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All Journal Teknik dan Ilmu Komputer TESLA: Jurnal Teknik Elektro Jurnal Migasian Akamigas Balongan Indramayu Jurnal Migasian
Lukas Lukas
Jurusan Teknik Elektro, Univeristas Katolik Indonesia Atma Jaya
Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Public Health

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SISTEM PENGUKUR PERUBAHAN TEKANAN DARAH MENGGUNAKAN OKSIMETER FOTO SEBAGAI KOMPONEN UNTUK MENDETEKSI STRES PADA MANUSIA ., Lukas; Joenarto, Prawibowo
Teknik dan Ilmu Komputer vol. 2 no. 5 Januari-Maret 2013
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

AbstrakStres mempunyai berbagai efek pada tubuh manusia. Sistem pendeteksi stres adalah alat yang dapat mengenali gejala-gejala stres umum, dan dapat membantu pengguna menghindari stres di tingkat yang lebih lanjut. Salah satu indikator stres adalah perubahan tekanan darah. Tulisan ini bertujuan untuk mengukur tekanan darah sebagai salah satu komponen alat pendeteksi stress dan untuk mendeteksi stres menggunakan logika fuzzy dengan masukan seperti tekanan darah, detak jantung, suhu tubuh, dan resistansi kulit. Dengan metode Pulse Wave Transit Time dan waktu diastolik, tekanan darah diukur dengan alat oksimeter foto yang dipasangkan pada jari dan elektrokardiogram yang dipasangkan ke tubuh. Dari hasil pengujian, peningkatan tekanan darah walaupun bervariasi bagi setiap individu adalah salah satu indikator stres. Dari hasil tersebut, dengan sifat stres yang personal, sistem ini dapat menunjukkan tingkat stres seseorang bila dibandingkan dengan data umum. Kata Kunci: PPG, tekanan darah, pulse wave transit time, waktu diastolik, pendeteksi stres  AbstractStress has various effects on human’s body. People are frequently unaware that they are suffering from stress. Stress detection system can be useful to identify common stress symptoms and to avoid the stress level increase.  One indicator of stress is changes in blood pressure. This project aims at examining blood pressure to detect stress level and at detecting stress by using fuzzy logic with bio-signal inputs. Based on Pulse Wave Transit Time and Diastolic Time, blood pressure can be measured using photoplethysmograph attached to the finger and electrocardiogram attached to the body.  The study shows that the blood pressure increase is an indicator of stress although the increase varies for each individual. The system allows stress detection based on the general data.     Keywords: PPG, blood pressure, pulse wave transit time, diastolic time, stress detection
Pergerakan Jalan Stabil Robot Hexapod di Atas Medan yang Tidak Rata Rudy Rudy; Lukas Lukas
TESLA: Jurnal Teknik Elektro Vol 19, No 2 (2017): TESLA: Jurnal Teknik Elektro
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1113.576 KB) | DOI: 10.24912/tesla.v19i2.2711

