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All Journal POSITRON Jurnal Neutrino : jurnal fisika dan aplikasinya Bulletin of Electrical Engineering and Informatics Jurnal Spektra JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Unnes Science Education Journal JPPPF (Jurnal Penelitian dan Pengembangan Pendidikan Fisika) Spektra: Jurnal Fisika dan Aplikasinya JURNAL METEOROLOGI DAN GEOFISIKA Sarwahita : Jurnal Pengabdian Kepada Masyarakat Risenologi Parameter PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Mitra Teras: Jurnal Terapan Pengabdian Masyarakat
Widyaningrum Indrasari
Department Of Physics, Faculty Of Mathematics And Natural Sciences, Universitas Negeri Jakarta, Jakarta 13220
Aerospace Engineering Humanities Chemistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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KARAKTERISASI SENSOR HY-SRF05 DAN LOAD CELL SINGLE-POINT SEBAGAI PARAMETER PENGUKURAN ANTROPOMETRI PADA SISTEM PEMANTAUAN STATUS GIZI BAYI Halimah, Nova Nur; Umiatin, Umiatin; Indrasari, Widyaningrum
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA10

Abstract

Abstrak Status gizi merupakan ukuran keberhasilan status kesehatan yang dihasilkan oleh keseimbangan antara kebutuhan dengan masukan nutrisi. Salah satu indikator dalam penentuan status gizi bayi dapat dilihat melalui pengukuran antropometri. Parameter utama dalam pengukuran antropometri pada bayi adalah massa badan dan panjang badan. Perkembangan sistem antropometri yang akurat dapat membantu upaya dalam proses modernisasi di bidang kesehatan. Pada sistem pengukuran antropometri diperlukan beberapa sensor untuk memenuhi indikator dalam penentuan status gizi bayi, yaitu sensor HY-SRF05 sebagai pendeteksi panjang badan dan sensor load cell single-point sebagai pendeteksi massa badan. Penelitian ini bertujuan untuk mengetahui rentang kerja, sensitivitas, tingkat akurasi, serta resolusi pada tiap sensor. Oleh karena itu, dilakukan dengan mengkarakterisasi sensor HY-SRF05 dan sensor load cell single-point menggunakan Raspberry Pi sebagai sistem kendali. Karakterisasi dilakukan dengan membandingkan nilai keluaran sensor dengan alat ukur konvensional. Hasil karakterisasi menunjukkan bahwa sensor HY-SRF05 dapat bekerja dengan baik pada rentang 30 cm-75 cm dengan kesalahan relatif sebesar 0.16%. Sedangkan untuk sensor load cell single-point dapat bekerja dengan baik pada rentang 1500 gram-12700 gram dengan kesalahan relatif sebesar 0.08%. Berdasarkan hasil karakterisasi yang telah didapatkan dapat disimpulkan bahwa sensor HY-SRF05 dan load cell single-point dapat digunakan sebagai parameter pengukuran antropometri pada sistem pemantauan status gizi bayi. Kata-kata kunci: antropometri, HY-SRF05, raspberry pi, sensor load cell single-point, status gizi. Abstract Nutritional status is a measure of the success of health status resulting from a balance between nutritional needs and inputs. One indicator in determining the nutritional status of infants can be seen through anthropometric measurements. The main parameters in anthropometric measurements in infants are body mass and body length. The development of an accurate anthropometric system can assist efforts in the process of modernization in the health sector. In the anthropometric measurement system, several sensors are needed to meet the indicators in determining the nutritional status of infants, namely the HY-SRF05 sensor as a body length detector and a single-point load cell sensor as a body mass detector. This study aims to determine the working range, sensitivity, level of accuracy, and resolution of each sensor. Therefore, it was carried out by characterizing the HY-SRF05 sensor and single-point load cell sensor using the Raspberry Pi as the control system. Characterization is done by comparing the output value of the sensor with conventional measuring instruments. The characterization results show that the HY-SRF05 sensor can work well in the range of 30 cm-75 cm with a relative error of 0.16%. As for the single-point load cell sensor, it can work well in the range of 1500 grams-12700 grams with a relative error of 0.08%. Based on the characterization results that have been obtained, it can be concluded that the HY-SRF05 sensor and single-point load cell can be used as anthropometric measurement parameters in the infant nutritional status monitoring system. Keywords: anthropometry, HY-SRF05, raspberry pi, single-point load cell sensor, nutritional status.
KARAKTERISASI DAN PENGUJIAN SENSOR MQ-4 DAN MG-811 UNTUK PENGEMBANGAN SISTEM MONITORING KONSENTRASI GAS METANA DAN KARBON DIOKSIDA DI UDARA Ramadhani, I Gusti Ayu Isnaini Fatha; Indrasari, Widyaningrum; Suhendar, Haris; Marpaung, Mangasi Alion
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA12

