Article Per Year (5 Year)
p-Index From 2019 - 2024
0.61
P-Index
This Author published in this journals
All Journal Journal of Information System Sistemasi: Jurnal Sistem Informasi
Habibie Ed Dien
Politeknik Negeri Malang
Computer Science & IT Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penentuan Learning Rate Terbaik CNN Pada Pengenalan Individu Berbasis Analisis Gait Septian Enggar Sukmana; Deasy Sandhya Elya Ikawati; Habibie Ed Dien; Ashafidz Fauzan Dianta
JOINS (Journal of Information System) Vol 8, No 1 (2023): Edisi Mei 2023
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v8i1.7806

Abstract

Trayektori tubuh manusia untuk analisis gait tidak terbatas pada kondisi permukaan medan yang rata. Hal ini berpengaruh pada analisis gait untuk penelitian pengenalan identitas individu yang terkait dengan kondisi medan yang dilalui. Pergelangan kaki menjadi bagian tubuh yang berkontribusi pada trayektori tubuh manusia terhadap medan yang dilalui melalui dua kondisi yaitu Heel-Strike (HS) dan Toe-Off (TO). HS dan TO memiliki pola trayektori yang saling berbeda untuk setiap individu sehingga membutuhkan penentuan parameter learning rate yang tepat. Penentuan learning rate terbaik merupakan salah satu langkah penting dalam menghasilkan pengenalan identitas individu terbaik. Pada kegiatan penelitian ini, data yang digunakan adalah data berformat C3D yang direkam melalui perangkat motion capture dengan skenario berjalan lurus (WS/Walking Straight) oleh enam orang sebagai partisipan. Penentuan learning rate terbaik menggunakan metode convolutional neural network (CNN) dengan pretrain pembanding adalah ResNet18 dan ResNet50. Percobaan yang dilakukan menghasilkan performa terbaik diperoleh ResNet18 baik pada pengukuran Average Position (AP) maupun pendeteksian kondisi HS dan TO.
Genetic Grouping Algorithm based on Rank and Research Group for Timetabling Thesis Examination Habibie Ed Dien; M. Hasyim Ratsanjani; Andhika Satrio Wiratama; Vit Zuraida
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v12i2.2394

Abstract

Timetabling is a common problem faced by various academic institutions, especially in the process of timetabling thesis examination. In the process of timetabling thesis examination there are several problems that arise, namely the problem of determining examiners and their order, arranging space and time slots, which makes the timetabling process inefficient. This problem will be solved by using a genetic grouping algorithm (GGA) combined with the parameters of rank and research groups (RG), which have proven to be efficient to use to solve problems such as in the thesis exam timetabling process. The results showed that GGA with ran and RG succeeded in increasing efficiency by 99,97% when applied to solving this problem in the thesis exam timetabling process.
Analysis of LoRa with LoRaWAN Technology Indoors in Polytechnic of Malang Environment Noprianto Noprianto; Habibie Ed Dien; M. Hasyim Ratsanjani; Muhammad Afif Hendrawan
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i2.3884

Abstract

Technology is one of the fields heavily influenced by rapid developments, undergoing significant changes each year. One of the technologies affected is data transmission. Data transmission faces its own challenges, and each region encounters different constraints in their connections, such as the distance of data delivery. In this regard, expanding the data delivery range is crucial to optimize connections and system performance. The use of LoRaWAN for sensor monitoring in IoT devices is designed to transmit data over a wide area with low power consumption and long-term usability, thus overcoming these issues. Data collection in this study utilizes the technique of measuring RSSI (Received Signal Strength Indicator), SNR (Signal-to-Noise Ratio), and LoRa's time interval, considering distance and location parameters at Politeknik Negeri Malang and its surrounding areas. Locations chosen include each floor of the Civil Engineering building to obtain data parameters like RSSI, SNR, and time intervals, which improve when the distance between the transmitting LoRa node and the LoRa gateway gets closer. After conducting tests, it was found that using a 35 dBi antenna outperforms a 10 dBi antenna in data transmission. This was evidenced by the RSSI values approaching 0 from floor 8 to 1 in the Civil Engineering building of Politeknik Negeri Malang. Additionally, the use of a 35 dBi antenna resulted in a 50% faster data transmission compared to the 10 dBi antenna. LoRaWAN technology, particularly The Things Network, can be employed to manage LoRa. However, similar technologies like Chripstack can also be used to manage LoRaWAN more flexibly on the local network
Co-Authors Andhika Satrio Wiratama Ashafidz Fauzan Dianta Deasy Sandhya Elya Ikawati Hendrawan, Muhammad Afif M. Hasyim Ratsanjani M. Hasyim Ratsanjani Noprianto, Noprianto Septian Enggar Sukmana Vit Zuraida