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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) EMITTER International Journal of Engineering Technology JURNAL NASIONAL TEKNIK ELEKTRO INTEGER: Journal of Information Technology JMM (Jurnal Masyarakat Mandiri) International Journal of Community Service Learning Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal Technology and Implementation Bussines Jurnal Teknologi dan Terapan Bisnis Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Teknologi dan Terapan Bisnis Proceeding of Community Service and Engagement
Moch. Iskandar Riansyah
Universitas Telkom
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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ANALISA STUDI TENTANG PERANCANGAN ALAT MONITORING KUALITAS AIR PDAM BERBASIS INTERNET OF THINGS : ANALYSIS STUDY: DESIGN OF LOCAL WATER SUPPLY QUALITY MONITORING USING INTERNET OF THINGS Anifatul Faricha; Dimas Adiputra; Isa Hafidz; Lora Khaula Amifia; Moch. Iskandar Riansyah
Jurnal Teknologi dan Terapan Bisnis Vol. 2 No. 1 (2019): Vol 2 No 1 (2019): Jurnal Teknologi dan Terapan Bisnis
Publisher : Program Studi Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.96 KB) | DOI: 10.0301/jttb.v2i1.61

Abstract

Abstract Nowadays, as the gain of the global manufacturing technology, particularly at the industrial revolution 4.0, commonly it has also been increasing the amount of the waste products which directly impact and contaminate to the water quality. Hence, the water monitoring is required to maintain water’s quality whether it is safe or not, moreover at the local water supply utility (PDAM) which generally consumed by residents. Water quality monitoring becomes a vital issue and main concerns in these current days because the numbers of water resources are limited, whereas the total citizens in Indonesia are continuously increasing. Therefore, this study presents a review analysis about the design of water quality monitoring using the Internet of Things (IoT), which includes the key parameters selection at the water quality, proper sensors selection, and also IoT's platforms selection. Water quality monitoring will be acquired at several points in Surabaya using sensor array contain many sensors such as temperature sensors, turbidity sensors, conductivity sensors, and oxygen gas sensors. Then, data acquired from sensors are transmitted to the microcontroller which has the IoT module. Hence, information access from central to the user can be monitored, downloaded, or controlled everywhere and anywhere.
DESAIN DETEKSI KESALAHAN BATTERY MANAGEMENT SYSTEM MENGGUNAKAN ALGORITMA KALMAN FILTER PADA MOBIL LISTRIK NASIONAL Lora Khaula Amifia; Moch. Iskandar Riansyah; Isa Hafidz; Dimas Adiputra; Anifatul Faricha
Jurnal Teknologi dan Terapan Bisnis Vol. 2 No. 1 (2019): Vol 2 No 1 (2019): Jurnal Teknologi dan Terapan Bisnis
Publisher : Program Studi Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.112 KB) | DOI: 10.0301/jttb.v2i1.63

Abstract

Electric cars are currently being developed by many people because of low pollution and many countries used them in their daily activity. One of the important and main component is a battery, especially the Battery Management System (BMS) which can optimize the implementation of electric cars. BMS can protect and maintain the battery performance efficiently and at the same time can be a fault detection. Basically, It has three important parameters, there are current, voltage, and temperature that must be maintained and there is no overcurrent, overcharging, and discharging for too long because it can cause a fire. The protection of the BMS on electric cars need battery testing and done by taking current and voltage data, which prioritizes discharging and overdischarging test with a capacity of 2,2 Ah or a maximum capacity of 4,2 Volt. This research optimizes the work of BMS when experiencing faults/errors in order to work properly. The battery is modelled with a simple battery model (Rint) which previously identified parameters and formed a state space that aims to make fault detection. The results showed that fault detection using the Kalman Filter algorithm is very efficient and reliable in improving readings of overcurrent and overdischarge data so as to maintain security and extend/lifetime battery so that it can be implemented safely by the public
Desain dan Implementasi Sistem Sensor untuk Lokalisasi pada Autonomous Robot IVANA di Area Gedung Moch. Iskandar Riansyah Riansyah; Ardiansyah Al Farouq; Putu Duta Hasta Putra
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1093.2023

