized into two classes: 'High', which refers to the gender-specific addiction risk threshold from Kwon et al. (2013), and 'Moderate', which includes scores below that threshold. Four classification algorithms—Logistic Regression, K-Nearest Neighbors (KNN), Decision Tree, and Random Forest—were implemented to compare their performance. To address class imbalance in the data, the SMOTE oversampling technique was applied to the training data. Model evaluation was based on accuracy, precision, recall, and F1-score. The research results show that the Logistic Regression model achieved the best performance with an accuracy of 1.0000 and an average F1-score of 1.00 on the test data. Nevertheless, it should be noted that this perfect performance was obtained from a very limited test data size (8 samples), so generalization requires further validation. Feature importance analysis from the Random Forest model identified that the question related to Planned tasks/work often interrupted by smartphone use (Q0) was the most dominant predictor. These results indicate that machine learning models based on psychometric scales have initial potential as a screening and exploratory tool to identify students at risk of smartphone addiction, but require extensive development and validation on larger data before practical implementation.
RANCANG BANGUN SISTEM PAKAN IKAN MOLLY OTOMATIS BERBASIS IOT DENGAN PEMANTAUAN SUHU DAN KUALITAS AIR Naufal Aulio Sopian; Ary Prabowo
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 5 No. 1 (2026): Februari
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v5i1.7446

Abstract

Perkembangan teknologi Internet of Things (IoT) memungkinkan penerapan otomatisasi pada pemeliharaan ikan hias yang sebelumnya masih dilakukan secara manual. Toko Hoki Akuarium menghadapi permasalahan berupa pemberian pakan yang tidak konsisten serta keterbatasan pemantauan suhu dan kualitas air secara real-time, terutama ketika pemilik tidak berada di lokasi. Penelitian ini merancang sistem pemberian pakan ikan molly otomatis berbasis IoT yang dilengkapi pemantauan suhu dan kualitas air menggunakan parameter Total Dissolved Solids (TDS) serta terintegrasi dengan aplikasi mobile berbasis Dart. Komunikasi data antara perangkat IoT dan aplikasi mobile menggunakan protokol Message Queuing Telemetry Transport (MQTT) yang bersifat ringan dan berbasis publish–subscribe, sehingga memungkinkan pengiriman data sensor dan status sistem secara real-time. Metode pengembangan sistem menggunakan model prototipe yang meliputi analisis kebutuhan, pembuatan prototipe, evaluasi, implementasi, dan pengujian. Hasil pengujian menunjukkan sensor TDS memiliki akurasi sebesar 98,03% menggunakan larutan standar 342 ppm, sensor suhu DS18B20 memiliki akurasi 96,24%, dan sensor loadcell memiliki akurasi 91,4%. Pengujian aktuator menunjukkan motor servo, pompa air, dan aerator berfungsi sesuai dengan skenario pengujian. Aplikasi mobile mampu menampilkan data suhu, TDS, dan status sistem secara real-time serta memudahkan pengguna dalam melakukan pemantauan dan pengendalian. Secara keseluruhan, sistem ini dinilai efektif, stabil, dan layak diterapkan untuk meningkatkan efisiensi pemberian pakan serta menjaga kualitas lingkungan akuarium ikan molly.
Mengembangkan Bakat dan Potensi Anak-Anak Usia 3 sampai 10 Tahun melalui Kegiatan Edukatif dan Kolaboratif Qori Halimatul Hidayah; Dewi Setiowati; Ary Prabowo; Nurmala
NJCOM: Community Service Journal Vol. 2 No. 1 (2026): January
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18316683

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengembangkan bakat serta potensi anak-anak Taman Pendidikan Al-Qur’an (TPA) Yayasan Nur Ummiyah Kedoya Selatan, Jakarta Barat, dengan fokus utama pada peningkatan minat belajar dan penguatan religiusitas sejak usia dini. Sasaran kegiatan ini adalah anak-anak berusia 3 hingga 10 tahun yang mengikuti kegiatan pembelajaran di TPA tersebut. Pelaksanaan program dilakukan secara kolaboratif oleh dosen dan mahasiswa melalui penerapan metode edutainment, yaitu pendekatan pembelajaran yang memadukan unsur bermain dengan proses belajar, serta melalui penyelenggaraan berbagai lomba edukatif. Pendekatan tersebut dipilih guna menciptakan lingkungan pembelajaran yang menyenangkan, interaktif, dan sesuai dengan karakteristik perkembangan anak usia dini. Hasil kegiatan menunjukkan adanya peningkatan antusiasme dan partisipasi anak-anak dalam proses pembelajaran, sekaligus tumbuhnya minat terhadap kegiatan keagamaan. Program ini diharapkan dapat menjadi model efektif dalam pengembangan bakat dan potensi anak serta memperkuat sinergi antara perguruan tinggi dan masyarakat dalam bidang pendidikan dan pembinaan karakter sejak usia dini.
Co-Authors Adigunawan, Adigunawan Aditya, Bintang Akbar, Habibullah Annisa Annisa Arini Winur Baeti Azzahra, Fayza Bambang Irawan Binastya Anggara Sekti Budi Tjahjono Desmond Orix Khoermala Dzikrya, Kaysa Herwanto, Agus Innova, Zacky Kalagi, Richard Kevin Maruli Kristy Wijaya, Marchello Kusdaryanto, Ardo Latumapayahu, Febrian Firmansyah Liu, Vico Andrean M. Rafi Maulana, Irfan Zidny Mohamad Rafi Naufal Aulio Sopian Niken Rahma Diasri Nizirwan Anwar Nurmala Nurmala Pasha, Muhammad Kemal Poppy Camenia Jamil Pramuditya, Benno Qori Halimatul Hidayah Ramadhan, Ridwan Ratna Yulika Go Saputra, Ragil Raditya Setiowati, Dewi Sharen Ming Sianggara Sinta Yulyanti Suryana, Septiara Pratama Verrel, Anggoro Widyantara Usat, Paskalis Dwi Wijanarko, Christoporus Dimas Wisnu Ananta Kusuma