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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Elektron Jurnal Ilmiah EMITTER International Journal of Engineering Technology Jurnal Inotera Manutech : Jurnal Teknologi Manufaktur J-Innovation

Salfikar, Inzar

Politeknik Aceh

Author-ID : 694924

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 14 Documents Claim Missing Document

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Automatic Samples Selection Using Histogram of Oriented Gradients (HOG) Feature Distance Salfikar, Inzar; Sulistijono, Indra Adji; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 5, No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v5i2.182

Finding victims at a disaster site is the primary goal of Search-and-Rescue (SAR) operations. Many technologies created from research for searching disaster victims through aerial imaging. but, most of them are difficult to detect victims at tsunami disaster sites with victims and backgrounds which are look similar. This research collects post-tsunami aerial imaging data from the internet to builds dataset and model for detecting tsunami disaster victims. Datasets are built based on distance differences from features every sample using Histogram-of-Oriented-Gradient (HOG) method. We use the longest distance to collect samples from photo to generate victim and non-victim samples. We claim steps to collect samples by measuring HOG feature distance from all samples. the longest distance between samples will take as a candidate to build the dataset, then classify victim (positives) and non-victim (negatives) samples manually. The dataset of tsunami disaster victims was re-analyzed using cross-validation Leave-One-Out (LOO) with Support-Vector-Machine (SVM) method. The experimental results show the performance of two test photos with 61.70% precision, 77.60% accuracy, 74.36% recall and f-measure 67.44% to distinguish victim (positives) and non-victim (negatives).

PROTOTYPE PEMANFAATAN WIRELESS SENSOR NETWORK MENGGUNAKAN KOMUNIKASI WIRELESS ZIGBEE UNTUK MONITORING POWER QUALITY PADA PEMBANGKIT PLTMH Rachmad Ikhsan; Inzar Salfikar
J-Innovation Vol. 4 No. 1 (2015): J-Innovation
Publisher : Politeknik Aceh

The continued development of industrial technology at this point that leads to the field of moderninformation technologies so as to facilitate the work of man. The use of electrical energy continues toincrease over time, causing consumers want to know the quality of electrical energy consumed, resultingfrom the demand for electrical energy monitoring needs to be done in this case concerns the quality ofelectric power generated from a mini-hydro power plant (PLTMH). In this study, we will design andsimulate the process parameters of electrical energy to be monitored, in the form of voltage, current,frequency and different phase that will be on all four of these parameters will be used as a reference if thequality of power (power quality) of a plant is good or no. To obtain the data we use multiple sensorsnamely, voltage sensor, current sensor and sensor using a frequency of zero crossing detector. Dataparameters of electrical energy on each sensor node is transmitted wirelessly using XBee RF modules areintegrated with zigbee protocol to the gateway. On the side of the gateway will connect via CDMA andsend packets of data - the data packets to the web database. Consumers can access the data - the data viathe mobile phone network to a web-connected database. On the web will be shown the data - the dataparameter values of the electrical energy. So that consumers can see the parameters of electrical energythat is needed is good or not.

PENDETEKSI KONSENTRASI GAS AMMONIA (NH3) BERBASIS INTERNET OF THINK Rouhillah; Inzar Salfikar
J-Innovation Vol. 10 No. 1 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Everyone really needs air in the process of breathing, but they don't know how much ammonia (NH3) is in the air. Therefore it is necessary to monitor ammonia (NH3) levels in the room with an Internet of Think (IoT) based ammonia (NH3) concentration meter with Wemos D1 as a microcontroller and an MQ-137 sensor, with this measuring instrument you can find out the level of ammonia levels ( NH3) in the room in real time using the MQ-137 as an ammonia level sensor (NH3), a programmed Wemos D1 that can process the level of ammonia (NH3) levels in the air. From the experimental results that the MQ 137 sensor can be said to be linear because it gets the results of R2 = 0.9613216, the ammonia gas condition is more than 25 ppm, the buzzer and fan will turn on.

Rancang Bangun Alat Monitoring Nutrisi Kebun Hidroponik Rouhillah; Inzar Salfikar; Javid Hamar
J-Innovation Vol. 10 No. 2 (2021): Jurnal J-Innovation
Publisher : Politeknik Aceh

Hydroponics is a way of farming that does not use soil as a planting medium, but its uses water that contains nutrients. In the growth of hydroponic plants, it can be affected by various factors, one of them is the delay in adding hydroponic water nutrients. This research aims to create a system monitoring nutrient levels and water availability in reservoir. Then, the microcontroller processes the data and sends the data with the help of NodeMcu ESP8266 to Firebase. The data in Firebase will be forwarded to Android using the MIT App Inventor software with Internet of Thing (IoT) technology. In this research, the hydroponic plants used are lettuce which has a nutritional value of around 560 - 840 in units of parts per million (ppm). As a result of testing, the sensor is not able to measure nutrient levels reaching 850 ppm and the xkc-y25 sensor can detect water in a full or reduced reservoir, all of these sensors data are measured in real time, and can be monitored via android.