Abstract

Abstrak Seiring dengan perkembangan zaman, berbagai kegiatan indrustrialisasi dan urbanisasi dapat memicu peningkatan gas CH4 dan CO2 yang dapat memperburuk kualitas udara di lingkungan. Salah satu upaya untuk mengetahui kualitas udara adalah dengan melakukan monitoring konsentrasi gas di udara. Konsentrasi gas CH4 di udara dapat diukur menggunakan sensor MQ-4 sedangkan gas CO2 diukur menggunakan sensor MG-811. Dalam penggunaannya, perlu dilakukan karakterisasi sensor dan pengujian sensor dengan tujuan untuk mendapatkan persamaan kalibrasi, kesalahan relatif pengukuran, dan rentang kerja dari masing-masing sensor. Maka pada penelitian ini dilakukan proses karakterisasi sensor dengan membandingkan hasil keluaran sensor MQ-4 dengan CH4 Analyzer G2203 dan sensor MG-811 dengan CO2 Analyzer G2301 Picarro. Adapun hasil karakterisasi menunjukkan bahwa sensor MQ-4 memiliki kesalahan relatif rata-rata sebesar 0,066%. Sedangkan sensor MG-811 memiliki kesalahan relatif rata-rata sebesar 0,047%. Sedangkan pengujian sensor dilakukan dengan melakukan pengukuran sampel berupa asap kendaraan bermotor menggunakan variasi waktu. Adapun hasil pengujian menunjukkan bahwa sensor MQ-4 dapat bekerja dengan baik dalam rentang 1,885-1,914 PPM, sedangkan sensor MG-811 dapat bekerja dengan baik dalam rentang 406,311-409,169 PPM. Hasil tersebut selanjutnya akan digunakan dalam pengembangan sistem monitoring konsentrasi gas CH4 dan CO2 di udara. Kata-kata kunci: metana, karbon dioksida, MQ-4, MG-811, konsentrasi gas. Abstract Along with times, various industrialization and urbanization activities can trigger an increase in CH4 and CO2 gases which can improve air quality in environment. One effort to determine air quality is to monitor gas concentrations in air. Concentration of CH4 gas in air can be measured using MQ-4 sensor and CO2 gas is measured using MG-811 sensor. In use, it is necessary to characterize sensors and test sensors with aim of obtaining measured equations, relative measurement errors, and working distance of each sensor. So, in this research sensor characterization process was carried out by comparing output results of MQ-4 sensor with CH4 Analyzer G2203 and MG-811 sensor with CO2 Analyzer G2301 Picarro. Characterization results show that MQ-4 sensor has an average relative error of 0,066% and MG-811 sensor has an average relative error of 0,047%. While sensor testing is done by measuring samples in form of motorized vehicle smoke using time variations. The sensor testing results show that The MQ-4 sensor can work well in range of 1,885-1,914 PPM, while MG-811 sensor can work well in range of 406,311-409,169 PPM. These results will then be used in development of a monitoring system for CH4 and CO2 gases concentrations in air. Keywords: methane, carbon dioxide, MQ-4, MG-811, gas concentration.
KARAKTERISASI DAN PENGUJIAN SENSOR MQ-7 DAN MQ-136 UNTUK PENGEMBANGAN SISTEM MONITORING KONSENTRASI GAS KARBON MONOKSIDA (CO) DAN SULFUR DIOKSIDA (SO2) Muqita, Saffanah Ghina; Indrasari, Widyaningrum; Suhendar, Haris; Marpaung, Mangasi Alion
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA13

