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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) BIMASTER Coding: Jurnal Komputer dan Aplikasi Jurnal Simetris Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Teknologi dan Sistem Komputer Jurnal Khatulistiwa Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) BULETIN AL-RIBAATH JURIKOM (Jurnal Riset Komputer) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) The Indonesian Journal of Computer Science
Dwi Marisa Midyanti
Universitas Tanjungpura
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering 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 Mathematics Medicine & Pharmacology Public Health

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Penerapan Algoritma Pruned Exact Linear Time (PELT) Dalam Deduplikasi Data Sensor Pada Sistem Pemantauan Tanaman Anggur Valentino, Viktorius; Ristian, Uray; Midyanti, Dwi Marisa
Coding: Jurnal Komputer dan Aplikasi Vol 13, No 2 (2025): Edisi September 2025
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/coding.v13i2.91551

Abstract

Penerapan teknologi Internet of Things (IoT) dalam sistem pemantauan tanaman anggur menghasilkan volume data sensor yang besar, dengan banyak data yang memiliki nilai serupa secara berurutan. Hal ini menyebabkan peningkatan signifikan dalam kebutuhan penyimpanan di cloud server. Penelitian ini mengimplementasikan algoritma Pruned Exact Linear Time (PELT) untuk mendeteksi titik perubahan (changepoint) dalam data guna mengurangi duplikasi dan mengoptimalkan penggunaan penyimpanan. Hasil penelitian menunjukkan bahwa deduplikasi dengan PELT menggunakan penalty Akaike Information Criterion (AIC) berhasil menurunkan jumlah data dari 2.203.730 menjadi 249.730 baris, sementara dengan Bayesian Information Criterion (BIC), jumlahnya berkurang lebih drastis menjadi 115.939 baris. Selain itu, ukuran data yang awalnya 206,476 MB berkurang menjadi 23,382 MB dengan AIC dan 10,86 MB dengan BIC. Berdasarkan hasil pengurangan tersebut, efisiensi kompresi yang diperoleh dengan penalty AIC mencapai efisiensi sebesar 88,68% dan penalty BIC mencapai 94,7%. Hasil ini membuktikan bahwa algoritma PELT efektif dalam mendeteksi titik perubahan untuk deduplikasi data sensor, sehingga secara signifikan mengurangi kebutuhan penyimpanan di cloud server. Kata kunci: Internet of Things (IoT), Deduplikasi Data, Algoritma PELT, efisiensi penyimpanan
Pengembangan dan Sosialisasi Website Sistem Informasi Desa Punggur Kecil Sebagai Media Informasi Desa Suhardi Suhardi; Hirzen Hasfani; Ikhwan Ruslianto; Rahmi Hidayati; Cucu Suhery; Tedy Rismawan; Dwi Marisa Midyanti; Syamsul Bahri; Irma Nirmala; Uray Ristian; Kasliono Kasliono; Karika Sari; Hafiz Muhardi
ABDI: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 7 No 3 (2025): Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : Labor Jurusan Sosiologi, Fakultas Ilmu Sosial, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/abdi.v7i3.1279

Abstract

Pengembangan dan sosialisasi website Sistem Informasi Desa Punggur Kecil bertujuan untuk menyediakan media informasi yang efektif bagi masyarakat Desa Punggur Kecil, Kabupaten Kubu Raya. Kegiatan ini merupakan bagian dari Pengabdian Pada Masyarakat dengan berfokus pada pembangunan website yang berfungsi sebagai pusat informasi desa, mencakup berbagai aspek antar lain profile desa, informasi public, informasi kegiatan, dan transparansi dana desa. Kegiatan dimulai dengan pertemuan dengan kepala desa untuk membahas rencana pembuatan sistem informasi dan pelaksanaan sosialisasi. Setelah didapatkan kebutuhan menu website yang dibutuhkan, dibangun website sistem informasi Desa Punggur Kecil. Setelah itu, dilaksanakan sosialisasi penggunaan website di lingkungan desa Punggur Kecil. Sosialisasi yang dilaksanakan pada tanggal 10 Juli 2024 di Aula Kantor Desa Punggur Kecil dari jam 13.00 WIB. Tujuan dari sosialisasi ini adalah untuk memperkenalkan dan memberikan pemahaman kepada masyarakat mengenai penggunaan dan manfaat website. Peserta yang mengikuti kegiatan ini sebanyak 23 peserta, diantaranya pegawai kantor desa, ketua RT, BPD, dan masyarakat. Hasil dari kegiatan sosialisasi menunjukkan bahwa mayoritas peserta dapat memahami fungsi dan cara mengakses website dengan baik. Kegiatan PKM ini telah berhasil memperkenalkan teknologi informasi yang berguna untuk meningkatkan transparansi dan efisiensi dalam pengelolaan desa.
Single hidden layer feedforward neural networks for indoor air quality prediction Midyanti, Dwi Marisa; Bahri, Syamsul; Ilhamsyah, Ilhamsyah; Khairunnisa, Zalikhah; Midyanti, Hafizhah Insani
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp322-328