Abstract

 Over the years, natural disasters such as volcano eruption, landslide, as well as flood have occurred and caused victims. Immediate response is required to rescue them, however, detecting and rescuing victims accurately in natural disasters is not easy to be done. The dangerous area with a slippery and sloppy land, as well as the worry that there could be an aftershock disaster, makes it hard to be reached by the rescue team, to get into the area and detect victims. It takes so much time for them to detect and drive the ambulance to the desired location and bring the victims into the car. To solve those problems mentioned by using a robotic technology. The robotic technology can be used to rescue victims during natural disasters with design the prototype of a hexapod that implements inverse kinematics and gait algorithm. Hence, the robot can walk passing the uneven surface and keep being balanced. The hexapod robot is chosen because it has a good stability level when running. The hexapod robot is successfully tested in six different field conditions and is fully capable of maintaining stability in every test such as standing still on a moving surface, running on sloping surfaces, grass and sandy surfaces with a percent error of less than 10%. Beberapa tahun terakhir, bencana alam seperti gunung meletus, tanah longsor, dan banjir sering terjadi dan menimbulkan korban jiwa. Upaya penyelamatan korban jiwa dalam bencana tersebut menjadi sulit dilakukan, karena daerah bencana sangat sulit dicapai oleh tim penyelamat. Permukaan tanah daerah bencana yang tidak rata dan potensi bencana susulan menjadi salah satu kendala dalam penyelamatan korban oleh tim penyelamat. Proses penyelamatan korban biasa dilakukan oleh tim penyelamat dengan membawa mobil ambulans ke lokasi bencana dan tim penyelamat menyusuri daerah bencana untuk menemukan korban. Masalah yang akan muncul adalah tim penyelamat saat mencari korban membahayakan diri saat berada di daerah bencana yang masih berpotensi mengalami bencana susulan, mobil ambulans untuk mengangkut korban tidak bisa menuju lokasi korban karena permukaan tanah daerah bencana yang tidak rata. bila korban berada jauh dari lokasi mobil ambulans, tim penyelamat akan membutuhkan waktu untuk membawa korban menuju mobil ambulans. Sehubungan dengan ini diusulkan suatu rancangan pemecahan masalah dengan menggunakan teknologi robot. Robot digunakan untuk melewati daerah yang memiliki permukaan yang tidak rata berupa sebuah prototype robot hexapod yang menerapkan inverse kinematic dan algoritma gait, sehingga robot dapat melewati daerah yang memiliki permukaan tidak rata serta menjaga kestabilan badan robot saat berjalan. Robot hexapod dipilih karena memiliki tingkat kestabilan yang baik saat berjalan. Robot hexapod berhasil diuji dalam enam kondisi bidang berbeda dan sepenuhnya mampu menjaga kestabilan di setiap pengujian seperti ketika berdiri diam di permukaan yang bergerak, berjalan di permukaan miring, pemukaan rumput maupun berpasir dengan dengan persen kesalahan kurang dari 10%
Perancangan Fidget Device Berbasis Internet Of Things Nova Eka Budiyanta; Mega Cynthia Wishnu; Doli Ramli W; Lukas Lukas
TESLA: Jurnal Teknik Elektro Vol 21, No 1 (2019): TESLA: Jurnal Teknik Elektro
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (281.906 KB) | DOI: 10.24912/tesla.v21i1.3241

Abstract

Increasing stress level among the people is rising a concern. Fidget devices are proposed as a way to help relieve stress. They are easy to use and can be carried everywhere. Two of most commonly used fidget devices are fidget spinner and fidget cube. These fidget devices are believed to cope with anxiety so that users can focus their nervous energy on fidget devices. In this research, the fidget device to be discussed is the fidget cube, since it is considered as safer and has various button than the fidget spinner. Not only stress relievers, IoT-based fidget cube also has the ability to send data to a web server. It aims to see a trend or data about the user's behavior, which buttons are often used by users and the frequency of using fidget cube in daily life. This data can later be used in other scientific fields.Tingkat stress di dunia mengalami kenaikan dari tahun ke tahun. Oleh karena itu, teknologi semakin berkembang menciptakan alat pengurang stres yang mudah digunakan dan dibawa kemanapun. Salah satu alat pengurang stres adalah fidget devices. Saat ini, ada dua bentuk fidget devices yang umum digunakan, yaitu fidget spinner dan fidget cube. Kedua fidget devices ini dipercaya untuk mengatasi kegelisahan sehingga pengguna dapat memusatkan kegelisahannya ke fidget devices. Dalam perancangan kali ini, fidget device yang akan dibahas adalah fidget cube karena fidget cube dirasa lebih aman dan lebih bervariasi jika dibandingkan fidget spinner. Tak hanya penghilang stres, fidget cube berbasis IoT juga memiliki kemampuan untuk mengirim data ke web server. Hal ini bertujuan untuk melihat suatu trend atau data mengenai perilaku si pengguna, tombol mana saja yang sering digunakan oleh pengguna dan frekuensi penggunaan fidget cube pada kehidupan sehari-hari. Data ini nantinya dapat digunakan dalam bidang keilmuan lainnya.
Stuck Pipe Detection For North Sumatera Geothermal Drilling Operation Using Artificial Neural Network Sarwono Sarwono; Lukas Lukas; Maria Angela Kartawidjaja; Raka Sudira Wardana
Jurnal Migasian Vol 6 No 1 (2022): 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.v6i1.192