Abstract

Abstrak Jenis gas polutan yang banyak dihasilkan dari kegiatan transportasi dan industri adalah CO dan SO2. Apabila gas tersebut berada dalam konsentrasi tinggi, maka akan memicu terjadinya pencemaran udara. Oleh sebab itu, dibutuhkan sistem monitoring konsentrasi gas dengan memanfaatkan sensor MQ-7 untuk mengukur konsentrasi gas CO dan sensor MQ-136 untuk mengukur konsentrasi gas SO2. Untuk menghasilkan pengukuran yang akurat, sensor tersebut perlu dilakukan karakterisasi dan pengujian dengan tujuan untuk mendapatkan persamaan kalibrasi, kesalahan relatif pengukuran dan rentang kerja dari masing-masing sensor. Maka dari itu pada penelitian ini dilakukan proses karakterisasi sensor dengan membandingkan hasil keluaran sensor MQ-7 dengan CO Analyzer CO-30r Los Gatoss dan sensor MQ-136 dengan SO2 Analyzer Model 43i-TLE Thermo. Hasil karakterisasi menunjukkan bahwa sensor MQ-7 memiliki kesalahan relatif pengukuran sebesar 0,286%, sedangkan sensor MQ-136 memiliki kesalahan relatif rata-rata sebesar 0,280%. Adapun pengujian sensor dilakukan dengan mengukur sampel berupa asap kendaraan bermotor menggunakan variasi waktu. Hasil pengujian menunjukkan bahwa sensor MQ-7 dapat bekerja dengan baik dalam rentang 4,36 – 4,68 PPM, sedangkan sensor MQ-136 dapat bekerja dengan baik dalam rentang 0,00387 – 0,00419 PPM. Hasil tersebut selanjutnya akan digunakan dalam pengembangan sistem monitoring konsentrasi gas CO dan SO2 di udara. Kata-kata kunci: karbon monoksida, sulfur dioksida, MQ-7, MQ-136, konsentrasi gas. Abstract Types of pollutant gases that are mostly produced from transportation and industrial activities are CO and SO2. If these gases are in high concentrations, it will trigger air pollution. Therefore, a gas concentration monitoring system is needed by utilizing MQ-7 sensor to measure CO gas concentration and MQ-136 sensor to measure SO2 gas concentration. To produce accurate measurements, these sensors need to be characterized and tested with the aim of obtaining calibration equations, relative measurement errors and working ranges of each sensor. Therefore, in this study, the sensor characterization process was carried out by comparing output of MQ-7 sensor with CO Analyzer CO-30r Los Gatoss and MQ-136 sensor with SO2 Analyzer Model 43i-TLE Thermo. The characterization results show that MQ-7 sensor has a relative measurement error of 0,286%, while MQ-136 sensor has has a relative measurement error of 0,280%. The sensor testing was carried out by measuring samples in the form of motor vehicle smoke using time variations. The test results show that MQ-7 sensor can work well in range of 4,36 – 4,68 PPM, while MQ-136 sensor can work well in range of 0,00387 – 0,00419 PPM. These results will then be used in the development of a monitoring system for CO and SO2 gas concentrations in the air. Keywords: carbon monoxide, sulfur dioxide, MQ-7, MQ-136, gas concentration.
KARAKTERISASI SENSOR PIEZOELEKTRIK LDT0-028K UNTUK PERANCANGAN SISTEM PENGUKURAN GETARAN PADA MESIN Dewi, Ratna Komala; Indrasari, Widyaningrum; Firmansyah, Heri
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA14

