Article Per Year (5 Year)
p-Index From 2020 - 2025
0.983
P-Index
This Author published in this journals
All Journal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Mohammad Irfan Fahmi
Universitas Prima Indonesia
Computer Science & IT

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Desain Prototype Smart Building Menggunakan Internet of Things dengan Protokol MQTT Evta Indra; Mohammad Irfan Fahmi; Daniel Ryan Hamonangan Sitompul; Stiven Hamonangan Sinurat; Andreas Situmorang; Ruben Ruben; Dennis Jusuf Ziegel
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 5 No. 1 (2022): Jutikomp Volume 5 Nomor 1 April 2022
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v5i1.2595

Abstract

Energy saving is the most wanted thing to prevent overspending in carrying out daily activities in the building. One form of energy savings is implementing Smart Building technology to control Air conditioners (AC) dan lamps according to its need. Methods used in this research were started with the Architectural Design of the devices, Managing of the devices, and their Decommission. The result carried in this research is that the prototype made was running well on low-scale implementation. Buttons in the website functioned well, even though there are still many problems when implementing the project on a huge scale because this research still uses a freeware-based MQTT broker.
PENERAPAN METODE FORCASTING DALAM MENENTUKAN JUMLAH SISWA BARU MENGGUNAKAN ALGORITMA SIMPLE LINEAR REGRESSION Tajrin Tajrin; Mohammad Irfan Fahmi; Maikel Felix Ginting; Unika Nduru
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.880

Abstract

New student admission is a school activity to recruit new prospective students that occurs regularly every year even in the middle of the teaching year. Madrasah Tsanawiyah (MTs) Al-Ittihadiyah is a school under the auspices of the Ministry of Religion. Where every year the school always accepts a fairly large number of new students around 300 people. This results in the school always having difficulties in preparing infrastructure facilities such as classrooms and teachers because the increase in the number of new students increases every year. This will happen repeatedly in schools from year to year. So that it will be an accumulation of data every year to help transform data into data information into useful information. This large amount of data opens up opportunities to generate useful information for schools. In this study, researchers see an opportunity to create a new technology that answers the needs and problems that have occurred so far. In determining the number of new students at MTs. Al-Ittihadiyah Pkl. Masyhur researchers used 2 dataset scenarios where scenario 2 datasets used a simple linear regression algorithm. In pre-processing data that produces prediction performance, namely Y = 71.9538 + 0.709269X, in the dataset for forecasting estimates for the number of new students if the registrant is 374 students, it will produce a prediction of new students of 337 students.
ANALISIS SENTIMEN ULASAN APLIKASI MEDIA SOSIAL WHATSAPP MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER Nova Rosalina Siahaan; Rosita Yolanda Tiffany; Shandy Roland Evansius Sinaga; Elsa Vio Nauli Br Naibaho; Mohammad Irfan Fahmi
JURNAL ILMIAH BETRIK Vol. 14 No. 02 AGUSTUS (2023): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : P3M Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/betrik.v14i02 AGUSTUS.104

Abstract

Analisis sentimen adalah proses menggunakan teknik dan metode komputasional untuk memahami dan mengevaluasi opini, sikap, atau emosi yang terkandung dalam teks atau data lainnya. Masalah utama dalam aplikasi media sosial whatsapp ini pada saat mengupload foto atau video story resolusi tidak jernih dan pecah . Masalah lain muncul pesan error atau terhenti, biasanya bertuliskan WhatsApp telah berhenti, atau mungkin pesan error lainnya. Hal semacam ini tentu mengganggu para pengguna karena pasti akan terbatas dalam aktivitas yang dilakukan . Untuk memberikan pengalaman yang baik bagi pengguna whatsapp, penting bagi pengembang aplikasi untuk memahami perasaan dan harapan pengguna. Penelitian ini bertujuan untuk menganalisis sentimen ulasan aplikasi WhatsApp menggunakan metode Naive Bayes Classifier. Hasil penelitian menunjukkan bahwa metode Naive Bayes Classifier efektif dalam menganalisis sentimen ulasan aplikasi media sosial WhatsApp. Pada Pelabelan, untuk mengklasisfikasi ulasan – ulasan dari suatu produk ke dalam kategori Positif, Negatif, dan Netral. Pada penelitian ini, tim peneliti telah melakukan pelabelan kedalam dataset. Pelabelan pada dataset ini dapat berupa : Rating <3 (lebih kecil dari angka-3) adalah sentimen Negatif, ==3 (sama dengan dari angka-3) adalah sentimen Netral, dan >3 (lebih besar dari angka -3) adalah Positif. Dan disertai penambahan kolom yaitu ‘Label’ yang berisi Sentimen Positif, Negatif, dan Netral.
ANALISIS PENILAIAN KINERJA DOSEN MENGGUNAKAN METODE ADAPTIVE NEURON-FUZZY INFERENCE SYSTEM (ANFIS) Rut Ronauli Hutagaol; Aida Elda Afriza; Mohammad Irfan Fahmi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1331

Abstract

This research examines the performance of lecturers at Universitas Prima Indonesia using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method to evaluate and enhance teaching quality. The research employs a quantitative approach, collecting data through observations, literature reviews, and questionnaires distributed to 100 students from the Faculty of Science and Technology. Four input variables used are pedagogical competence, professional competence, personal competence, and social competence. The collected data is analyzed using Matlab with ANFIS, which combines the capabilities of artificial neural networks and fuzzy logic to produce accurate predictions. The analysis results show that the ANFIS method is effective in measuring lecturer performance, with high validation results and low error rates. The ANFIS simulation indicates that the majority of lecturers fall into the "Quite Satisfied" category based on student assessments. This study is expected to make a significant contribution to improving the teaching quality of lecturers at Universitas Prima Indonesia through more accurate and technology-based performance evaluations.
PENERAPAN METODE ANT COLONY OPTIMIZATION (ACO) DALAM MENENTUKAN JALUR ALTERNATIF SOLUSI KEMACETAN KOTA MEDAN William William; Rizky Syahputra Sitompul; Adilman Reliance Hia; Roy F. Hasudungan Malau; Saut Parsaoran Tamba; Mohammad Irfan Fahmi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1221

Abstract

This research aims to analyze and implement the Ant Colony Optimization (ACO) method in determining alternative routes to reduce traffic congestion in Medan City. Against the background of significant congestion problems during rush hours, this research collects traffic data through surveys and observations to serve as input for the ACO algorithm. This method is inspired by the natural behavior of ants in searching for food, where ants collectively find the shortest route based on pheromone trails. Tests were carried out with variations in ACO parameters such as pheromone evaporation rate, number of ants, and iterations to analyze the effectiveness of alternative paths. The research results show that the application of this method can help reduce the burden on the road network and is proven to be able to reduce travel time by 37.5%, where the time needed from 40 minutes can be reduced to 25 minutes. The results of this research can contribute to the development of an intelligent transportation system that is adaptive to changes in traffic conditions and the needs of road users in the city of Medan.
Co-Authors Adilman Reliance Hia Aida Elda Afriza Andreas Situmorang Daniel Ryan Hamonangan Sitompul Dennis Jusuf Ziegel Elsa Vio Nauli Br Naibaho Evta Indra Maikel Felix Ginting Nova Rosalina Siahaan Rizky Syahputra Sitompul Rosita Yolanda Tiffany Roy F. Hasudungan Malau Ruben Ruben Rut Ronauli Hutagaol Saut Parsaoran Tamba Shandy Roland Evansius Sinaga Stiven Hamonangan Sinurat Tajrin Tajrin Unika Nduru William William