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All Journal Mechatronics, Electrical Power, and Vehicular Technology Jurnal INKOM Jurnal Teknologi dan Sistem Komputer Jurnal Elektronika dan Telekomunikasi JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Indonesian Journal of Laboratory
Ade Ramdan
Research Center for Informatics, Indonesian Institute of Sciences, Kompleks LIPI Gd. 20, Lt. 3, Jl. Sangkuriang, Bandung
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences

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Modeling of Electric Field Around 100 MVA 150/20 kV Power Transformator using Charge Simulation Method Rachman, Noviadi Arief; Risdiyanto, Agus; Ramdan, Ade
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 4, No 1 (2013)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2013.v4.33-40

Abstract

Charge Simulation Method is one of the field theory that can be used as an approach to calculate the electromagnetic distribution on the electrical conductor. This paper discussed electric field modeling around power transformator by using Matlab to find the safety distance. The safe distance threshold of the electric field to human health refers to WHO and SNI was 5 kV/m. The specification of the power transformator was three phases, 150/20 kV, and 100 MVA. The basic concept is to change the distribution charge on the conductor or dielectric polarization charge with a set of discrete fictitious charge. The value of discrete fictitious charge was equivalent to the potential value of the conductor, and became a reference to calculate the electric field around the surface contour of the selected power transformator. The measurement distance was 5 meter on each side of the transformator surface. The results showed that the magnitude of the electric field at the front side was 5541 V/m, exceeding the safety limits.
Desain dan Implementasi Fraction Collector Menggunakan MCs 51 Ramdan, Ade; Sutarlan, Elan; Gojali, Elli A.; S, Nanang
INKOM Journal Vol 6, No 1 (2012)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.292 KB) | DOI: 10.14203/j.inkom.168

Abstract

 This paper presents a design and an implementation of a chemical laboratory equipment which serves to collect automatically liquid droplets from a column in the chromatography colomn. This equipment uses MCs 51 family for setting hatching time, displaying hatching counter, and moving the dropper in X and Y axes. Two stepper motors are used to fill 225 tubs with each volume is 15 ml. Therefore, we have a Fraction Collector. The results shows that our system works well, all droplets occurs in the middle of the tube, and the time for transfering a dropler  from one tube to another time is 6.5 seconds.Keywords: chromatography colomn, MCs51 controller, test tube, Fraction Collector. Tulisan ini membahas mengenai desain dan pembuatan Fraction Collector yaitu peralatan laboratorium kimia yang berfungsi untuk menampung tetesan cairan yang keluar dari suatu kolom pada proses kromatografi kolom secara otomatis. Alat ini dilengkapi sebuah pengendali mikrokontroler MCs 51 untuk mengatur dan menampilkan lamanya waktu penetesan, juga menggerakkan penetes ke arah sumbu X dan Y oleh dua buah motor stepper untuk mengisi 225 tabung reaksi yang masing-masing berukuran 15 ml. Hasil pengujian sistem bekerja dengan baik, tetesan terjadi ditengah-tengah tabung dan rata-rata waktu yang dibutuhkan untuk perpindahan penetes dari satu tabung ke tabung berikutnya adalah 6.5 detik.  Kata kunci: Fraction Collector, kromatografi kolom, pengendali MCs 51, tabung reaksi  
Pendeteksian Gerakan Menggunakan Transduser Ultrasound dengan Metoda Pembandingan Pola Gema Prajitno, Dicky Rianto; Ramdan, Ade
INKOM Journal Vol 8, No 2 (2014)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.437 KB) | DOI: 10.14203/j.inkom.246

Abstract

Pada tulisan ini kami mengusulkan metoda pendeteksi gerakan. Pendeteksian dilakukan dengan cara membandingkan dua buah pola gema dalam interval waktu tertentu dan jeda antara pola gema. Perbedaan pola gema menunjukkan terjadinya gerakan dari benda-benda di area deteksi sensor. Dengan metoda pembandingan ini, sensor menjadi sensitif terhadap gerakan atau perubahan posisi setiap objek yang berada disekitarnya. Hasil yang diperoleh memperlihatkan bahwa sensor ini secara khusus lebih sensitif dibandingkan sensor PIR dalam mendeteksi gerakan-gerakan kecil. Pada prakteknya metoda ini telah mampu mendeteksi beberapa gerakan tubuh manusia seperti: dari mulai berjalan; duduk; berbicara; hingga gerak respirasi tubuh.
Rancang Bangun Smart Lamp Ramdan, Ade; Prajitno, Dicky Rianto; Herlan, Herlan; Gojali, Elli Ahmad
INKOM Journal Vol 7, No 2 (2013)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3357.255 KB) | DOI: 10.14203/j.inkom.240