Abstract

Abstrak Getaran pada mesin biasanya tidak dapat dicegah atau dihindari. Getaran yang semakin besar dan tidak dimonitoring akan menyebabkan kemungkinan terjadinya kerusakan fatal pada mesin. Pada penelitian ini dilakukan perancangan sistem pengukuran getaran pada mesin menggunakan sensor piezoelektrik LDT0-028K. Dalam penggunaannya, sensor perlu dilakukan karakterisasi sebelum digunakan. Tujuan karakterisasi sensor piezoelektrik LDT0-028K yaitu untuk mengetahui keakuratan nilai frekuensi yang terukur oleh sensor. Dalam proses karakterisasi digunakan kalibrator sebagai penghasil getaran dengan frekuensi yang dapat dikontrol. Metode yang digunakan dalam mengkarakterisasi sensor piezoelektrik LDT0-028K yaitu dengan cara membandingkan hasil pengukuran sensor dengan alat standar Tachometer. Berdasarkan hasil uji coba, sensor piezoelektrik LDT0-028K memiliki kesalahan relatif pengukuran rata-rata sebesar 0,67% dan dapat bekerja dengan baik pada rentang frekuensi 13,53 Hz sampai dengan 59,57 Hz. Selanjutnya, sensor akan digunakan untuk pengembangan sistem pengukuran dan monitoring getaran pada mesin berbasis IoT (Internet of Things). Kata-kata kunci: sensor piezoelektrik, getaran mesin, monitoring mesin, karakterisasi sensor. Abstract Vibration in engines usually cannot be prevented or avoided. Vibrations that are getting bigger and not monitored will cause the possibility of fatal damage to the machine. In this research, a vibration measurement system was designed on a machine using a piezoelectric sensor LDT0-028K. In use, the sensor needs to be characterized before use. The purpose of characterizing the LDT0-028K piezoelectric sensor is to determine the accuracy of the frequency value measured by the sensor. In the characterization process, a calibrator is used as a vibration generator with controllable frequency. The method used in characterizing the LDT0-028K piezoelectric sensor is by comparing the measurement results of the sensor with a standard tachometer. Based on the test results, the LDT0-028K piezoelectric sensor has an average relative measurement error of 0.67% and can work well in the frequency range of 13.53 Hz to 59.57 Hz. Furthermore, the sensor will be used for the development of a vibration measurement and monitoring system on IoT (Internet of Things) based machines. Keywords: piezoelectric sensors, machine vibration, machine monitoring, sensor characterization.
KARAKTERISASI ESP32 CAMERA DAN SENSOR SUHU MLX90614-DCI PADA SISTEM PENGENDALI PINTU OTOMATIS Muthiah, Alya; Indrasari, Widyaningrum; Firmansyah, Heri
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA15

Abstract

Abstrak Salah satu langkah yang dapat dilakukan untuk meminimalisir kecelakaan kerja yaitu menerapkan sistem keamanan pada pintu masuk wilayah kerja. Sistem keamanan yang umum digunakan adalah teknologi biometrik dengan wajah sebagai parameternya. Selain itu, pada kondisi pasca pandemi COVID-19, sistem keamanan juga ditunjang dengan proses pengecekan suhu tubuh. Pada penelitian ini dilakukan proses karakterisasi ESP32 Camera untuk mendeteksi biometrik wajah dan sensor MLX90614-DCI untuk pengecekan suhu tubuh menggunakan mikrokontroler Arduino UNO. Proses karakterisasi ESP32 Camera bertujuan untuk menentukan rentang jarak dan posisi wajah yang dapat dideteksi modul kamera. Selain itu, dilakukan juga karakterisasi sensor MLX90614-DCI dengan cara membandingkan hasil keluaran sensor suhu dengan alat ukur standar berupa thermogun. Proses tersebut bertujuan untuk mengetahui jarak optimal dan keakuratan dari sensor. Berdasarkan hasil karakterisasi, rentang jarak deteksi ESP32 Camera adalah 5 hingga 20 cm dimana kamera dapat mengenali wajah apabila posisi bagian wajah yang terlihat sebesar 90% hingga 100%. Sedangkan, hasil karakterisasi sensor MLX90614-DCI menunjukkan bahwa jarak optimal pengukuran sensor adalah 14 cm. Pada jarak tersebut, pengukuran suhu dengan rentang 35°C hingga 41°C menghasilkan rata-rata kesalahan relatif sebesar 0.15%. Data hasil karakterisasi ini akan digunakan dalam pengembangan sistem pengendali pintu otomatis berdasarkan pengenalan wajah dan suhu tubuh. Kata-kata kunci: biometrik, ESP32 camera, suhu tubuh, sensor MLX90614-DCI, karakterisasi. Abstract One of the steps that can be taken to minimize work accidents is to implement a security system at the entrance to the work area. The commonly used security system is biometric technology with face as its parameter. In addition, in post-COVID-19 pandemic conditions, the security system is also supported by the process of checking body temperature. In this research, the ESP32 Camera characterization process is carried out to detect facial biometrics and the MLX90614-DCI sensor for checking body temperature using an Arduino UNO microcontroller. The ESP32 Camera characterization process aims to determine the range of distances and face positions that can be detected by the camera module. In addition, the characterization of the MLX90614-DCI sensor is also carried out by comparing the output results of the temperature sensor with a standard measuring instrument, a thermogun. The process aims to determine the optimal distance and accuracy of the sensor. Based on the characterization results, the ESP32 Camera detection distance range is 5 to 20 cm where the camera can recognize faces if the position of the visible part of the face is 90% to 100%. Meanwhile, the MLX90614-DCI sensor characterization results show that the optimal distance for sensor measurement is 14 cm. At 14 cm, temperature measurements with a range of 35°C to 41°C produce an average relative error of 0.15%. This characterization data will be used in the development of an automatic door control system based on face recognition and body temperature. Keywords: biometric, ESP32 camera, body temperature, MLX90614-DCI sensor, characterization.
KARAKTERISASI SENSOR KAMERA TERMAL AMG8833 UNTUK PERANCANGAN SISTEM PENGUKURAN TEMPERATUR PADA MESIN Achmadi, Ridho; Indrasari, Widyaningrum; Firmansyah, Heri
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA17