Abstract

One of the popular studies recently is about social robots that have been implemented in several public areas such as offices. The  robot is an employee or worker assistant robot in the Telkom Surabaya Institute of Technology building to help carry out the work of delivering packages to the destination according to the tasks given. The problem that often occurs is an error in the robot's localization system causing the robot's movement to the target point to experience a position error. This research contributes to the comparative evaluation of 2 localization methods on mobile robots, namely the first is the use of a rotary encoder sensor and the second is the use of sensor fusion based on the extended Kalman filter implemented on the robot prototype. This study aims to develop a sensor system that is adapted to the design of the robot and the environment in which the robot is tested and to find out the comparison of the two methods. The use of extended Kalman filter-based sensor fusion can provide more accurate results in robot localization, especially when moving on complex paths. Sensor fusion enables the combination of several sensors such as rotary encoders and IMU (Inertial Measurement Unit) sensors to provide more complete and accurate information about the position and orientation of the robot. In this study, sensor fusion successfully reduced the localization error of the  robot to 0.63 m when moving straight and 0.29 m when moving on a complex path, compared to the use of a single sensor which resulted in a larger error of 0.89 m. Based on the study that has been conducted, it can be considered as a potential solution in the development of other social robots to improve the accuracy and performance of the robots when performing certain tasks in the future.
Design Configuration of Water Quality Monitoring System in Surabaya: Design Configuration of Water Quality Monitoring System in Surabaya Anifatul Faricha; Dimas Adiputra; Isa Hafidz; Moch. Iskandar Riansyah; Lora Khaula Amifia; Moch. Fauzan Rasyid; Moch. Bagus Indrastata; Abdulloh Hamid Nushfi
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 1 No. 1 (2020): July
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v1i1.43

Abstract

Water have been important needs for human life in many sectors such as in industry, agriculture, and household that its quality must be conserved so is in Surabaya city. The quality of water could influence the quality of human life directly, thus it is important to have an integrated water quality monitoring system. Information regarding water quality monitoring such as pH, dissolved oxygen, turbidity, and conductivity were collected to produce a periodic decision for controlling, analyzing, and fixing the condition of the water. This paper proposed a design configuration of water quality monitoring system for tap water in Surabaya. First, a comparison study of water quality monitoring technology in terms of area, parameter, and methodology from the previous researchers is presented. From the study, the design configuration of water quality monitoring system to be implemented in Surabaya is concluded. The data collection method is better to be done by using Internet of Things (IoT) technology where it is possible to do multiple data type and multiple point real-time data collection throughout the water distribution network remotely.
Pendampingan Terapis Anak Berkebutuhan Khusus (ABK) Terhadap Penggunaan Teknologi SMILE (Smart Mobile Inclusive Learning (SMILE): AI-driven Multipurposed Therapy for Disability Children) Farah Zakiyah Rahmanti; Endah Suryawati Ningrum; Moch. Iskandar Riansyah; Gede Aditra Pradnyana; Fayruz Rahma
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 4 No. 2 (2024): The Proceeding of Community Service and Engagement (COSECANT) Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v4i2.8549

