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All Journal International Journal of Electrical and Computer Engineering Jurnal Keteknikan Pertanian Perfecting a Video Game with Game Metrics JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Computer, Electronic, and Telecommunication (COMPLETE)
Nanda, Muhammad Achirul
Universitas Padjadjaran
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

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The Comparative Study for Predicting Disease Outbreak anifatul faricha; M. Achirul Nanda; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Robin Addwiyansyah Alvaro Samrat
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 1 No. 1 (2020): July
Publisher : Institut Teknologi Telkom Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v1i1.48

Abstract

To know the prediction of disease outbreak, proper predictive modeling is required to represent the dataset. This study presents the comparative predictive modeling for predicting disease outbreak using two models i.e., optimizable support vector machine (SVM) and optimizable gaussian process regression (GPR). The dataset used in this study contains three cases i.e., positive cases, recovered cases, and death cases. The dataset at each case is divided into training dataset for the training process and external validation dataset for the validation process. Based on the training process and validation process, the root mean square error (RMSE) at positive cases, recovered cases, and death cases using optimizable GPR is substantially more effective for prediction than the optimizable SVM. According to the result performance, by applying optimizable GPR, the training process has the average RMSE of 19.54 and the validation process has the average RMSE of 15.85.
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

Abstract

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

Abstract

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.
EVALUASI RESPON MASYARAKAT PADA DISEMINASI PENERAPAN TEKNOLOGI HIDROPONIK SMART WATERING Muhammad Achirul Nanda; Sophia Dwiratna Nur Perwitasari; Kharistya Amaru
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 28, No 1 (2022): JANUARI-MARET
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jpkm.v28i1.32189

Abstract

Hidroponik merupakan salah satu teknik budidaya tanaman pertanian tanpa menggunakan tanah sebagai media tanam. Pada investigasi ini, kami mengusulkan sebuah terobosan teknologi untuk mengatasi kesenjangan pada berbagai konsep hidroponik, yang dikenal sebagai teknologi smart watering (SW). Teknologi SW merupakan sebagai sebuah produk inovasi hidroponik kit yang menggunakan prinsip self-watering system atau penyiraman otomatis dan mandiri. Agar teknologi SW lebih dikenal oleh masyarakat, maka proses diseminasi teknologi harus terus dilakukan sebagai media untuk mengenalkan berbagai fitur dan keunggulan. Penelitian ini dilakukan secara virtual (webinar daring). Untuk menjaring peserta yang lebih banyak, poster terkait informasi webinar disebarkan di berbagai media online. Selanjutnya, kuisioner evaluasi disebarkan untuk mengukur indeks keberhasilan dengan memberikan skala penilaian antara 1 – 5. Semakin tinggi nilai skala, maka kegiatan webinar dinilai semakin berhasil. Berdasarkan analisis, jumlah peserta yang hadir dalam webinar adalah 35 orang, yang mana ini didominasi oleh mahasiswa (39%), disusul dengan profesi karyawan (11%), dan pengusaha, dokter, ibu rumah tangga masing-masing dengan persentase yang sama, yaitu 3%. Dalam hal usia, kegiatan webinar ini dihadiri oleh beragam usia mulai dari 17 – 44 tahun. Berdasarkan evaluasi, kegiatan webinar teknologi SW dinilai baik dengan skala 3,66 sampai 4,14. Artinya, para peserta merasa puas telah mengikuti webinar, dapat memahami penjelasan yang dibawakan oleh pemateri, dan memiliki minat untuk menerapkan hidroponik. Pada akhirnya, webinar ini diharapkan dapat memberikan pengetahuan kepada masyarakat terkait penerapan teknologi hidroponik yang sesuai dengan kebutuhan.
Karakteristik Emisi Akustik untuk Mendeteksi Rayap Tanah pada Kayu Muhammad Achirul Nanda; Kudang Boro Seminar; Dodi Nandika
Jurnal Keteknikan Pertanian Vol. 5 No. 3 (2017): JURNAL KETEKNIKAN PERTANIAN
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1356.309 KB) | DOI: 10.19028/jtep.05.3.227-234