Abstract

Abstrak Monitoring temperatur pada mesin dapat digunakan untuk pencegahan kondisi overheating. Untuk melakukan monitoring temperatur mesin, dibutuhkan suatu sistem pengukuran temperatur. Pada penelitian ini, dilakukan perancangan sistem pengukuran temperatur pada mesin menggunakan sensor kamera termal AMG8833. Namun dalam penggunaanya, setiap sensor harus dikarakterisasi terlebih dahulu sebelum digunakan. Tujuan karakterisasi pada sensor kamera termal AMG8833 agar dapat diketahui jarak pengukuran optimal, rentang kerja, dan keakuratan dalam pengukuran temperatur. Metode yang digunakan dalam mengkarakterisasi sensor kamera termal AMG8833 yaitu membandingkan langsung nilai yang terbaca pada sensor dengan nilai yang terbaca pada termogun industri. Hasil pengukuran jarak optimal menunjukan bahwa sensor mampu bekerja optimal pada jarak 3 cm. Sedangkan hasil uji coba sensor pada rentang 32,50˚C hingga 65,70˚C memiliki rata-rata error relatif pengukuran sebesar 0,12%. Selanjutnya, sensor akan digunakan dalam pengembangan sistem pengukuran dan monitoring temperatur pada mesin. Kata-kata kunci: monitoring, temperatur mesin, kamera termal, karakterisasi sensor AMG8833. Abstract Monitoring the temperature of the engine can be used to prevent overheating. To monitor engine temperature, a temperature measurement system is needed. In this study, a temperature measurement system was designed on the engine using the AMG8833 thermal camera sensor. However, in its use, each sensor must be characterized before being used. The purpose of characterization of the AMG8833 thermal camera sensor is to find out the optimal measurement distance, working range, and accuracy in temperature measurement. The method used in characterizing the AMG8833 thermal camera sensor is to directly compare the value read on the sensor with the value read on an industrial thermometer. The optimal distance measurement results show that the sensor is able to work optimally at a distance of 3 cm. While the results of the sensor trials in the range of 32.50˚C to 65.70˚C have an average relative measurement error of 0.12%. Furthermore, the sensor will be used in the development of a temperature measurement and monitoring system on the engine. Keywords: monitoring, machine temperature, thermal camera, AMG8833 sensor characterization.
ANALISIS MODEL PREDIKSI CUACA MENGGUNAKAN SUPPORT VECTOR MACHINE, GRADIENT BOOSTING, RANDOM FOREST, DAN DECISION TREE Risanti, Risanti; Indrasari, Widyaningrum; Suhendar, Haris
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA18