RANCANG BANGUN MESIN ABSENSI TANPA MENYENTUH DENGAN RFID Rizki Faulianur; Inzar Salfikar
J-Innovation Vol. 11 No. 1 (2022): Jurnal J-Innovation
Publisher : Politeknik Aceh

In education, attendance is very important for lecturers and students. Currently, attendance used in universities still uses signatures or fingerprints so that there is direct contact with certain objects. But in the current pandemic. students and lecturers are required to keep their distance and avoid physical contact with shared objects because they can spread the virus quickly. This Attendance machine is offered to limit direct contact and inhibit the spread of the coronavirus by using Radio Frequency Identification (RFID) as a method of controlling Raspberry pi. RFID will generate a unique code that is used as user data which will then be stored with Raspberry pi and then stored in the database. RFID can read the reader within a range of 3 cm. From the test results, this machine is able to recognize 3 users who detect and process data quickly

Mesin Absensi Face Recognition Berbasis Raspberry Pi Rizki Faulianur; Inzar Salfikar; Ryan Mulyawan
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 10, No 4 (2022): Vol. 10, No 4, Desember 2022
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v10i4.119557

Mesin absensi sidik jari gagal merekap absensi dengan kondisi jari yang terluka, tergores, kulit jari terkelupas dan lainnya sehingga kehadiran tidak tercatat. Penelitian ini bertujuan membuat mesin absensi pengenalan wajah untuk meminimalisir kegagalan seperti pada mesin sidik jari. Penelitian ini merupakan pengembangan penelitian sebelumnya dengan sistem absensi Radio Frequency Identification (RFID) karena sistem absensi dengan RFID dapat dicurangi. Penggabungan sistem rekognisi wajah dan RFID pada sebuah mesin absensi dengan raspberry pi diharapkan dapat menimalisir kegagalan pada saat melakukan absensi. Seandainya terjadi kegagalan rekognisi wajah, pengguna dapat melakukan absensi dengan RFID. Absensi dengan RFID pada sistem ini hanya dapat dilakukan ketika terjadi kegagalan deteksi wajah. Untuk mengetahui persentase keberhasilan dan keakurasian mesin, setiap pengguna melakukan beberapa kali percobaan. Selanjutnya dicatat jumlah keberhasilan rekognisi wajah dan dihitung nilai akurasinya dengan metode perhitungan akurasi. Hasil percobaan identifikasi wajah, diperoleh keakurasian pengguna pertama sebesar 53 %, pengguna kedua 48 %, pengguna ketiga 45 % dan pengguna keempat 52 %. Mesin mampu memprediksi 4 gambar pengguna dengan 4 posisi wajah yang berbeda dengan waktu rata-rata proses identifikasi selama 7 detik.Kata kunci : Face recognition, mesin absensi, raspberry pi. The fingerprint attendance machine failed to record attendance with injured, scratched, peeled finger skin and others so that attendance was not recorded. This research is a development of previous research with Radio Frequency Identification (RFID) attendance system because attendance system with RFID can be rigged. The incorporation of a facial recognition system and RFID on an attendance machine with a raspberry pi is expected to minimize failures during attendance. If there is a facial recognition failure, the user can make attendance with RFID. Attendance with RFID in this system can only be done when there is a face detection failure. To find out the percentage of success and accuracy of the machine, each user performs several trials. Furthermore, the number of facial recognition successes was recorded and the accuracy value was calculated using the accuracy calculation method. The results of the face identification experiment showed that the accuracy of the first user was 53%, the second user was 48%, the third user was 45% and the fourth user was 52%. The machine is able to predict 4 user images with 4 different face positions with an average identification process time of 7 seconds.Keywords: Face recognition, attendance machine, raspberry pi.

Implementasi Sensor Pir dan Kamera untuk Keamanan Ruangan Berbasis Internet of Things Rouhillah; Inzar Salfikar; Fajri Aqsalmi
J-Innovation Vol. 12 No. 1 (2023): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v12i1.177

Room security is a very important thing to prioritize. One of the solutions to prevent crime levels needs to be equipped with a security device or a device capable of monitoring a room with the ability to detect the presence of an unwanted person. Therefore, this study designed a tool to monitor rooms based on the Internet of Thing (IoT) with surveillance cameras, which is one way to monitor the situation in a room. This system combines the use of the pir sensor, the raspberry pi camera module, and the raspberry pi, in order to be able to find out the condition of the room in the form of photos sent and also use bot features on internet applications, namely telegram messenger. This system is more efficient because it uses storage from telegram, and also the system will send notifications via telegram bots. So that the user can take action as soon as possible if things happen that are not desired. When the pir sensor detects movement in the room, the camera takes a photo and then sends it to the user's telegram bot account and the buzzer sounds as an early prevention of crime.

