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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Migasian Akamigas Balongan Indramayu TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Ade Irawan
Department Of Computer Science, Universitas Pertamina, Jakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Mechanical Engineering Public Health

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Identifikasi Batuan Berdasarkan Data Well Log Menggunakan K-Means Clustering Meredita Susanty; Prinsislamsheeny Brilliantdianty Ebelaristra; Ahmad Fauzan Rahman; Ade Irawan; Ikri Madrinovella; Weny Astuti
Jurnal Migasian Vol 4 No 1 (2020): Jurnal Migasian
Publisher : LPPM Akademi Minyak dan Gas Balongan Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36601/jurnal-migasian.v4i1.96

Abstract

One of the stages in oil and gas exploration is a Petrophysical analysis, which aims to determine the structure of rock layers below the earth's surface. The petrophysical analysis uses physical properties in a well-log to determine the rock type below the surface. Nowadays, the software for conducting petrophysical analysis has utilized a machine-learning approach to predict rock types. Most of the software uses the supervised learning method to classify rock types. This research uses a different approach, unsupervised learning, to group rock types based on various features in a well-log. Using a publicly available well-log in Stafford, United States, and the k-means clustering algorithm, this study groups the data into 3 clusters. The result is compared with manual analysis interpretation and shows an alignment between them. From the result, it shows that the unsupervised learning method effectively predicts limestone, shale, and evaporites in the well. It classifies the dataset into useful clusters, generates useful lithologies, provides useful rock characterization, and less time-consuming.
Robust Principal Component Analysis for Feature Extraction of Fire Detection System Herminarto Nugroho; Muhamad Koyimatu; Ade Irawan; Ariana Yunita
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v5.1716

Abstract

Fire detection system with deep learning-based computer vision (DLCV *) algorithm is proposed in this paper. It uses visible light sensor charged-coupled device (CCD) which can be usually found in closed circuit television camera (CCTV). The performance of this DLCV fire detection depends on how many fire image datasets are trained that might lead to the curse of dimensionality. To tackle the curse of dimensionality, Principal Component Analysis (PCA) will be used. PCA is a technique for feature extraction in which the dimensionality of such datasets is reduced significantly. This will results in increasing interpretability but at the same time minimizing information loss.
Peningkatan Literasi Komputer Melalui Pelatihan Micosoft Excel Advanced Untuk Efisiensi Pekerjaan di Instansi Pemerintahan Meredita Susanty; Erwin Setiawan; Wahyu Kunto Wibowo; Herminarto Nugroho; Ade Irawan; Tasmi Tasmi; Muhamad Koyimatu; Aulia Rahma Annisa; Teguh Aryo Nugroho; Ariana Yunita
Terang Vol 4 No 2 (2022): TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/terang.v4i2.1528

Abstract

Era digital melahirkan berbagai potensi dan tantangan yang memasuki berbagai bidang seperti politik, ekonomi, sosial budaya, pertahanan dan keamanan serta teknologi informasi. Pemerintahan atau sistem birokrasi di Indonesia juga tidak luput dari potensi dan tantangan perkembangan era digital ini. Salah satu tantangan besar yang harus dihadapi oleh sistem birokrasi Indonesia adalah tuntutan lahirnya inovasi yang berorientasi pada teknologi digital, sehingga inovasi ini diharapkan dapat memudahkan Aparatur Sipil Negara (ASN) dalam melaksanakan tugas dan fungsinya. Kemudahan segala pekerjaan dengan berbasis aplikasi dan teknologi ini selanjutnya diharapkan mampu memberikan pelayanan yang lebih optimal kepada masyarakat. Menanggapi tantangan ini, civitas Universitas Pertamina melalui program Pengabdian Kepada Masyarakat (PKM) berbagi pengetahuan, ilmu dan keahlian dalam penggunakan Microsoft Excel untuk mendukung efektivitas pengerjaan pekerjaan harian pada ASN Kantor Pelayanan Kekayaan Negara dan Lelang (KPKNL) Bekasi. Kegiatan ini diharapkan meningkatkan kemampuan Sumber Daya Manusia di kalangan KPKNL Bekasi, meningkatkan efektifitas dan efisiensi pelaksanaan tugas dan fungsi sehari-hari, serta menjadi katalis dalam munculnya inovasi yang berorientasi pada teknologi digital.
The Tweetology of New and Renewable Energy in Indonesia Ariana Yunita; Sara Florensia Telaumbanua; Ade Irawan
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 17, No 2 (2023): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.81397

Abstract

The amount of unstructured data is increasing annually, which is promising forgaining insights. Twitter, a platform producing unstructured data, is currently one of the mostpopular media platforms used for conducting research on a topic's trend. This study attempts toanalyze the topic of New and Renewable Energy (NRE) in Indonesia. The purpose of this studyis to gain insights into the NRE topic trend over the last ten years by modeling the topicsdiscussed on Twitter and examining the location distribution of users who post tweets about thetopic. Accordingly, this study employed descriptive analysis, geocoding analysis, and topicmodeling. The results of descriptive analysis show that the development of NRE has acceleratedin recent years, particularly in 2021. Geocoding analysis reveals that the distribution of peoplewho engage in NRE posting activities is dominated by DKI Jakarta province. Topic modelingyielding two topics that were discussed the most by Indonesians over a 10-year period. The twotopics are related to government policies that support the development of NRE and electricity,which is Indonesia's focus in NRE. This study highlights the importance of analyzing theTweetology of NRE.
Co-Authors Ahmad Fauzan Rahman Ariana Yunita Aulia Rahma Annisa Erwin Setiawan Herminarto Nugroho Ikri Madrinovella Koyimatu, Muhamad Meredita Susanty Muhamad Koyimatu Nugroho, Herminarto Prinsislamsheeny Brilliantdianty Ebelaristra Sara Florensia Telaumbanua Tasmi Tasmi Teguh Aryo Nugroho Wahyu Kunto Wibowo Weny Astuti