Abstract

Abstrak Machine learning dapat diaplikasikan untuk melakukan prediksi terhadap suatu data. Salah satu data yang berkaitan dengan fenomena alam yang terdokumentasi dengan baik dan dapat diakses dengan mudah adalah data kondisi cuaca. Dalam penelitian ini digunakan data kondisi cuaca untuk melakukan pengembangan model machine learning dan prediksi keadaan cuaca. Data yang digunakan terdiri dari pengukuran suhu udara, kelembaban udara, dan kecepatan angin menggunakan data BMKG Provinsi Jawa yang bersifat open source dengan selang waktu 3 jam tahun 2020 dari bulan Januari - Desember. Tujuan penelitian ini adalah untuk mendapatkan nilai akurasi, presisi, F1 score, dan recall serta membandingkan fitur yang memberikan pengaruh paling besar terhadap hasil prediksi cuaca. Model yang digunakan dalam penelitian ini adalah support vector machine, gradient boosting, random forest, dan decision tree. Perbandingan antara data training dan data test adalah 70:30. Hasil penelitian menunjukan bahwa hasil akurasi model support vector machine, gradient boosting, random forest, decision tree masing-masing sebesar 0.1697; 0.6696; 0.7918; 0.8416; 0.8280. Pada hasil terlihat bahwa random forest memiliki pengaruh paling besar terhadap hasil prediksi cuaca dengan dengan hasil akurasi 0.8416. Kata-kata kunci: Prediksi, Cuaca, SVM, Gradient Boosting, Random Forest, Decision Tree. Abstract Machine learning can be applied to make predictions on a given dataset. One well-documented and easily accessible dataset related to natural phenomena is weather condition data. In this study, weather condition data is used to develop machine learning models and predict weather conditions. The data used consists of air temperature, air humidity, and wind speed measurements obtained from the BMKG (Meteorology, Climatology, and Geophysics Agency) of the Jawa Province, which are open source and collected at 3-hour intervals throughout the year 2020 from January to December. The aim of this research is to obtain accuracy, precision, F1 score, and recall values and compare the features that have the most significant influence on weather prediction outcomes. The models used in this study are support vector machine, gradient boosting, random forest, and decision tree. The data is divided into a 70% training set and a 30% test set. The research results show that the accuracy values for, support vector machine, gradient boosting, random forest, and decision tree models are 0.1697, 0.6696, 0.7918, 0.8416, and 0.8280, respectively. It can be observed that random forest has the greatest influence on weather prediction outcomes, with an accuracy value of 0.8416. Keywords: Prediction, Weather, SVM, Gradient Boosting, Random Forest, Decision Tree.
PENGEMBANGAN SISTEM PEMANTAUAN STATUS GIZI BALITA TERINTEGRASI ALAT ANTROPOMETRI BERBASIS RASBERRY PI Umiatin, Umiatin; Halimah, Nova Nur; Indrasari, Widyaningrum
PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) Vol. 12 (2024): PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) SNF2023
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1201.FA20