Abstract

In this paper, we propose a LED-based smart lamp prototype that integrated with sensor. The smart lamp use information of people and lighting confirmation, to turn on or turn off the lamp automatically. In addition, the sensor calculates and balances flash and ambient light exposure to decrease the light, so that can make energy efficiently in use. PIR (Passive Infrared Receiver) and Ultrasonic sensor is preferred to detect people condition in one place and LDR (Light Dependent Resistant) is preferred to detect intensity of light. In experimental system of smart lamp obtain good condition where the average of illuminance 257,6 lux. The smart lamp can detect large and small movements caused by human beings and can provide a constant room lighting.keywords: Smart lamp, Presence detection, Ultrasonic Pada tulisan ini, sebuah lampu pintar berbasis LED berbasis integrasi sensor deteksi keberadaan dan sensor deteksi cahaya diusulkan. Sensor digunakan untuk menyalakan atau memadamkan lampu secara otomatis berdasarkan keberadaan orang disekitarnya. Selain itu, lampu pintar juga dapat mengatur tingkat pencahayaan yang dibutuhkan  dengan memperhatikan cahaya ambien untuk mencegah terjadinya pencahayaan yang berlebih guna menghindari energi yang terbuang sia-sia. Deteksi keberadaan menggunakan penggabungan dua buah sensor yaitu PIR (Passive Infrared Receiver)  dan Ultrasonik, sedangkan deteksi cahaya menggunakan sensor LDR (Light Dependent Resistant). Hasil pengujian mendapatkan sistem lampu penerangan bekerja dengan baik dan dapat memberikan pencahayaan sebesar 257,6 lux. Lampu Pintar tersebut sudah dapat mendeteksi gerakan besar dan kecil yang ditimbulkan oleh manusia dan dapat memberikan pencahayaan ruangan yang konstan.kata kunci: Lampu pintar, Deteksi keberadaan, Ultrasonik
DEEP CNNBASED DETECTION FOR TEA CLONE IDENTIFICATION Ramdan, Ade; Suryawati, Endang; Kusumo, R. Budiarianto Suryo; Pardede, Hilman F.; Mahendra, Oka; Dahlan, Rico; Fauziah, Fani; Syahrian, Heri
Jurnal Elektronika dan Telekomunikasi Vol 19, No 2 (2019)
Publisher : Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jet.v19.45-50

Abstract

One factor affecting the quality of tea is the selection of plant material that would be planted on the field. Clonal selection is a common way to produce tea with better quality. However, as a natural cross pollination species, tea often consists of various clones or progenies of cross-pollinated process. This commonly occurs on plantations owned by smallholder farmers. To produce a consistent quality tea, the clones or progenies need to be identified. Usually, human experts distinguish the plants from leaves by visual inspection on the physical attributes of the leaves, such as the textures, the bone structures, and the colors. It is very difficult for non-experts or common farmers to do such identifications. In this, we propose a deep learning-based identification of tea clones. We apply deep convolutional neural network (CNN) to identify 3 types of tea clones of Gambung series, a series of tea clones developed at Research Institute of Tea and Cinchona. Our study indicates that the performance of the CNN systems are affected by the depth of the convolutional layers. VGGNet, a popular CNN architectures with 16 layers, achieves better accuracy compared to AlexNet, a CNN with 6 layers.
Komunikasi Data Antara Modul MMI (Man Machine Interface) dan Modul Scrambler/Descrambler pada Telepon Scrambler Herlan, Herlan; Ramdan, Ade
INKOM Journal Vol 6, No 2 (2012)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.218 KB) | DOI: 10.14203/j.inkom.194

Abstract

This paper proposes a data communication system between MMI module with scrambler/descrambler module. The system is designed and implemented on a scrambler phone. The trasmitted data is needed to determine the speed of randomization sound signal processes and patterns. The data is transmitted through microcontroller based serial communication. A data communication protocol is designed to perform data communication between two modules. The experiment shows serial data communication between the MMI module and the scrambler/ descrambler module with 1200 bps data transmission speed is working properly without errors by a proof that the scrambler/descrambler module sends a "OK" after the MMI module sends data of the speed and pattern of the sound signal randomization that ends with a "AA".
Automatic detection of crop diseases using gamma transformation for feature learning with a deep convolutional autoencoder Zilvan, Vicky; Ramdan, Ade; Supianto, Ahmad Afif; Heryana, Ana; Arisal, Andria; Yuliani, Asri Rizki; Krisnandi, Dikdik; Suryawati, Endang; Suryo Kusumo, Raden Budiarianto; Yuawana, Raden Sandra; Kadar, Jimmy Abdel; Pardede, Hilman F.
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 10, Issue 3, Year 2022 (July 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14250

Abstract

Precision agriculture is a management strategy for sustaining and increasing the production of agricultural commodities. One of its implementations is for crop disease detection. Currently, deep learning methods have become widespread methods for the automatic detection of crop diseases. Most deep learning methods showed better performance when using an original image in raw form as inputs. However, the original image of crop diseases may appear similar between one disease to another.  Therefore, the deep learning methods may misclassify the data. To deal with these, we propose the gamma transformation with a deep convolutional autoencoder to extract good features from the original image data. We use the output of the gamma transformation with a deep convolutional autoencoder as inputs to a classifier for the automatic detection of crop diseases. Our experiments show that the average accuracies of our method improve the performance of crop disease detection compared to only using raw data as inputs.
Robust remaining useful life prediction of lithium-ion battery with convolutional denoising autoencoder Yuliani, Asri Rizki; Pardede, Hilman Ferdinandus; Ramdan, Ade; Zilvan, Vicky; Yuwana, Raden Sandra; Amri, M Faizal; Kusumo, R. Budiarianto Suryo; Pramanik, Subrata
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.905

