Arif Budianto

High-quality water resources are important parameters for the sustainability of human civilization, the health of ecosystems, and the advancement of vital sectors. High-quality water is also needed for shrimp cultivation ponds. However, water-quality monitoring in the estuary is limited. In line with this, this study focuses on the design and implementation of an IoT-based TDS and temperature measurement system for estuarine water, aiming to develop an efficient, accurate, and automated prototype to support the fisheries sector in West Lombok regency. This study used a microcontroller, temperature and TDS (total dissolved solids) sensors, a wireless router, and a display. These elements were developed as a water-quality-level monitoring system based on TDS and temperature. The system was calibrated using a standard comparator before being examined under real conditions. The calibration procedure was conducted inside a controlled chamber at a water temperature of 25°C for 60 minutes, with a steady flow rate. All procedures were repeated three times and tested using a Student’s t-test. The IoT platform was tested using RSSI values with a 2s update interval. The calibration data were interpreted as a linear function between the standard and the developed system. The resulting design shows that the developed system can be installed at a shrimp cultivation pond with good performance. The designed system has a linearity of more than 90%. The system has a reliable accuracy level over 30 consecutive measurement days, resulting in the percentages of 85% to 93% (average = 91%). It can be concluded that IoT data communication via a wireless internet router performs well, with RSSI> -50 dBm for both sending and receiving. The IoT platform using ThingSpeak shows good performance (good stability), with a 2-second interval between data updates.

Emisi udara merupakan salah satu isu penting yang dapat berdampak secara langsung bagi kesehatan masyarakat. Semakin besar sumber emisi, semakin besar pula potensi paparan emisi yang dihasilkan. Permasalahan ini juga dihadapi oleh warga (mitra) di lingkungan Pesona Banyu Asri, Banyumulek, Kabupaten Lombok Barat. Polusi udara yang dihasilkan dari banyak penjuru (empat sumber utama) di area sekitaran mitra (pengelolaan sampah di TPA Kebon Kongok, pemrosesan limbah plastik di BRIDA, pemrosesan sanpah menjadi biofuel, dan proses produksi gerabah di desa wisata Banyumulek) cukup tinggi, namun proses kuantifikasi dan karakterisasi emisi belum dilaksanakan/ dikaji secara detail. Oleh sebab itu, tujuan dari pengabdian kepada masyarakat ini adalah untuk memberikan solusi alternatif yang dapat memberikan peningkatan akan kesiapsiagaan warga terkait mitigasi kebencanaan emisi udara. Metode pelaksanaan kegiatan pengabdian kepada masyarakat difokuskan pada teknik PAR (participatory action research) terhadap peningkatan aspek sosial kemasyarakatan. Prioritas yang dilakukan adalah identifikasi permasalahan dan pemberian solusi alternatif terkait dampak paparan emisi udara akibat aktivitas sumber emisi di sekitar area mitra. Sistem manajemen udara berbasis IoT (Internet of Things) yang telah dikembangkan oleh tim pengabdian sebelumnya diimplementasikan secara langsung ke masyarakat, melalui tahapan observasi, sosialisasi, pelatihan, instalasi, dan penilaian akhir. Hasil proses pengabdian dapat ditunjukkan dari proses kuantifikasi data kuisioner, di mana terdapat peningkatan yang cukup signifikan antara sebelum dan sesudah kegiatan pengabdian. Kesiapsiagaan masyarakat mitra meningkat 62% terkait kemampuan pemahaman mitigasi udara, baik dari segi pemahaman jenis-jenis emisi udara, sistem purifikasi udara, hingga operasional sistem manajemen udara berbasis IoT yang bermanfaat bagi mitra.

VOCs (volatile organic compounds) can be used as a biomarker of placebo phenomenon, such as stress, panic disorder, health conditions, and many others. VOCs from the exhaled breath have different concentration levels that are also related to many health diseases. However, the use of VOCs as biomarkers in exhaled breath are very limited. Hence, this study aims to develop a novel e-nose (electric nose) system based on a VOC measurement system to identify placebo phenomenon in emission areas. For this purpose, a digital semiconductor VOC sensor and a microcontroller were used to detect VOC level. The developed system was tested inside a chamber for the initial calibration and comparation steps using fresh air and a comparator device. After calibration, the system was used to measure the VOC concentrations of 20 exhaled breath samples in the emission sampling areas (control and emission sources). In other sides, the VOC levels surrounding the emission areas were also measured using the comparator device. The placebo levels (PLS) of the exhaled breath samples were divided into PLS(-) or placebo negative and PLS(+) or placebo positive related to the placebo conditions. The sampling areas were divided into indoor and outdoor areas to identify the different placebo percentages and the dependence related to the emission levels. The results show that the emission levels of the emission sources are about 504-528 ppb, meanwhile, the control area (clean area) has 78 ppb of VOC levels, while PLS(-) samples has < 78 ppb of VOC levels (p < 0.05). It can be concluded that VOC concentrations in the emission sources has a potential to influence the placebo quantification in human psycological health. The developed e-nose system can be used to identify VOC levels as a biomarker of a placebo phenomenon.

