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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Electrical Engineering and Computer (JEECOM) Heca Journal of Applied Sciences Infolitika Journal of Data Science
Misbullah, Alim
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Health Professions Medicine & Pharmacology

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Evaluating Geothermal Power Plant Sites with Additive Ratio Assessment: Case Study of Mount Seulawah Agam, Indonesia Azhar, Fauzul; Misbullah, Alim; Lala, Andi; Idroes, Ghazi Mauer; Kusumo, Fitranto; Noviandy, Teuku Rizky; Irvanizam, Irvanizam; Idroes, Rinaldi
Heca Journal of Applied Sciences Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v2i1.158

Abstract

Indonesia, a country rich in geothermal resources, has yet to fully exploit its potential, particularly in volcanic regions like Mount Seulawah Agam. This study investigates the application of the Additive Ratio Assessment (ARAS) method for the site selection of Geothermal Power Plants (GPP) in Indonesia. The ARAS method provides a systematic approach to evaluating and prioritizing geothermal development sites by integrating multiple criteria, including geological, environmental, and socio-economic factors. The study collects data from various sources and weights criteria using the Ordinal Priority Approach (OPA), incorporating expert opinions. The findings demonstrate the effectiveness of the ARAS method in identifying optimal locations for GPP development, ensuring sustainability and feasibility. The study also tests the ARAS method in existing GPP locations in Jaboi, Sabang, Indonesia, to investigate alignment with the results and validate the approach. Furthermore, the study presents recommendations for GPP site selection. This research emphasizes the significance of multi-criteria decision-making techniques in facilitating renewable energy projects. It promotes a more systematic and informed approach to geothermal energy development in Indonesia and other geothermal-rich regions.
Optimizing Geothermal Power Plant Locations in Indonesia: A Multi-Objective Optimization on The Basis of Ratio Analysis Approach Rahman, Isra Farliadi; Misbullah, Alim; Irvanizam, Irvanizam; Yusuf, Muhammad; Maulana, Aga; Marwan, Marwan; Dharma, Dian Budi; Idroes, Rinaldi
Infolitika Journal of Data Science Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i1.184

Abstract

As the global energy landscape shifts towards sustainable sources, geothermal energy emerges as a pivotal renewable resource, particularly in regions with abundant geothermal potential like Indonesia. This study focuses on Mount Seulawah in Aceh Province, a region rich in geothermal resources, to optimize the selection of geothermal power plant (GPP) sites using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method. Our approach integrates environmental, technical, and accessibility criteria, including distance to settlements, land slope, proximity to fault lines and heat sources, and road access. By employing a structured decision matrix and applying MOORA, we systematically evaluated and ranked potential sites based on their suitability for GPP development. The results highlight the site at Ie Brôuk as the most optimal due to its minimal environmental impact and superior geological and accessibility conditions. This study not only contributes to the strategic deployment of geothermal resources in Indonesia but also provides a replicable model for other regions with similar geothermal potentials, emphasizing the importance of a balanced and informed approach to renewable energy site selection.
Sistem Identifikasi Pembicara Berbahasa Indonesia Menggunakan X-Vector Embedding Misbullah, Alim; Saifullah Sani, Muhammad; Husaini; Farsiah, Laina; Zahnur; Martiwi Sukiakhy, Kikye
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 2: April 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241127866