Abstract

Using lithium-ion (Li-ion) batteries exceeding their useful lifetime may be dangerous for users, and hence, developing an accurate prediction system for batteries that remain useful for life is necessary. Many deep learning models, such as gated recurrent units and long short-term memory (LSTM), have been proposed for that purpose and have shown good results. However, their performance when dealing with noisy data degrades significantly. This may hamper their implementations for the real world since battery data are prone to noise. In this paper, we develop a robust prediction model in a noisy environment for predicting the remaining useful life (RUL) of Li-ion batteries. We propose a denoising autoencoder (DAE) utilized to remove noise from the data. The DAE is built with convolutional layers instead of traditional feed-forward networks here. We combine DAE with LSTM as the predictor. The proposed framework is evaluated using artificially corrupted battery data provided by National Aeronautics and Space Administration (NASA). The results reveal that our proposed method improves robustness when data contain various types of noise. A comparative study using the traditional approach has also been conducted. Our evaluation shows that convolutional layers are more effective than the traditional approach and that the original composition of the DAE was built using traditional feed-forward networks. DAE with convolutional layers has the best average performance with MSE of 0.61 and is the most consistent model.
Two-Stage Object Detection for Autonomous Vehicles With VGG-16 Based Faster R-CNN Dewi, Arnetta Listiana; Pardede, Hilman F.; Suryawati, Endang; Pratiwi, Hasih; Heryana, Ana; Yuliani, Asri R; Ramdan, Ade
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.551

Abstract

The implementation of object detection for autonomous vehicles is essential as it is necessary to identify common object on the street so proper response could be designed. While single stage object may be smaller in computations, two-stage object detection is preferred due to the ability to localize the object. In this paper, we propose to use Faster R-CNN with VGG-16 backbone for detections of object on the street. We evaluate the method with open image subset by selecting objects that are common on street. We explore several hyper-parameters setup such as learning rate and the number of ROI regions to find the optimum set-up. We found that the use of learning rate 10-6 with Adam optimizer to be the optimum value for this task. We also found that increasing the number of ROI may benefit the performance. This shows that there is potential for getting a higher mAP with increase the amount of RoI.
Pengembangan Konsep Landasan Robot Beroda Omnidirection Pemindah Barang Berbahan Extrusi Profil Aluminium Ramdan, Ade; Prayoga, Reka Ardi; Ramadhan, Nur Jamiludin; Subekti, Irham; Anjani, Rifania
JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Vol 6 No 2 (2024): Volume: 6 | Nomor: 2 | Oktober 2024
Publisher : Pusat Penelitian, Pengembangan, dan Pemberdayaan Masyarakat (P4M) Politeknik Manufaktur Bandung (Polman Bandung)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48182/jtrm.v6i2.170

Abstract

This research examines how concept development was carried out to design an omnidirectional wheeled robot base made from extruded aluminum profiles used for moving goods. Concept design goes through a series of stages, that is: identifying problems, determining the function structure, looking for alternative solutions, building concept variations, assessing concept variations and determining the selected concept. After going through all these stages, it was concluded that an omnidirectional robot base can be divided into 2 sub-functions, namely: base frame and electrical energy converter. These two sub-functions have 6 parameters that can be varied, such as: various frame shapes, type of frame material, type of frame bar shape, type of frame connection, type of wheel, type of motor. Alternative solutions can be sought for each parameter, combined and assessed to obtain a variation of the selected concept that meets the list of requirements.
Co-Authors Agus Risdiyanto Ahmad Afif Supianto Amri, M Faizal Andria Arisal, Andria Anjani, Rifania Dahlan, Rico Dewi, Arnetta Listiana Fani Fauziah, Fani Gojali, Elli A. Gojali, Elli Ahmad Heri Syahrian, Heri Herlan, Herlan Heryana, Ana Kadar, Jimmy Abdel Krisnandi, Dikdik Kusumo, R. Budiarianto Suryo Noviadi Arief Rachman Oka Mahendra Pardede, Hilman F. Pardede, Hilman F. Pardede, Hilman Ferdinandus Prajitno, Dicky Rianto Pramanik, Subrata pratiwi, hasih Prayoga, Reka Ardi Ramadhan, Nur Jamiludin S, Nanang Subekti, Irham Suryawati, Endang Suryo Kusumo, Raden Budiarianto Sutarlan, Elan Vicky Zilvan, Vicky Yuawana, Raden Sandra Yuliani, Asri R Yuliani, Asri Rizki Yuwana, Raden Sandra