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Prototype Sistem Buka Tutup Pintu Air Otomatis Menggunakan Prakiraan Cuaca Rizaldi, Fazrin Muhammad; Sujjada, Alun
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.529

Abstract

Improvements in managing agriculture are urgently needed at this time. Along with the many occurrences of crop failure due to the rainy season which causes flooding in the rice fields. The lack of supervision of the irrigation system makes the water discharge when the rainfall is high, causing the rice plants to be damaged by the flow of water. With this, it is necessary to regulate the immigration channel to prevent crop failure and flooding. Along with this problem, a prototype of an Arduino-based automatic sluice system was made. This prototype has 2 functions, the first is to regulate when the floodgates in the reservoir operate with reference to the water level using an ultrasonic sensor. The sensor signals the Arduino to be processed. The output signal from the Arduino instructs the relay to activate and makes the solenoid work to open or close the water line. The second function is to manage the reservoir which has a water gate leading to the rice field area. This floodgate works with a time setting that can be set as desired. The prototype of the floodgate in irrigation is driven by a 12V DC motor and locks the floodgate when it is opened using a servo motor. With the work of these 2 functions, it can make it easier to regulate the water level in the reservoir and the management of irrigation channels in rice fields.
Perbandingan Rest Api Menggunakan Node Js Dan Php Pada Aplikasi Pemilihan Umum Haryadi, Habbyan Lazuard; Sujjada, Alun; Simatupang, Dwi Sartika
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.631

Abstract

This study aims to analyze the comparison of the Representational State Transfer (REST) Application Programming Interface (API) between PHP and Node.js in the context of general election applications. The Prototype System Development Life Cycle (SDLC) method is used for application development. The performance of both programming languages is evaluated based on response speed, ease of development, and system capabilities. Data on Permanent Residents of Malang City with a total of 600 thousand data is used as a sample for database and server testing. The comparison results show that Node.js has a better response speed than PHP. However, PHP has an advantage in terms of ease of development. Both are able to handle applications with a large number of voters based on system capabilities. This research provides insight into the performance of PHP and Node.js in the context of REST API development for election applications
Analisis Clustering Data Penyandang Disabilitas Menggunakan Metode Agglomerative Hierarchical Clustering dan K-means Sujjada, Alun; Insany, Gina Purnama; Noer, Silvia
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.10654

Abstract

Disability issues are still a major concern in society due to the discrimination often faced by people with disabilities. Many of them have abilities that are equal to individuals without physical limitations. Through this case study, this research aims to Cluster disability data by considering three types of disabilities: physical, visual and hearing, and hearing and speech using agglomerative hierachical Clustering and kmeans methods. This research was conducted by analyzing data from people with disabilities in 7 provinces in Indonesia. K-means to group data and agglomerative hierarchical Clustering as a centroid determinant in k-means. to enrich the results of data analysis, the EDA (Exploratory Data Analysis) process is used to identify outliers and anomalies. The results of the data analysis show that there are three main Clusters. The first Cluster has a high level of disability and includes 62 cities and districts, the second Cluster has a medium level of disability with 37 cities and districts, and the third Cluster has a low level of disability with 27 cities and districts. The best evaluation using the Davies Bouldin Index method resulted in two Clusters, indicating a better quality of Cluster division. The results of this study provide a better understanding of the distribution of disability in Indonesia, which can be used as a foundation to improve inclusion and accessibility for people with disabilities. Further recommendations can be made based on these findings to improve their situation in terms of employment and education.
KIPAS ANGIN OTOMATIS BERBASIS ARDUINO: KIPAS ANGIN OTOMATIS BERBASIS ARDUINO Muhamad Dani Meinanda; Alun Sujjada
Prosiding Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer Vol 1 (2022): Sentimeter 2022
Publisher : Prosiding Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer

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

Abstract

Suhu pada tubuh manusia dapat dengan mudah berubah sesuai dengan suhu disekitarnya. Negara Indonesia yang beriklim tropis serta pemanasan global juga menjadi faktor lain yang membuat cuaca menjadi tidak tertentu. Untuk mengatasi permasalahan ini diperlukan sebiah alat untuk membatu menstabilkan suhu pada tubuh manusia. Salah satu alat pembantu tersebut adalah kipas angin, namun kipas angin yang banyak di pakai saat ini rata-rata masih manual dimana untuk menghidupkan dan mematikannya masih secara manual yang dimana kita harus mendekati kipas anginnya terlebih dahulu untuk bisa mengendalikannya. Berdasarkan permasalahan ini maka dibuatlah sebuah alat yang dapat mengandalikan kipas angina secara otomatis. Kipas angin di buat secara otomatis dengan memanfaatkan sensor suhu (DHT11) dan dikendalikan menggunakan Arduino Uno. Sensor suhu DHT11 berfungsi untuk mendeteksi suhu di dalam ruangan , sedangkan arduino uno berfungsi sebagai alat untuk mengendalikannya. Tujuan dibuatnya kipas angin otomatis ini, yaitu untuk membantu manusia dalam menghidupkan dan mamatikan kipas. Hasil pengujian yang di peroleh adalah jika sensor suhu mendeteksi suhu ruangan melebihi 30C maka kipas angin akan otomatis hidup dan jika sensor suhu mendeteksi suhu ruangan kurang dari 29°C maka kipas angin otomatis akan mati dengan sendirinya.
SISTEM PENGATUR SUHU KELEMBABAN RUANGAN PADA BUDIDAYA JAMUR TIRAM BERBASIS ARDUINO Mansur Ponimat; Sujjada, Alun
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1548