Abstract

Kurangnya sumber daya manusia yang paham terhadap teknologi berbasis kecerdasan buatan dan visi komputer yang belum tersedia pada Yayasan Pembinaan Anak Cacat (YPAC). Oleh karena itu, kelompok pengabdian masyarakat yang terdiri dari beberapa dosen yang berasal dari berbagai universitas di Indonesia diantaranya dosen yang berasal dari Institut Teknologi Sepuluh Nopember (ITS), Politeknik Elektronika Negeri Surabaya (PENS), Universitas Telkom (Tel-U), Universitas Pendidikan Ganesha (UNDIKSA), dan Universitas Islam Indonesia (UII) memberikan pendampingan penggunaan teknologi SMILE kepada terapis ABK yang berada di YPAC Surabaya. SMILE merupakan teknologi berbasis kecerdasan buatan dan visi komputer yang terdapat mini komputer dan kamera. Perangkat keras tersebut bertujuan untuk mengenali tangan manusia yang akan digunakan untuk terapi ABK. Hasil yang telah dicapai yakni terapis dan ABK sebagai pengguna dari teknologi SMILE dapat menggunakan teknologi tersebut dengan baik.
Pemanfaatan Teknologi Visi Komputer bagi Penyandang Disabilitas dan Pasien Pasca Stroke untuk Peningkatan Kualitas Terapi Fisik dan Kognitif Farah Zakiyah Rahmanti; Endah Suryawati Ningrum; Moch. Iskandar Riansyah; Gede Aditra Pradnyana; Fayruz Rahma
International Journal of Community Service Learning Vol. 9 No. 3 (2025): August
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijcsl.v9i3.92082

Abstract

Keterbatasan fasilitas rehabilitasi medis serta mahalnya biaya terapi menjadi hambatan utama dalam pemenuhan pelayanan kesehatan yang berkualitas bagi Anak Berkebutuhan Khusus (ABK), khususnya anak dengan tuna grahita. Hambatan tersebut berdampak pada rendahnya aksesibilitas terhadap terapi fisik dan kognitif yang efektif dan berkelanjutan. Pengabdian ini bertujuan untuk merancang dan mengembangkan perangkat terapi inovatif berbasis visi komputer yang mampu meningkatkan efektivitas layanan rehabilitasi secara interaktif dan terjangkau. Pengabdian ini menggunakan pendekatan pengembangan (research and development) dengan desain riset berbasis pengabdian masyarakat berbasis riset. Subjek terdiri dari lima orang terapis ABK dan lima wali ABK sebagai informan, serta sepuluh anak penyandang disabilitas sebagai subjek uji coba. Metode pengumpulan data dilakukan melalui observasi langsung, wawancara semi terstruktur, dan angket terbuka, dengan instrumen berupa lembar observasi, pedoman wawancara, dan kuesioner. Analisis data dilakukan secara deskriptif kualitatif dan kuantitatif sederhana untuk menilai efektivitas dan kepraktisan produk. Hasil menunjukkan bahwa perangkat terapi berupa permainan interaktif berbasis deteksi gerakan tangan melalui kamera, aplikasi pemantauan perkembangan berbasis web, serta video edukatif animasi 2D, mampu meningkatkan partisipasi dan keterlibatan anak dalam sesi terapi.
Improving 3D Human Pose Orientation Recognition Through Weight-Voxel Features And 3D CNNs Moch. Iskandar Riansyah; Oddy Virgantara Putra; Farah Zakiyah Rahmanti; Ardyono Priyadi; Diah Puspito Wulandari; Tri Arief Sardjono; Eko Mulyanto Yuniarno; Mauridhi Hery Purnomo
EMITTER International Journal of Engineering Technology Vol 13 No 1 (2025)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v13i1.847

Abstract

Preprocessing is a widely used process in deep learning applications, and it has been applied in both 2D and 3D computer vision applications. In this research, we propose a preprocessing technique involving weighting to enhance classification performance, incorporated with a 3D CNN architecture. Unlike regular voxel preprocessing, which uses a zero-one (binary) approach, adding weighting incorporates stronger structural information into the voxels. This method is tested with 3D data represented in the form of voxels, followed by weighting preprocessing before entering the core 3D CNN architecture. We evaluate our approach using both public datasets, such as the KITTI dataset, and self-collected 3D human orientation data with four classes. Subsequently, we tested it with five 3D CNN architectures, including VGG16, ResNet50, ResNet50v2, DenseNet121, and VoxNet. Based on experiments conducted with this data, preprocessing with the 3D VGG16 architecture, among the five architectures tested, demonstrates an improvement in accuracy and a reduction in errors in 3D human orientation classification compared to using no preprocessing or other preprocessing methods on the 3D voxel data. The results show that the accuracy and loss in 3D object classification exhibit superior performance compared to specific preprocessing methods, such as binary processing within each voxel.
Static Sign Language Classification Using RGB, Skeleton Image, and Fusion Representations: A Cross-Dataset Evaluation Moch. Iskandar Riansyah; Mohamad Yani; Ubaidillah Umar; Helmy Widyantara
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 15 No. 2 (2026)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v15i2.114587

