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All Journal Jurnal Pekommas DoubleClick : Journal of Computer and Information Technology MULTINETICS Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang International Journal of Engineering, Technology and Natural Sciences (IJETS) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Mitra Akademia: Jurnal Pengabdian Masyarakat Brilliance: Research of Artificial Intelligence Jurnal Pendidikan Amartha Jurnal Informasi dan Teknologi (JITU)
Sari, Risna
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Social Sciences Other

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Implementasi Enkripsi Dekripsi Paket Data pada Rancang Bangun Smart Home Menggunakan Protokol MQTT Sari, Risna; -, Ayu Rosyida Zain; Marta Surya Cakraningrat
MULTINETICS Vol. 8 No. 2 (2022): MULTINETICS Nopember (2022)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v8i2.4110

Abstract

Internet of Things (IoT) technology can be applied in many ways, one of which is home automation or Smart Home. There are several sensors and actuator modules in the Smart Home system such as movement sensors (PIR) to detect the presence of living things around the house, radio wave frequency-based authentication sensors (RFID) to ensure that only registered residents can enter the house, actuator servo actuator (SG90) which is used to open the door, and actuator switch (Relay) to automatically turn off the lights. All activities at home that apply the Smart Home concept can be done automatically without touching it directly by using a special application called SUSAH v2, which is an Android-based application created using MIT App Inventor. What is still a concern is the lack of the Smart Home system where the network usInternet of Things (IoT) technology can be applied in many ways, one of which is home automation or Smart Home. There are several sensors and actuator modules in the Smart Home system such as movement sensors (PIR) to detect the presence of living things around the house, radio wave frequency-based authentication sensors (RFID) to ensure that only registered residents can enter the house, actuator servo actuator (SG90) which is used to open the door, and actuator switch (Relay) to automatically turn off the lights. All activities at home that apply the Smart Home concept can be done automatically without touching it directly by using a special application called SUSAH v2, which is an Android-based application created using MIT App Inventor. What is still a concern is the lack of the Smart Home system where the network used is still a LAN and can only be controlled if the user is on the same network as the Smart Home system. Therefore, this research objective is to developing, testing, and implementing security using cryptographic methods and the integration of the Antares Platform based on the MQTT protocol to be able to make the Smart Home system accessible on a WAN anywhere and anytime, taking into account the security of the data information sent. To create an IoT-based Smart Home system that is more efficient and remains safe when used.ed is still a LAN and can only be controlled if the user is on the same network as the Smart Home system. Therefore, this research objective is to developing, testing, and implementing security using cryptographic methods and the integration of the Antares Platform based on the MQTT protocol to be able to make the Smart Home system accessible on a WAN anywhere and anytime, taking into account the security of the data information sent. To create an IoT-based Smart Home system that is more efficient and remains safe when used.
IMPLEMENTASI ALGORITMA DECISION TREE DENGAN FITUR SELEKSI WEIGHT BY INFORMATION GAIN Ali, Euis Oktavianti; Agustin, Maria; Sari, Risna
MULTINETICS Vol. 9 No. 2 (2023): MULTINETICS Nopember (2023)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v9i2.5715

Abstract

This paper aims to apply the weight selection feature by considering the Gain Ratio value in the decision tree algorithm in classifying student academic scores. We determine the feature selection from the gain ratio based on the split value information to reduce the feature's (attribute) bias value. The highest Gain Ratio' value will be the root of the branching in the tree in which becomes a determining feature (attribute) of student graduation. We use 82 data which are divide into two classes called a pass and a not pass. From the data, we know that the attribute ip smt 7 got the highest gain ratio value with 0.581. On the other hand, the multimedia introduction attribute got the lowest gain ratio value with 0.070. The calculation model using cross-validation with a value of k = 5 resulted in optimal performance. The resulting accuracy is 79.19% and AUC 0.778 using the decision tree algorithm. The threshold value of the gain ratio used is 1.00 so that four attributes are not used in this paper. feature selection using weights with information gain ratio will select the attribute selection process to be built in the model.
Aplikasi Sakubalita Sebagai Media Edukasi Perkembangan Balita dan Skrining Hipotiroid Kongenital Ismail, Iklima Ermis; Sari, Risna; Oktavianti, Euis; Hidayati, Anita
Abdimas Galuh Vol 6, No 1 (2024): Maret 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i1.13176