Abstract

Indoor air quality (IAQ) has become a problem because it affects human health, comfort, and productivity. Predicting air quality is a complex task due to the dynamic nature of IAQ variable values simultaneously. In this study, the single hidden layer feedforward neural networks model is used, namely radial basis function (RBF), self-organizing maps (SOM)-RBF, and extreme learning machine (ELM) to classify IAQ. This study also observed the effect of the number of neurons in the hidden layer on the model accuracy and overfitting of each network. The experimental results show that the number of neurons in the hidden layer can affect the accuracy of the RBF and SOM-RBF models. Among the three models used, RBF produces very good training data accuracy but also the most significant overfitting value. The largest overall accuracy was obtained using SOM-RBF, with a value of 86.37%.
Otomatisasi Pengontrolan Kualitas Air Pada Akuarium Ikan Arwana Berbasis IOT Menggunakan Logika Fuzzy Tsukamoto Ade Muhamad Nurhadi; Dwi Marisa Midyanti; Suhardi Suhardi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6947

Abstract

Arowana fish is an ornamental fish that has a beautiful body shape and color that makes it have a high price, and requires excellent care. The quality of the water in the aquarium must be maintained so that the Arowana fish are not stressed, sick, or die. However, many Arowana owners do not monitor water conditions closely. Therefore, a system is needed that can monitor the state of the aquarium environment, including automatic and manual water changes from the website. In this study using Arduino uno as a microcontroller connected to a pH and turbidity sensor, then NodeMCU ESP32 was used to send data to the internet and to perform the calculation process of Tsukamoto's fuzzy logic. The test results obtained an average accuracy on pH sensors of 96.62%, on turbidity sensors an average accuracy of 92.84%, on ultrasonic sensors an average accuracy of 99.62%. The system also tested Tsukamoto's fuzzy logic where the results were fuzzy with an accuracy of 83%. Testing of the system as a whole was carried out for 4 days. From the tests carried out, the average water pH per day results are 7.1 and turbidity of 18 NTU and all water quality conditions can be met according to the desired output using 9 rule bases.
Penentuan Pencemaran Air Menggunakan Metode Self Organizing Maps (SOM) Deni; Midyanti, Dwi Marisa; Hidayati, Rahmi
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3036

Abstract

Water pollution is the entry of a component or substance into water, which causes water quality to decrease. The decrease in water quality causes the water to be unfit and affects the community's health. Therefore, an application for determining the water quality level building using the SOM algorithm with several data input parameters: Fluoride, Hardness, and Nitrite. These parameters use for data clustering in determining clean and polluted water. The SOM algorithm arranges SOM neurons based on the data input values ​​in a SOM cluster. For testing the SOM method on 114 data, the Silhouette Coefficient value was used to find the best number of clusters. Silhouette Coefficient will evaluate clustering the proximity of the distance between data. The test was carried out 27 times with variations of the experiment with the learning rate starting from 0.1 to 0.9 and the number of clusters from 2 to 4 to get the best Silhouette Coefficient value. The result of clustering the best silhouette coefficient value obtained is 0.7276473444141 with 3 clusters and the learning rate of 0.2.
Co-Authors , Syahru Rahmayuda, Haris Febriyanto Ramadhan , Sampe Hotlan Sitorus Abdul Hamid Abdul Hamid Ade Muhamad Nurhadi Adi Kurnia Agung Jati Swiknyo Arista, Agamita Sasya Cahyani Astrid Lestari Tungadi Caecilia Cantica Gita Mileniae Ahen Chairul Mukmin Cucu Suhery Dedi Triyanto Deni Deni Dian Prawira, Dian Edwin Rianto Erick Alfons Lisangan Farhan Fajar Luthfi Firdaus, Akmal Firdaus, Nurul Fajri 'Aini Hafiz Muhardi Halawa, Yasman Hanafi, Ahmad Abdul Hansen Alexander Rustan Herlian, Wildan Hirzen Hasfani Ikhwan Ruslianto Ilham Syah Ilhamsyah Indrawan, Muhammad Catur Irma Nirmala Junianti, Suci Kartika Sari Kasliono Kasliono Khairunnisa, Zalikhah Kurniawan, Robbi Lestari, Ayu Lathalia Mahfuza, Sri Martha, Shantika Midyanti, Hafizhah Insani Mochammad Imron Awalludin Mulia, Agung Wira Neneng Suriati Nova Andaresta Qadari, Ilham Latul Rahman, Reiza Aditya Rahmi Hidayati Renny Puspita Sari Rikki Pratama Saputro, Arinto Mangku Shantika Martha Suhardi Syamsul Bahri Syamsul Bahri Tedy Rismawan Tedy Rismawan Tedy Rismawan That, Shau Thomas Adi Putra Tri Floren Doni Uray Ristian Valentino, Viktorius Wahiddatun Nisa Yunizar, Ahmad