Abstract

One of the most common problems encountered during geothermal drilling operations is stuck pipe. The risk of stuck pipe is higher in geothermal drilling operations since geothermal drilling targets the lost circulation zone at reservoir depth. The stuck pipe problem can cause a significant increase in drilling time and costs. The cost of a stuck pipe includes the time and money spent on extracting the pipe, fishing the parted BHA, and the effort required to plug and abandon the hole. Therefore preventing stuck pipes is far more cost effective than the most effective freeing procedures. Many researchers are working to identify the symptoms to reduce the risk of a stuck pipe. Due to the complexion of stuck pipe’s symptoms and indicators, some researcher proposed artificial intelligence (AI) as the tool to predict stuck pipes. Although researches have been made to build systems employing artificial intelligence (AI) to avoid stuck pipe occurrences in oil and gas drilling operations, few works have been done for geothermal drilling operations. This paper describes a study that employed Artificial Neural Networks (ANN) approaches to predict stuck pipe incidents. Field data were collected from 6 geothermal wells drilled in North Sumatera fields. ANN was used to construct models to forecast stuck pipe incidents. The investigation found that ANN showed good performance with 84% accuracy and 74% recall for the limited training dataset. These ANN approaches provide good predictions that can help increase response time and accuracy in preventing stuck pipes.
Stuck Pipe Detection For North Sumatera Geothermal Drilling Operation Using Artificial Neural Network Sarwono Sarwono; Lukas Lukas; Maria Angela Kartawidjaja; Raka Sudira Wardana
Jurnal Migasian Vol 6 No 1 (2022): Jurnal Migasian
Publisher : LPPM Institut Teknologi Petroleum Balongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36601/jurnal-migasian.v6i1.192

Abstract

One of the most common problems encountered during geothermal drilling operations is stuck pipe. The risk of stuck pipe is higher in geothermal drilling operations since geothermal drilling targets the lost circulation zone at reservoir depth. The stuck pipe problem can cause a significant increase in drilling time and costs. The cost of a stuck pipe includes the time and money spent on extracting the pipe, fishing the parted BHA, and the effort required to plug and abandon the hole. Therefore preventing stuck pipes is far more cost effective than the most effective freeing procedures. Many researchers are working to identify the symptoms to reduce the risk of a stuck pipe. Due to the complexion of stuck pipe’s symptoms and indicators, some researcher proposed artificial intelligence (AI) as the tool to predict stuck pipes. Although researches have been made to build systems employing artificial intelligence (AI) to avoid stuck pipe occurrences in oil and gas drilling operations, few works have been done for geothermal drilling operations. This paper describes a study that employed Artificial Neural Networks (ANN) approaches to predict stuck pipe incidents. Field data were collected from 6 geothermal wells drilled in North Sumatera fields. ANN was used to construct models to forecast stuck pipe incidents. The investigation found that ANN showed good performance with 84% accuracy and 74% recall for the limited training dataset. These ANN approaches provide good predictions that can help increase response time and accuracy in preventing stuck pipes.
Co-Authors Doli Ramli W Joenarto, Prawibowo Maria Angela Kartawidjaja Mega Cynthia Wishnu Nova Eka Budiyanta RAKA SUDIRA WARDANA Rudy Rudy Sarwono Sarwono