Desain and Construction Hybrid System of PLN-PV-Battery in the Receiver Box Package Based Internet of Things Rachmad Ikhsan; Inzar Salfikar; Ramadhani
Jurnal Inotera Vol. 8 No. 2 (2023): July - December 2023
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol8.Iss2.2023.ID263

In previous research, if there was a power outage from PLN, the electrical system in the package receiving box experienced problems, so that the package courier could not access the package receiving box. The purpose of making this tool is to overcome electrical supply failures in IoT-based package receiving boxes. The system designed uses voltage sensors connected to each source of electrical energy from PLN, Photovoltaic (PV) and also batteries. After that, the voltage sensor gives a signal to the Arduino for the switching process to be carried out on each source of electrical energy. This system works, if there is a power outage from PLN, the electrical energy is supplied via PV. If the PV voltage is not sufficient, the electrical system will be supplied via batteries, so that the electrical energy in the package receiving box will always be available and can work even if there is a power outage from PLN. Based on the hybrid system test results, it was found that the voltage sensor works by detecting voltage from each source of electrical energy. When the voltage sensor does not detect a voltage source from PLN, the system will switch to PV, when the voltage sensor on the PV detects a voltage below 10 Volts, then the system will switch to battery.

Rancang Bangun Alat Hand Sanitizer Otomatis dan Pengukur Suhu Tubuh Rouhillah; Inzar Salfikar; Hafis Husna
J-Innovation Vol. 13 No. 1 (2024): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v13i1.280

During the Covid-19 pandemic, medical equipment is needed by all humans. One of them that is widely used as initial protection is hand sanitizer. Hand sanitizer is an antiseptic in the form of a gel that is widely used as a practical hand sanitizer. This final project aims to make a body temperature checking device and automatic hand sanitizer spraying, so that with this tool it can help prevent the transmission of the Covid-19 virus in routinely checking body temperature and cleaning hands from bacteria or germs without touching the tool. The sensors used in the manufacture of this final project consist of a temperature sensor mlx90614 as a body temperature detector and a proximity sensor as a trigger for a water pump. LCD (Liquid Crystal Display) serves to display temperature data that has been detected and the speaker emits sound according to the temperature detected later. Based on the detection accurasy test, the accurasy value is 94,74%.

Prototype of Fire, Gas, and Steam Pressure Detection Based on Internet of Things (Case Study: PT Agro Sinergi Nusantara) Inzar Salfikar; Faulianur, Rizki; Yhona Syela Inri; Dodi Syahputra
Jurnal Inotera Vol. 10 No. 1 (2025): January-June 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss1.2025.ID429

This study is based on a conversation that took place during an industrial vist by Aceh Polytechnic D3 Mechatronics students at PT Agro Sinergi Nusantara (ASN), where the company does not yet have a system in place to monitor gas, steam, and fire pressure in order to reduce hazardous circumstances in the factory. A fire detection system is needed to prevent fires because palm oil factories often have processes that involve flammable materials and have the potential to cause fires. The steam pressure in the boiler of the Steam Power Plant (PLTU) system at PT ASN needs to be monitored to prevent explosions. The PLTU combustion system that utilizes palm oil pulp and empty bunches produces carbon emissions that are harmful to health. Information on carbon gas levels also needs to be known to ensure whether the surrounding conditions are dangerous. The presence of fire, gas and steam pressure needs to be monitored via a smartphone connected to the Internet network. Thus, workers do not have to be close to the machine area because monitoring is sufficient on a smartphone. The research method is a case study at PT ASN, surveys and interviews, literature studies, experiments and simulations on prototypes and data collection in the laboratory. The data used for measurement are fire and gas from matches and air pressure from the compressor. The results obtained, this prototype is able to detect fire, gas and vapor pressure. When fire is detected, pressure and gas that exceed the setting limit will trigger the alarm to activate. The presence of fire and gas and vapor pressure data can be monitored on a smartphone with a delay of 17 seconds. The average accuracy of pressure detection with arduino is 96.20% and smartphone 97.07%.

Co-Authors Aan Febriansyah Achmad Basuki Ahyar Mustafa Andrian Maulana Atthariq, Atthariq Dodi Syahputra Fajri Aqsalmi Faulianur, Rizki Hafis Husna Ichan, Maulidi Indra Adji Sulistijono Javid Hamar Rachmad Ikhsan Ramadhani Rizki Faulianur Rouhillah Rouhillah Rouhillah, Rouhillah Ryan Mulyawan Yhona Syela Inri

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