Abstract

AbstractVarious methods for detecting termites in the wood have been developed, one of those was based on acoustic emission. Eventhough, that method was difficult to distinguish the signal generated by termites or interference noise from the environment. It could be solved through a combination of acoustic emission and behavior of termites. Therefore, the purposes of this study were to analyze the acoustic signal and the moisture content to classify infested and uninfested wood by termites. The wood used in this study were made from Pinus logs, in air dried condition, which measure of 20(l) x 9.5(w) x 2.5(h) cm. Five wood were infested by 220 of C. curvignathus (‘infested wood’), the others were in sound condition (‘uninfested wood’). The acoustic signal was analyzed by FFT (Fast Fourier Transform) to transform from the time domain into the frequency domain. The results showed that moisture content of infested wood (11.94±0.792%) was higher than uninfested board (10.82±0.525%). Whereas the results of the acoustic signal indicated that the value of zero moment power of infested wood as well as uninfested wood, i.e., 13.405±3.019 and 9.573±2.188 respectively. Finally, the parameters which able to classify infested and uninfested wood by termites significantly were moisture content and the zero moment power.AbstrakBerbagai metode untuk mendeteksi rayap di dalam kayu telah dikembangkan, salah satunya adalah berbasis emisi akustik. Namun, metode tersebut kesulitan untuk membedakan sinyal yang diakibatkan oleh rayap atau pengaruh gangguan dari lingkungan. Hal tersebut dapat diatasi dengan mengkombinasikan emisi akustik dengan perilaku rayap. Tujuan dari penelitian ini adalah untuk menganalisis sinyal emisi akustik dan kadar air untuk mengklasifikasikan kayu yang terserang oleh rayap dan tidak terserang oleh rayap. Kayu yang digunakan pada penelitian ini dibuat dari kayu pinus, pada kondisi kering dengan ukuran 20 (p) x 9.5 (l) x 2.5 (t) cm. Lima kayu terserang sebanyak 220 rayap C. Curvignathus (‘kayu terserang’), kayu lain dalam keadaan baik (‘kayu normal’). Hasil menunjukkan bahwa kadar air dari kayu terserang oleh rayap (11.94±0.792%) lebih tinggi dibandingkan kayu normal (10.82±0.525%). Sedangkan hasil dari sinyal akustik menunjukkan bahwa nilai zero moment power pada kayu terserang oleh rayap dan kayu normal secara berurutan adalah 13.405±3.019 dan 9.573±2.188. Selanjutnya, parameter yang mampu untuk mengklasifikasikan kayu yang terserang oleh rayap dan kayu normal secara signifikan adalah parameter kadar air dan zero moment power
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

Abstract

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.
Shannon entropy on near-infrared spectroscopy for nondestructively determining water content in oil palm Inna Novianty; Walidatush Sholihah; Gema Parasti Mindara; Muhammad Iqbal Nurulhaq; Anifatul Faricha; Rismen Sinambela; Pradeka Brilyan Purwandoko; Muhammad Achirul Nanda
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5397-5405

Abstract

Indonesia is the world’s largest producer of palm oil. To preserve its competitive advantages, the Indonesian oil palm sector must expand high-quality palm oil output. In oil palm quality control, the water content is a crucial parameter as it can be used as a reference to determine the right harvest time. Thus, this study proposed a near-infrared (NIR) spectroscopy as a fast and non-destructive analysis to assess oil palm water content. NIR spectra were processed using Shannon entropy to describe the characteristics at each wavelength. In this study, oil palm fruit samples at various maturity levels were collected with eight different maturity fractions. Based on the analysis, the Shannon entropy value is closely related to any changes in the water content of palm oil. The entropy value has a decreasing trend as the water content increases. The proposed technique can predict the water content of an oil palm with satisfactory performance with values of 0.9746 of coefficient of determination (R2) and 2,487 of root mean square error (RMSE). Application of this model will lead to a fast and accurate prediction system related to oil palm water content.
Co-Authors Anifatul Faricha Anifatul Faricha anifatul faricha Christopher Andreas Djoko Purwanto Dodi Nandika Gema Parasti Mindara Ilma Amira Rahmayanti Indasyah, Enny Inna Novianty Kharistya Amaru Kudang Boro Seminar M. Rivai Mardhiana, Hawwin Muhammad Falahudin Malich Salaz Muhammad Iqbal Nurulhaq Ni'matut Tamimah Ni'matut Tamimah Pradeka Brilyan Purwandoko Qurrotun 'Ayun Mawadatur Rohmah Rika Susanti Rismen Sinambela Rizki Anhar R.P. Robin Addwiyansyah Alvaro Samrat Sholihah, Walidatush Siti Maghfirotul Ulyah Siti Maghfirotul Ulyah Sophia Dwiratna Nur Perwitasari Suwito Suwito Ulfah Abqari