Penderita asma menghembuskan gas sisa pernapasan yang mengandung berbagai macam gas dan senyawa, seperti gas nitrogen, gas karbon dioksida, senyawa aldehida, dan masih banyak lagi. Keberadaan gas dan senyawa dapat dijadikan sebagai biomarker dalam tahap preliminary study terkait teknologi electric nose (e-nose). Di sisi lain, pengembangan teknologi e-nose untuk identifikasi konsentrasi senyawa aldehida pada udara pernapasan secara umum dan pada asma secara khusus belum banyak dilakukan. Sejalan dengan hal tersebut, penelitian ini bertujuan untuk mengembangkan teknologi e-nose berbasis sensor MS-1100 guna menganalisis konsentrasi gas senyawa aldehida (formaldehida) yang terkandung di dalam hembusan nafas manusia, secara khusus pada penderita asma dan orang sehat. Penelitian ini menggunakan e-nose berbasis sensor MS-1100. Sensor tersebut dihubungkan dengan sebuah mikrokontroller dan analog to digital converter yang memiliki resolusi sebesar 10 bit pada pin analog. E-nose dikalibrasi menggunakan udara terfilter di dalam chamber dan dikarakterisasi dengan beberapa varian gas (formaldehida, karbon monoksida, hidrogen sulfida, dan etanol). Setelah dikalibrasi, pengujian sampel nafas manusia dilakukan dengan melibatkan sampel 20 penderita asma dan 20 orang sehat. Selanjutnya, dilakukan uji Student’s t-test untuk melihat perbedaan konsentrasi gas antara penderita asma dengan orang sehat. Hasil pengujian menunjukkan bahwa e-nose terkalibrasi dan memiliki selektivitas dan sensitivitas tertinggi pada senyawa aldehida (formaldehida) dengan tingkat 0,96 Volt/ppm formaldehida dibandingkan pendeteksian ketiga gas lainnya. Terdapat perbedaan yang signifikan pada konsentrasi senyawa aldehida antar penderita asma sebesar (1,15-1,30 ppm) dan orang sehat berkisar antara (0,17-0,89 ppm) dengan nilai (p < 0,05). Tingkat akurasi e-nose dalam mendeteksi senyawa aldehida pada hembusan nafas manusia mencapai ~90%. Hasil tersebut menyimpulkan bahwa E-nose berbasis sensor MS-1100 dapat digunakan untuk mengidentifikasi konsentrasi aldehida pada pernapasan penderita asma dengan orang sehat secara akurat. E-nose ini dapat digunakan sebagai analisator biomarker senyawa aldehida non-invasif penderita asma dan orang non-asma.

Gas karbon dioksida adalah salah satu jenis emisi udara yang dapat berasal dari berbagai sistem pembakaran. Gas karbon dioksida juga dapat dihasilkan dari hembusan udara sisa pernapasan manusia. Hal yang menarik adalah indikasi hubungan antara perubahan metabolisme tubuh dengan konsentrasi karbon dioksida yang dihembuskan oleh sistem pernapasan manusia. Di sisi lain, terdapat limitasi perkembangan teknologi di bidang pendeteksian konsentrasi gas karbon dioksida di dalam udara pernapasan sebagai biomarker akan keberadaan kondisi psikologi tertentu, seperti pada kasus plasebo (placebo effect). Oleh sebab itu, penelitian ini memiliki tujuan untuk mengidentifikasi hubungan antara tingkat atau besar konsentrasi emisi udara jenis CO2 dengan persentase kasus plasebo di masyarakat yang berada di daerah emisi. Penelitian dilakukan terhadap 90 sampel nafas di tiga sumber emisi yang berbeda, yakni E1, E2, dan E3. Kondisi plasebo diklasifikasikan menjadi tiga jenis, yakni PLS(-), PLS(+)P, dan PLS(+)N dengan kondisi psikologi yang berbeda-beda. Hasil penelitian menunjukkan bahwa sistem pengukuran konsentrasi gas karbon dioksida berbasis sensor MG-811 dapat digunakan untuk mengidentifikasi hubungan antara besar konsentrasi emisi terhadap persentase plasebo. Ketiga daerah sumber emisi menghasilkan emisi CO2 dengan konsentrasi yang bervariasi, yaitu berkisar 740 ppm hingga 790 ppm yang jauh lebih tinggi dibandingkan konsentrasi kontrol (< 405 ppm). Sejalan dengan hal ini diperoleh tingkat persentase plasebo yaitu PLS(+)N. Hasil tersebut meyimpulkan bahwa semakin tinggi konsentrasi emisi, maka semakin tinggi persentase kejadian plasebo (PLS(+)N). Semakin rendah tingkat konsentrasi emisi CO2, maka semakin rendah persentase plasebo di masyarakat yang menjadi sampel.