Abstract

One of the businesses that is often in demand by farmers is cultivating oyster mushrooms because oyster mushrooms are very tasty and have many health benefits, but cultivating oyster mushrooms requires quite complicated care, if the temperature and humidity of the environment where the mushrooms grow are abnormal, it will inhibit the growth of the fungus. With this research the author aims to create a system that can regulate and monitor temperature in real time so that fungal growth will be more fertile and increase production. The development method used to make this research is the waterfall method, this method is very easy to use and is able to solve problems quickly. The main purpose of this research is to create a system that can assist oyster mushroom farmers in regulating and monitoring temperature conditions by using a fan and a water pump as a medium for cooling the temperature which is regulated by an Arduino microcontroller.
SISTEM PENGATUR SUHU KELEMBABAN RUANGAN PADA BUDIDAYA JAMUR TIRAM BERBASIS ARDUINO Mansur Ponimat; Sujjada, Alun
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.711 KB) | DOI: 10.54367/jtiust.v6i2.1548

Abstract

One of the businesses that is often in demand by farmers is cultivating oyster mushrooms because oyster mushrooms are very tasty and have many health benefits, but cultivating oyster mushrooms requires quite complicated care, if the temperature and humidity of the environment where the mushrooms grow are abnormal, it will inhibit the growth of the fungus. With this research the author aims to create a system that can regulate and monitor temperature in real time so that fungal growth will be more fertile and increase production. The development method used to make this research is the waterfall method, this method is very easy to use and is able to solve problems quickly. The main purpose of this research is to create a system that can assist oyster mushroom farmers in regulating and monitoring temperature conditions by using a fan and a water pump as a medium for cooling the temperature which is regulated by an Arduino microcontroller.
Application of YOLOv8 Model for Early Detection of Diseases in Bean Leaves Yustiana, Indra; Sujjada, Alun; Tirawati
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2514

Abstract

Bean plant is one of the high economic value horticultural commodities widely cultivated in Indonesia. However, its productivity declines due to pest attacks and leaf diseases. Farmers' limitations in accurately identifying disease types also pose obstacles in early mitigation efforts. Therefore, technology-based solutions capable of quickly and accurately detecting plant diseases are needed. This research aims to develop and evaluate the performance of a leaf disease detection model for bean plants using the You Only Look Once version 8 (YOLOv8) algorithm with a transfer learning approach. The dataset used consists of 1,037 images of bean leaves, classified into three categories: angular leaf spots, leaf rust, and healthy leaves. Data were obtained from two sources, namely field documentation in Sindang Village, Sukabumi Regency, and an open repository on GitHub. The dataset was divided into training data (70%), validation (20%), and testing (10%). The model was trained using the YOLOv8s architecture for 30 epochs and achieved a detection accuracy of 85%. Performance evaluation was conducted using precision, recall, and mean average precision (mAP) metrics. The results of this study are expected to be an initial contribution to the application of artificial intelligence in agriculture, particularly in helping farmers efficiently detect leaf diseases in beans to improve productivity and quality of harvest.
Implementation of Content-Based Filtering in a Novel Recommendation System to Enhance User Experience Sanjaya, Imam; Sujjada, Alun; Pratama, Yudistira
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2833

Abstract

This study addresses a critical challenge in digital novel platforms: the difficulty of delivering personalized and accurate recommendations due to limited user interaction data. This limitation often leads to irrelevant or generic suggestions, which can diminish user engagement and hinder content discovery. The significance of solving this issue lies in enhancing user experience by ensuring that readers are presented with novels that truly align with their interests, even in the absence of extensive behavioral data. To overcome this problem, the study proposes an innovative hybrid recommendation system that integrates Content-Based Filtering (CBF) with the Random Forest algorithm. The system generates personalized recommendations by analyzing novel attributes such as title, genre, score, and popularity. The methodology involves extracting features from textual data using Term Frequency-Inverse Document Frequency (TF-IDF), followed by the calculation of cosine similarity to assess title relevance. These similarity scores are then combined with popularity predictions derived from the Random Forest model to produce final recommendations that reflect both content similarity and statistical relevance. The proposed system demonstrates strong performance, achieving an accuracy of 94.0%, precision of 81.4%, recall of 80.3%, and an F1-score of 80.8%. These results underscore the system’s capability to deliver accurate and diverse suggestions. By enhancing personalization and addressing the limitations of conventional CBF systems, this hybrid approach offers practical value for digital novel platforms. It serves as an effective tool for improving content discovery, increasing reader satisfaction, and supporting user retention in content-rich environments.
Sistem Prediksi Konsumsi Energi Listrik Subsidi dan Non Subsidi Berbasis Web dengan Metode RNN (Kasus Kota Sukabumi) Insany, Gina Purnama; Sujjada, Alun; Lidena, Salwa Dwi; Fadilah, Muhammad Sahrul; Wilianti, Refi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.917

Abstract

Sukabumi City experiences an annual increase in electricity consumption, especially in subsidized and non-subsidized categories. However, the energy distribution planning process remains manual and reactive. This research developed a web-based electricity consumption prediction system using the Recurrent Neural Network (RNN) method integrated with the Laravel framework. The development process applied the Rapid Application Development (RAD) method and system modeling using UML. The RNN model achieved a prediction accuracy of 92.4% with an MAE of 12.38 kWh and RMSE of 16.12 kWh. The application provides interactive prediction visualizations to support more efficient energy planning.