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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Technomedia Journal JISICOM (Journal of Information System, Infomatics and Computing) Siber International Journal of Digital Business
Noeman, Achmad
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Fire Detection System Using Android-Based Microcontroller Jani, Akbar Rafni Rafsan; Handayani, Dwipa; Noeman, Achmad
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 9 No 2 (2021): September 2021
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v9i2.3074

Abstract

The Fire Detection System can be supported by Internet of Things technology, e.g. a Microcontroller device which is used to control the related devices. In this study, android-Based fire detection system was designed in which the house owner can always monitor the condition of the house all the times and accessing the information about their house when a fire occurs until the fire suppression process is complete. Information of the house condition will be displayed on the Blynk application which is located in the kitchen area and is connected to several supporting sensors. The design of a Fire Detection System Using an Android-Based Microcontroller is divided into several stages, namely: (1) Requirement Identification; (2) Requirement Analysis;(3) Hardware Design; (4) The software design (Arduino IDE 1.8.5 and Blynk). The testing results showed that the android-based Fire Detection System Using Microcontroller was able to provide information to residents of the house in the real-time.
Employee Work Schedule Presence System Application Design at PT. Tasya Putry Mandiri Uses Genetic Algorithm Method Noeman, Achmad; Rahman Fauzi, Denny; Hartanti, Dian; Hiswara, Abrar; Kustanto, Prio; Hafizah, Hafizah; Mayadi, Mayadi; Lubis, Hendarman
Siber International Journal of Digital Business (SIJDB) Vol. 2 No. 1 (2024): (SIJDB) Siber International Journal of Digital Business (July - September 2024)
Publisher : Siber Nusantara Review & Yayasan Sinergi Inovasi Bersama (SIBER)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/sijdb.v2i1.79

Abstract

Employee scheduling planning is a problem faced by many companies that have many employees. The traditional scheduling process is carried out by recording employee data one by one and collecting them in the form of an Excel report which is inefficient and takes a lot of time. Apart from that, to match the schedules, management needs to take great pains to arrange shift times so that they match and do not conflict between one shift schedule and another shift schedule. This method is very inefficient because it takes a long time if it turns out there is an error in the schedule. A popular method for making schedules is to use a genetic algorithm which is able to arrange schedules using a random approach to find schedule solutions that are most effective and do not collide with each other. Research was conducted to create a schedule from a list of existing employees. As a result, the schedule produced using a genetic algorithm was proven to be more optimal and faster.
Analisa Perancangan Sistem Informasi Dengan Fitur Rekomendasi Menggunakan Algoritma Apriori Fathurrozi, Ahmad; Hariyanto; Prio Pamungkas, R Wisnu; Kustanto, Prio; Noeman, Achmad; Handayani, Dwipa
Technomedia Journal Vol 8 No 2 Oktober (2023): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i2.2003

Abstract

This Ilham Green Shop has just started an online business by selling types of plants which are a growing business area now, but this Ilham Green Shop only has a few buyers, this is because the Ilham Green Shop has not been seen or heard among the public, so it is necessary a sales information system with a recommendation feature built using the PHP and MySQL programming languages and tested by the blackbox - testing method. Data collection techniques used are observation, interviews, and literature study. For processing sales transaction data using the Apriori Algorithm to get more accuracy in the process of processing data on the plant sales information system to find data on the best-selling plant products and see the buying pattern of a buyer by calculating the minimum support value and minimum confidence value to determine the association rules for a combination of itemset. . The results of the Apriori Algorithm calculation in this sales information system with sales transaction data from 03 December 2021 – 30 May 2022 obtained from Ilham Green Shop obtained the lift test value of 1.55 using the minimum support value = 10%, the minimum confidence value = 40% who form association rules with a confidence value of 93.55%. From these results it can be concluded, by processing plant product data with the Apriori Algorithm, it is able to provide good plant recommendations, so Ilham Green Shop can determine a strategy by multiplying the best-selling plant nurseries to get a lot of profit and recommending them to attract buyers' interest.
Aplikasi Sistem Pakar Diagnosa Penyakit Pada Kucing Menggunakan Algoritma Certainty Factor Berbasis Web Handayani, Dwipa; Mahbub, Asep Ramdhani; Noeman, Achmad; Febian, Guruh Putra; Lubis, Hendarman
Journal of Information System, Informatics and Computing Vol 9 No 2 (2025): JISICOM (December 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v9i2.2071

Abstract

This web-based expert system for diagnosing cat diseases is designed to provide fast and accurate diagnoses. Cat owners can input observed symptoms, which are then analyzed using the Certainty Factor algorithm to calculate the likelihood of possible diseases. Based on test data, the system achieves up to 90% accuracy for common diseases such as Feline Panleukopenia Virus and Feline Calicivirus. The algorithm handles uncertainty by generating values between 0 and 1, indicating the confidence level of each diagnosis. Built with PHP and MySQL, the system is accessible in real-time through a responsive web interface. This enhances the efficiency of disease diagnosis and reduces the reliance on veterinarians for initial assessments. Moreover, the system contributes to the advancement of expert system technology in animal health by integrating the proven effectiveness of the Certainty Factor algorithm.
Co-Authors Abrar Hiswara Dian Hartanti Dwipa Handayani Fathurrozi, Ahmad Febian, Guruh Putra Hariyanto Jani, Akbar Rafni Rafsan Kustanto , Prio Lubis, Hendarman Mahbub, Asep Ramdhani Mayadi, Mayadi Prio Pamungkas, R Wisnu Rahman Fauzi, Denny Solly Aryza