Abstract

Stunting adalah masalah gizi buruk yang disebabkan oleh kekurangan asupan gizi yang terus menerus yang menyebabkan anak mengalami gangguan pertumbuhan, yaitu tinggi badan yang lebih rendah atau pendek (kerdil) dari standar usianya. Hipotiroidisme kongenital adalah penyakit yang disebabkan oleh kurangnya hormon tiroid di dalam rahim. Kekurangan hormon tiroid menyebabkan gangguan pada tumbuh kembang anak pada masa emasnya.  Untuk pencegahan stunting dan HK, saat ini Dinas Kesehatan (Dinkes) Depok menggunakan buku Kesehatan Ibu dan Anak (KIA) sebagai media edukasi. Berbekal adanya beberapa materi perkembangan balita yang dikemas dalam format e-book berupa buku KIA didistribusikan melalui posyandu dirasa kurang efektif dan kurang sesuai dengan karakter lingkungan saat ini.Tujuan kegiatan pengabdian masyarakat ini adalah pengembangan Aplikasi SakuBalita yang dikemas dalam format video motion grafis yang lebih menarik untuk disimak dan ditonton. Pengabdian masyarakat SakuBalita dikembangkan melalui 5 tahap, yaitu identifikasi permasalahan dengan mitra, pembuatan media edukasi motion grafis, pengujian aplikasi motion grafis, integrasi dengan Depok Single Window (DSW) dan sosialisasi kepada masyarakat. Pembuatan motionn grafis SakuBalita dikembangkan menggunakan software Adobe Illustrator dan Adobe After Effect, menghasilkan 12 video yang disesuaikan dengan usia perkembangan bayi.Aplikasi ini diharapkan dapat dimanfaatkan secara lebih luas oleh fasilitator dan masyarakat sebagai media edukasi pencegahan stunting dan HK.
Utilizing ResNet-50 for Deep Learning-Based Rice Leaf Disease Detection Sari, Risna; Asbudi, Hedy Leoni; Susilawati, Fitrah Eka
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7425

Abstract

Rice is a primary global food commodity, yet its productivity is frequently threatened by various diseases that significantly reduce both yield quality and quantity. Traditional manual diagnosis by farmers is often subjective, time-consuming, and prone to inaccuracies, necessitating more efficient automated solutions. This research evaluates the ResNet50 architecture for the automated classification of rice leaf diseases through digital image analysis. The study specifically investigates the model's performance on a specialized dataset and analyzes how different data splitting ratios influence accuracy and stability. A public dataset comprising four classes—Hispa, Healthy, Leaf Blast, and Brown Spot—was employed. The data underwent rigorous labeling, pre-processing, and augmentation to enhance sample diversity before being partitioned into training and testing sets using three ratios: 85:15, 80:20, and 90:10. The ResNet50 model was implemented using transfer learning with pre-trained ImageNet weights and fine-tuned on the classification layers. Experimental results reveal that the 85:15 split ratio achieved the highest accuracy of 81.48%, followed by 78.77% for the 80:20 ratio and 76.21% for the 90:10 ratio. These findings suggest that ResNet50 provides competitive performance for rice disease detection. Furthermore, achieving an optimal balance between training and testing data is critical for maximizing model generalization within modern smart farming applications.
Co-Authors -, Ayu Rosyida Zain Agus Setiawan Ali, Euis Oktavianti Anggi Muhammad Rifa'i Anita Hidayati Antariksa, Vita Aprilya, Warda Arief, M.Ilham Asbudi, Hedy Leoni Dewi Yanti Liliana Eriya Eriya Eriya, Eriya Fajar Novriansyah Yasir Hata Maulana Iklima Ermis Ismail M. Ilham Arief Maria Agustin Marta Surya Cakraningrat Mauldy Laya Mera Kartika Delimayanti Mifta Cahya Anggraini Mohammad Rezza Pahlevi Muhammad Salimy Ahsan Oktaviana, Shinta Onki Alexander Pratama, Muh. Ikral Putra, Agustinus Dwiutomo P Putra, Agustinus Dwiutomo P Putra, Fadil Muhammad Putra, Fadil Muhammad Ramadan, Zaka Hadikusuma Salfita Susilawati, Fitrah Eka Syam, Andi Alif Utami, Putri Dinda Utami, Putri Dinda Yan Andriariza Ambhita Sukma Yan Andriariza Ambhita Sukma, Yan Andriariza Yoyok Sabar Waluyo