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ANALISA STUDI TENTANG PERANCANGAN ALAT MONITORING KUALITAS AIR PDAM BERBASIS INTERNET OF THINGS Faricha, Anifatul
Jurnal Teknologi dan Terapan Bisnis Vol 2 No 1 (2019): March
Publisher : AKADEMI KOMUNITAS SEMEN INDONESIA GRESIK

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

Di era perkembangan industri yang semakin maju umumnya juga dibarengi dengan meningkatnya produksi limbah pabrik yang mengakibatkan pencemaran dan turunnya kualitas air jika tidak dikelola dengan benar, untuk itu pengawasan air di beberapa titik lokasi yang berbeda perlu dilakukan untuk menjaga kualitas air yang didistribusikan kepada penduduk, terutama air PDAM. Terbatasnya sumber air dibandingkan dengan peningkatan jumlah populasi penduduk di Indonesia dan juga infrakstruktur distribusi air yang sudah tua merupakan tantangan besar dalam monitoring kualitas air secara real time. Maka dari itu, penelitian ini menyajikan analisa studi tentang perancangan alat monitoring kualitas air PDAM berbasis Internet of Things (IoT) yang meliputi pemilihan parameter-parameter yang digunakan dalam menentukan kualitas air, pemilihan sensor-sensor yang sesuai, serta pemilihan platform IoT yang digunakan. Pengawasan kualitas air PDAM akan dilakukan di beberapa sebaran titik di Surabaya menggunakan sensor suhu, sensor kekeruhan, sensor konduktivitas, dan sensor gas oksigen yang terintegrasi sebagai sensor array. Data-data yang berasal dari sensor-sensor tersebut kemudian ditransmisikan ke mikrokontroler yang memiliki modul IoT sehingga pengaksesan informasi dari sentral ke pengguna bisa dimonitor dari mana saja dan kapan saja.

The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia Muhammad Achirul Nanda; Anifatul Faricha; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Muhammad Falahudin Malich Salaz; Qurrotun 'Ayun Mawadatur Rohmah; Ulfah Abqari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2900-2910

The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.

Design of Electronic Nose System Using Gas Chromatography Principle and Surface Acoustic Wave Sensor Anifatul Faricha; Suwito Suwito; M. Rivai; M.A. Nanda; Djoko Purwanto; Rizki Anhar R.P.
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7127

Most gases are odorless, colorless and also hazard to be sensed by the human olfactory system. Hence, an electronic nose system is required for the gas classification process. This study presents the design of electronic nose system using a combination of Gas Chromatography Column and a Surface Acoustic Wave (SAW). The Gas Chromatography Column is a technique based on the compound partition at a certain temperature. Whereas, the SAW sensor works based on the resonant frequency change. In this study, gas samples including methanol, acetonitrile, and benzene are used for system performance measurement. Each gas sample generates a specific acoustic signal data in the form of a frequency change recorded by the SAW sensor. Then, the acoustic signal data is analyzed to obtain the acoustic features, i.e. the peak amplitude, the negative slope, the positive slope, and the length. The Support Vector Machine (SVM) method using the acoustic feature as its input parameters are applied to classify the gas sample. Radial Basis Function is used to build the optimal hyperplane model which devided into two processes i.e., the training process and the external validation process. According to the result performance, the training process has the accuracy of 98.7% and the external validation process has the accuracy of 93.3%. Our electronic nose system has the average sensitivity of 51.43 Hz/mL to sense the gas samples.

Sistem Identifikasi Gas Menggunakan Sensor Surface Acoustic Wave dan Metoda Kromatografi Anifatul Faricha; Muhammad Rivai; Suwito Suwito
Jurnal Teknik ITS Vol 3, No 2 (2014)
Publisher : Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS

Banyak metode yang digunakan untuk mengidentifikasikan suatu gas, salah satunya adalah dengan menggunakan metode kromatografi. Pada umumnya kromatografi gas memiliki prinsip kerja yang didasari dari pemisahan fisik senyawa organik pada suhu tertentu, di mana senyawa tersebut dibawa oleh suatu gas pembawa menuju kolom partisi. Setiap senyawa akan memiliki kecepatan yang berbeda-beda dalam melewati kolom sesuai dengan nilai kepolaran. Sensor surface acoustic wave digunakan sebagai detektor yang menghasilkan respon frekuensi, respon tersebut dihitung oleh sebuah device frequency counter. Pada penelitian ini telah dilakukan pengidentifikasian gas yang menggunakan algoritma neural network. Hasil percobaan menunjukkan bahwa sistem ini mampu mengidentifikasi jenis gas dengan tingkat keberhasilan 90%. Secara keseluruhan metode ini diharapkan menjadi metode yang baik untuk sistem identifikasi gas.

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 : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i1.61

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 : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i1.63

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

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 : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i1.61

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 : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i1.63

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

Comparison study of transfer function and artificial neural network for cash flow analysis at Bank Rakyat Indonesia Anifatul Faricha; Siti Maghfirotul Ulyah; Rika Susanti; Hawwin Mardhiana; Muhammad Achirul Nanda; Ilma Amira Rahmayanti; Christopher Andreas
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6635-6644

The cash flow analysis is essential to examine the economic flows in the financial system. In this paper, the financial dataset at Bank Rakyat Indonesia was used, it recorded the sources of cash inflow and outflow during a particular period. The univariate time series model like the autoregressive and integrated moving average is the common approach to build the prediction based on the historical dataset. However, it is not suitable to estimate the multivariate dataset and to predict the extreme cases consisting of nonlinear pairs between independent-dependent variables. In this study, the comparison of using two types of models i.e., transfer function and artificial neural network (ANN) were investigated. The transfer function model includes the coefficient of moving average (MA) and autoregressive (AR), which allows the multivariate analysis. Furthermore, the artificial neural network allows the learning paradigm to achieve optimal prediction. The financial dataset was divided into training (70%) and testing (30%) for two types of models. According to the result, the artificial neural network model provided better prediction with achieved root mean square error (RMSE) of 0.264897 and 0.2951116 for training and testing respectively.

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

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.

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