Evolusi keadaan kuantum pada foton di dalam sistem optik linier memiliki aplikasi yang beragam, mulai dari eksperimen kuantum optik mendasar hingga tingkat lanjut untuk pemrosesan informasi kuantum. Penelitian ini bertujuan untuk menyusun algoritma simulasi yang berfokus pada pemodelan elemen optik sebagai salah satu cara untuk mempelajari perilaku keadaan kuantum pada foton. Implementasi perhitungan komputasi kuantum dengan optik linier telah dikembangkan sebagai bagian dari simulasi dalam penelitian ini. Konfigurasi jaringan kuantum dilakukan dengan memodelkan komponen optik, seperti pembagi sinar, pemindah fase, dan hubungan antar komponennya melalui sejumlah wakilan matriks. Hasil pengukuran dinyatakan dalam distribusi kebolehjadian, dengan mempertimbangkan efek elemen optik yang dilewati oleh foton. Simulasi ini mampu melakukan perhitungan untuk jaringan kuantum dasar dengan keadaan kuantum awal tertentu. Melalui simulasi ini, kita dapat mendefinisikan jaringan kuantum dan mengimplementasikan algoritma kuantum melalui cara yang intuitif dengan menggunakan instruksi sederhana.

Formaldehyde is a kind of air pollutant with strong volatility at room temperature. Formaldehyde is emitted from many sources, such as furnishing, building sect

Liver diseases have been linked to ambient emission exposure, especially fine (FP) and ultrafine particles (UFP). At the same time, the influence of specific emission sources is needed due to the increase in the number of emission sources. In this study, we evaluated the influence of motorcycle FP and UFP emission on mice livers. Motorcycles emission was selected due to the number of motorcycles that were reported to increase significantly, especially in developed countries. The emission was also chosen because no one had yet evaluated the influence of motorcycle FP and UFP exposure on the liver. In order to fill this gap, we evaluated the impact of motorcycle FP and UFP on mice. The mice were grouped into the control and experiment groups. The mice from the experimental groups were exposed to motorcycle FP and UFP particles in different exposure doses: C1 (20 s), C2 (40 s), C3 (60 s), C4 (80 s), and C5 (100 s). All of the exposure were conducted twice a day for eight consecutive days. On the last day, all mice were sacrificed, while the Kupffer cells were observed under a digital microscope. In the results, we found that the exposure doses strongly influenced the number of Kupffer cells (R2>0.9) with increased exposure doses. The influence of exposure day was also substantial but not as significant as the exposure doses (R2>0.8). Furthermore, the Kupffer cells number was raised logarithmically for the exposure doses or exposure day increases. The inflammation was also increased with the Kupffer cell number increase. We observed that the increased exposure dose increases the population with higher inflammation scores. The destructive liver index was raised with increased exposure doses and exposure days. In conclusion, motorcycle FP and UFP exposure significantly impact Kupffer cell activation, liver inflammation, and damage to mice’s liver. However, an evaluation of another source of particles, e.g., gasoline or diesel-fueled vehicles, are needed to find the characteristic of each source of emissions.

This study aimed to investigate the association between DEPs (diesel exhaust particulate matter) exposure and emphysematous lung. There were three buses used as diesel particulate matter sources. DEPs were classified into ultrafine, fine, and coarse particles with different aerodynamic diameters. This study used mice that were divided into control and treatment groups. The treated mice were exposed to the DEPs in different concentrations (low, mid, and high doses) for eight consecutive days. The control group did not receive any exposure treatment, while the exposed mice were sacrificed on the ninth day to get the lung samples. The lung samples were observed under a digital microscope to identify the normal and deformed alveolar cells. According to the observation results, the emphysematous level increased linearly to the DEPs dose concentration. The emphysematous level was found in the range of 64-80%, depending on the exposure dose concentration. In summary, direct exposure to the DEPs was correlated to the emphysematous level. This study has given a novel explanation of the bus exhaust emission risk as a heavy-duty vehicle in organs, especially due to the ultrafine, fine, and coarse particles exposures.

Emissions from burning biomass have become a problem in Indonesia. As found on the Indonesian island of Lombok, agricultural waste is burned for traditional industrial activities. On the other hand, biomass burning emissions contain many PMs (particulates) in different size distributions recognized to have a significant correlation to health impact. This study is conducted to predict the impact of the PM exposure on blood using a ANN (artificial neural network) model as well as a histological examination. The relationship between both methods is determined to estimate the impact of biomass burning emissions on the blood. This study used male mice as the experimental animals exposed to PM emissions (PM0.1, PM2.5, and PM10 ) produced from the burning of various biomass (rice straw, rice husks, corn cobs, corn stalks, and tobacco) taken from Lombok Island. The sample exposure was conducted in a chamber for 100 s for ten sequence days. The blood samples were observed using a microscope with the 400 x magnification. The cell deformation was examined histologically by calculating the normal and abnormal cells. The percentage of the erythrocyte deformation was assessed using a fixed back and forth propagation ANN. The result shows that the biomass burning PM emissions have a significant impact on the erythrocyte deformation depending on the type of biomass and the particulate matter emissions. The ANN model confirms the erythrocyte deformation data obtained by the histological examination method.