Abstract

This study investigates static sign language classification by examining three image-based input representations, namely RGB images, skeleton images, and RGB+skeleton fusion, using two datasets with different visual characteristics. The first dataset reflects a relatively controlled acquisition setting, whereas the second dataset contains more complex background and visual variations. As an initial baseline, eight pretrained convolutional neural network (CNN) architectures were evaluated, and two representative models were subsequently selected for more detailed analysis. The baseline evaluation indicates that ResNet50 and EfficientNetB0 achieve the most competitive performance when RGB images are used as input. Further analysis of input representations shows that skeleton images are highly effective, particularly on the more challenging dataset, while RGB+skeleton fusion does not consistently improve classification performance. The cross-dataset evaluation further reveals a considerable performance drop across all configurations, suggesting the presence of a strong domain shift between the two datasets. In the A-B scenario, EfficientNetB0 with RGB input yields the best results, while in the B-A scenario, EfficientNetB0 with skeleton input shows the most stable performance. These findings indicate that the most effective input representation depends on the direction of domain transfer and that high intra-dataset performance does not necessarily reflect good generalization capability.
Fuzzy logic method for making push notifications on monitoring system of IoT-based electric truck charging Aqsha Al Madani Kurniawan; Lora Khaula Amifia; Moch. Iskandar Riansyah; Furizal Furizal; Iswanto Suwarno; Alfian Ma'arif; Hari Maghfiroh
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.7412

Abstract

To minimize the negligence when charging electric vehicles, it is deemed important to have an internet of things (IoT) based monitoring system using a notification feature. The monitoring system of electric vehicle battery charging used a voltage divider and temperature sensor (DS18B20) installed on the Arduino Mega 2560 microcontroller with the addition of an ESP8266 Wi-Fi module for sending microcontroller data into the Blynk platform. A notification feature was added as the reminder that the battery has been overcharging or overheating. This study applied the Mamdani fuzzy logic method to determine the conditions when notifications must appear. The results of the application of the Mamdani fuzzy logic method were able to determine the conditions for push notifications to appear using the parameters as desired; by so doing, it is possible to create a battery monitoring system with accurate push notification feature to prevent the battery from being overcharged and overheated.
Co-Authors Abdulloh Hamid Nushfi Adiputra, Dimas Ahmad Habibi Alfian Ma’arif Anak Agung Kusuma Jaya Ningrat Anifatul Faricha Aqsha Al Madani Kurniawan Ardiansyah Al Farouq Ardyono Priyadi Chaironi Latif Diah Puspito Wulandari DWI SURYANTO Eko Mulyanto Yuniarno Endah Suryawati Ningrum Endah Suryawati Ningrum Farah Zakiyah Rahmanti Fayruz Rahma Fayruz Rahma Furizal Furizal Gede Aditra Pradnyana Gede Aditra Pradnyana Habibi, Ahmad Hari Maghfiroh Helmy Widyantara Isa Hafidz Iswanto Suwarno Jesica Febriani Nura Lora Khaula Amifia Mauridhi Hery Purnomo Moch. Bagus Indrastata Moch. Fauzan Rasyid Mohamad Yani Muhammad Dwi Hariyanto Oddy Virgantara Putra Putu Duta Hasta Putra Putu Duta Putra Susijanto Tri Rasmana Tri Arief Sardjono Ubaidillah Umar