Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal JTM-ITI (Jurnal Teknik Mesin ITI) Coreid Journal
Firdaus, Imam
Unknown Affiliation
Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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

Found 3 Documents
Search

 1 
Prediksi Komposisi Unsur Dan HHV Sampel Bahan Bakar Sampah Incinerator PLTSa UNSIKA Menggunakan Analisa Proksimat Firdaus, Imam
JTM-ITI (Jurnal Teknik Mesin ITI) Vol 5, No 2 (2021): Jurnal Teknik Mesin ITI
Publisher : Institut Teknologi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (629.519 KB) | DOI: 10.31543/jtm.v5i2.611

Abstract

Pemanfaatan energi alternatif pada era modern ini sangat cepat perkembangannya, dimulai dari untuk kebutuhan sehari-hari hingga pemanfaatan di skala industri. Akan tetapi dalam proses perancangannya dibutuhkan data yang sangat banyak agar memperoleh hasil yang akurat. Salah satu di antaranya ialah nilai HHV dan komposisi unsur pada biomassa, yang dalam proses pengujian memerlukan waktu dan biaya yang cukup besar. Belum lama ini banyak penelitian tentang hubungan dari analisa proksimat dengan HHV maupun komposisi unsur tersebut, yang sangat bermanfaat dalam perancangan tungku atau pengoperasian yang menggunakan bahan bakar biomassa. Pada incinerator PLTSa di Universitas Singaperbangsa Karawang dibutuhkan komposisi unsur untuk menganalisis gas buang pembakarannya dan HHV untuk nilai kalor pembakarannya. Untuk sampel yang di ambil ada 3 buah sampel, yang terdiri dari campuran sampah kertas, daun mangga, daun pisang, dan daun ketapang. Untuk unsur-unsurnya terdiri dari unsur C (karbon), H (hidrogen), dan O (oksigen), untuk nilainya masing-masing berkisar antara 32,87-33,43%, 4,22-4,26%, 26,05-26,47%. Untuk nilai HHV-nya berkisar antara 15689,83-15690,53 kJ/kg.
Implementation of Finite State Automata on e-Knows Telegram Chatbot Alam, Cecep Nurul; Firdaus, Imam
CoreID Journal Vol. 1 No. 1 (2023): March 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i1.3

Abstract

The State Islamic University of Sunan Gunung Djati Bandung has a bold learning system called e-Knows. So far, if the user has a school, he must contact the admin manually. The problems are diverse, and several issues can bring personal impact. Automata language theory is the basic logic for mapping the telegram e-Knows chatbot system. The mapping is done by dividing each system using finite state automata to facilitate the completion of the system.
Academic Data Quality Measurement in SALAM Application Using Six Sigma Method Firdaus, Imam; Alam, Cecep Nurul; Gerhana, Yana Aditia; Irfan, Mohamad
CoreID Journal Vol. 3 No. 2 (2025): July 2025
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v3i2.136

Abstract

Data quality plays a critical role in ensuring the reliability and usefulness of information for decision making in higher education institutions. However, academic data within the SALAM application at UIN Sunan Gunung Djati Bandung has not previously undergone a systematic quality assessment, leading to uncertainty in several managerial and academic decisions. This study aims to evaluate the quality of academic data in the SALAM application using the Six Sigma method with the DMAIC (Define–Measure–Analyze–Improve–Control) framework. Five data quality dimensions completeness, consistency, conformity, uniqueness, and timeliness are employed to measure and analyze data quality performance. The measurement process begins with data definition and extraction, followed by quantitative analysis using sigma metrics. The results indicate that the overall quality of academic data is at a moderate level, with an average sigma score of approximately 3, primarily influenced by incomplete and inconsistent data. In contrast, the timeliness dimension demonstrates excellent performance, achieving a sigma metric of 6 due to the long-term availability of data over more than ten years. This study contributes by providing an empirical, data-driven evaluation of academic data quality and offers practical insights for implementing continuous monitoring and improvement strategies to enhance data reliability and support more effective decision making in higher education institutions.
Co-Authors Cecep Nurul Alam, Cecep Nurul Lumbessy, Salnida Yuniarti Mohamad Irfan, Mohamad Sitti Hilyana Yana Aditia Gerhana, Yana Aditia