Abstract

Penyemat pembicara adalah vektor yang terbukti efektif dalam merepresentasikan karakteristik pembicara sehingga menghasilkan akurasi yang tinggi dalam ranah pengenalan pembicara. Penelitian ini berfokus pada penerapan x-vectors sebagai penyemat pembicara pada sistem identifikasi pembicara berbahasa Indonesia yang menggunakan model speaker identification. Model dibangun dengan menggunakan dataset VoxCeleb sebagai data latih dan dataset INF19 sebagai data uji yang dikumpulkan dari suara mahasiswa Jurusan Informatika Universitas Syiah Kuala angkatan 2019. Untuk membangun model, fitur-fitur diekstrak dengan menggunakan Mel-Frequency Cepstral Coeffients (MFCC), dihitung Voice Activity Detection (VAD), dilakukan augmentasi dan normalisasi fitur menggunakan Cepstral Mean and Variance Normalization (CMVN) serta dilakukan filtering. Sedangkan proses pengujian model hanya membutuhkan fitur-fitur yang diekstrak dengan menggunakan MFCC dan dihitung VAD saja. Terdapat 4 (empat) model yang dibangun dengan cara mengombinasikan dua jenis konfigurasi MFCC dan dua jenis arsitektur Deep Neural Network (DNN) yang memanfaatkan Time Delay Neural Network (TDNN). Model terbaik dipilih berdasarkan akurasi tertinggi yang dihitung menggunakan metrik Equal Error Rate (EER) dan durasi ekstraksi x-vectors tersingkat dari keempat model. Nilai EER dari model yang terbaik untuk dataset VoxCeleb1 bagian test sebesar 3,51%, inf19_test_td sebesar 1,3%, dan inf19_test_tid sebesar 1,4%. Durasi ekstraksi x-vectors menggunakan model terbaik untuk data train berdurasi 6 jam 42 menit 39 detik, VoxCeleb1 bagian test berdurasi 2 menit 24 detik, inf19_enroll berdurasi 18 detik, inf19_test_td berdurasi 25 detik, dan inf19_test_tid berdurasi 9 detik. Arsitektur DNN kedua dan konfigurasi MFCC kedua yang telah dirancang menghasilkan model yang lebih kecil, akurasi yang lebih baik terutama untuk dataset pembicara berbahasa Indonesia, dan durasi ekstraksi x-vectors yang lebih singkat.   Abstract The speaker embedding is a vector that has been proven effective in representing speaker characteristics, resulting in high accuracy in the domain of speaker recognition. This research focuses on the application of x-vectors as speaker embeddings in the Indonesian language speaker identification system using a speaker identification model. The model is built using the VoxCeleb dataset as training data and the INF19 dataset as testing data, collected from the voices of students of Informatics Department, Universitas Syiah Kuala from the 2019 batch. To build the model, features are extracted using Mel-Frequency Cepstral Coefficients (MFCC), Voice Activity Detection (VAD) is applied, augmentation and normalization of features are performed using Cepstral Mean and Variance Normalization (CMVN), and filtering is applied. On the other hand, the model testing process only requires features extracted using MFCC and computed VAD. There are 4 (four) models are constructed by combining two configurations of MFCC and two types of Deep Neural Network (DNN) architectures that utilize the Time Delay Neural Network (TDNN). The best model is selected based on the highest accuracy calculated using the Equal Error Rate (EER) metric and the shortest duration of x-vector extraction from the four models. The EER values for the best model on the VoxCeleb1 test dataset are 3.51%, 1.3% for inf19_test_td, and 1.4% for inf19_test_tid. The x-vector extraction duration using the best model for the training dataset is 6 hours 42 minutes 39 seconds, 2 minutes 24 seconds for VoxCeleb1 test part, 18 seconds for inf19_enroll, 25 seconds for inf19_test_td, and 9 seconds for inf19_test_tid. The second DNN architecture and the second MFCC configuration designed result in a smaller model, better accuracy, especially for Indonesian language speaker datasets, and shorter x-vector extraction duration.  
Rancang Bangun Aplikasi Bank Sampah Universitas Syiah Kuala Berbasis Web Deviani, Rini; Aflah, Tsani; Misbullah, Alim
Journal of Electrical Engineering and Computer (JEECOM) Vol 6, No 1 (2024)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v6i1.8245

Abstract

Bank Sampah Universitas Syiah Kuala merupakan solusi dari Universitas Syiah Kuala untuk mengatasi dampak negatif dari peningkatan produksi sampah. Kesadaran masyarakat terhadap pengelolaan sampah yang terus berkembang telah mendorong peningkatan jumlah nasabah Bank Sampah USK. Pertumbuhan nasabah ini memunculkan masalah diantaranya sistem administrasi dan transaksi yang belum terstruktur, serta tidak adanya platform untuk menyebarluaskan informasi dan berita mengenai Bank Sampah USK kepada masyarakat. Adapun cara untuk mengatasi tantangan ini adalah dengan membangun aplikasi Bank Sampah USK berbasis web. Aplikasi ini dikembangkan menggunakan model waterfall sehingga tahapannya dikerjakan secara berurutan,mulai dari tahap identifikasi masalah yang dialami pengguna, tahap pengerjaan kode dengan bahasa pemrograman PHP hingga tahap dilakukannya pengujian untuk memastikan sistem berjalan dengan baik serta memberikan pengalaman pengguna yang optimal. Fitur-fitur aplikasi yang dihasilkan mencakup kemampuan pengunjung web untuk melihat informasi/berita oleh Bank Sampah USK. Administrator dapat mengelola informasi/berita, nasabah, setoran, jenis sampah, dan konfirmasi penarikan dana. Nasabah dapat mengelola profil, melakukan penarikan saldo, serta melihat riwayat setoran dan penarikan. Hasil analisis pengujian fungsionalitas menunjukkan bahwa aplikasi ini berhasil menjalankan semua skenario black box testing dan mendapatkan penilaian usability "Good" oleh 30 responden, dengan grade scale ‘B’ dan acceptability range berada pada kategori ‘Acceptable’.
Co-Authors Aflah, Tsani Azhar, Fauzul Deviani, Rini Dharma, Dian Budi Farsiah, Laina Husaini Husaini Idroes, Ghazi Mauer Irvanizam, Irvanizam Kusumo, Fitranto Lala, Andi Martiwi Sukiakhy, Kikye Marwan Marwan Maulana, Aga Muhammad Yusuf Noviandy, Teuku Rizky Rahman, Isra Farliadi Rinaldi Idroes Saifullah Sani, Muhammad Zahnur