Abstract

Abstrak Masa balita (bawah lima tahun) atau masa golden age merupakan masa yang penting untuk memonitoring status gizi balita. Keseimbangan antara kebutuhan dan asupan gizi balita harus terpenuhi agar tidak mengganggu perkembangan dan pertumbuhan balita. Pemantauan status gizi balita dapat dilakukan setiap bulan di Posyandu dengan mengukur berat badan, panjang / tinggi badan, lingkar kepala dan lingkar lengan atas balita. Selanjutnya hasil pengukuran berat badan dan tinggi badan akan diplot secara manual pada Kartu Menuju Sehat (KMS), kemudian dianalisis kurva pertumbuhannya. Namun, metode konvensional ini kurang efisien. Oleh karena itu dalam penelitian ini telah dikembangkan sistem pemantauan status gizi balita secara otomatis guna meningkatkan akurasi serta efisiensi dalam pemantauan status gizi balita. Dalam penelitian ini digunakan sensor load cell single point untuk pengukuran berat badan, sensor ultrasonik HY-SRF05 untuk pengukuran tinggi/panjang badan, Raspberry pi sebagai sistem kendali serta database SQLite. Hasil penelitian menunjukkan bahwa tingkat kesalahan relatif sensor HY-SRF05 sebesar 0.33%, sensor load cell single point sebesar 0.368%. Pada penelitian ini juga berhasil dilakukan pengintegrasian sistem pengukuran dengan database SQLite untuk mengelola kompleksitas data pada sistem pemantauan status gizi bayi Kata Kunci: status gizi balita, raspberry pi, sensor load cell, sensor ultrasonik, SQLite. Abstract The toddler phase (under five years) or golden age is a crucial period for monitoring the nutritional status of toddlers. It is essential to balance the nutritional intake and needs of toddlers to ensure proper development and growth. Nutritional status monitoring for toddlers can be conducted monthly at Posyandu by measuring weight, length/height, head circumference, and upper arm circumference. The results are then manually plotted on the Kartu Menuju Sehat (KMS) and analyzed for growth curves. However, this conventional method is inefficient. Therefore, this study developed an automated system for monitoring the nutritional status of toddlers to enhance accuracy and efficiency. The study employed a single-point load cell sensor to measure weight, an HY-SRF05 ultrasonic sensor for measuring length/height, a Raspberry Pi as the control system, and an SQLite database. The results showed that the relative error rate for the HY-SRF05 sensor was 0.33%, and for the single-point load cell sensor, it was 0.368%. Additionally, the study successfully integrated the measurement system with an SQLite database to manage data complexity in monitoring the nutritional status of toddlers. Keywords: toddler nutritional status, Raspberry Pi, load cell sensor, ultrasonic sensor, SQLite.
Internet of Things-Based Real-Time Thermal Monitoring: Utilizing the Affordable MLX90640 Thermal Camera and the Industrial MAX6675 Thermocouple Module with a Linear Regression Characterization Method Firmansyah, Heri; Indrasari, Widyaningrum
POSITRON Vol 15, No 1 (2025): Vol. 15 No. 1 Edition
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Univetsitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/positron.v15i1.89878

Abstract

Thermal monitoring is essential for preventive maintenance to ensure that electrical and mechanical devices operate safely within their optimal temperature range. This research developed a temperature monitoring system comprising an MLX90640 thermal camera and four type-K thermocouples, all integrated with the MAX6675 module and connected to the Internet of Things (IoT) system. The characterization of the temperature sensors uses an industrial thermogun to determine their ideal distance and accuracy with the linear regression method. The optimal distance for the thermal camera from the heat source is 15 cm, but the proper distance for the type-K thermocouple sensor at the MAX6675 module is direct contact with the heat source surface. The evaluation of the monitoring system involved assessing the temperature of two distinct items within a temperature spectrum, ranging from 36 °C to 48 °C and from 36 °C to 96 °C. The data from the array sensor system indicate a high degree of accuracy in relative sensor measurements, exhibiting few mistakes. The sensor's relative measurement error was relatively small: 1.29% for thermal camera MLX90640, 1.83% for thermocouple 1, 0.9% for thermocouple 2, 1.04% for thermocouple 3, and 1.9% for thermocouple 4. The advance of this IoT-integrated monitoring system is developed using the MING Stack environment (MQTT, InfluxDB, Node-RED, and Grafana), a popular collection of open-source technologies used for Industrial Internet of Things (IIoT) applications. The results indicate that the system can efficiently monitor temperature; the dashboard provides real-time insights and historical data analysis, allowing users to make informed decisions regarding temperature management.
Mapping Active Lava Flows from the 2022 Mauna Loa Eruption Using NOAA-20 and S-NPP Satellite Data Ramayanti, Suci; Lee, Chang-Wook; Iryanti, Mimin; Indrasari, Widyaningrum; Hamidah, Ida; Hasanah, Lilik
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 14 No 1 (2025): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v14i1.26753

Abstract

The development of satellite data has played an important role in monitoring natural disasters on the Earth's surface. Providing an overview of the current conditions of a volcanic crisis, including information on lava flow extension, is a challenge in observing volcanoes. Various methods were used to map lava flows, such as identifying lava on optical satellite images and detecting thermal anomalies emitted by hot lava. This study aimed to generate a preliminary map of active lava flow caused by the 2022 Mauna Loa eruption in near real-time by analyzing fire radiative power (FRP) data acquired from Suomi National Polar-orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration-20 (NOAA-20) satellites. FRP data was filtered to identify lava flow using statistically determined thresholds from its value distribution, including the 5th percentile, 3rd quartile, mean, and 95th percentile. The obtained active lava flow map is evaluated using confusion matrix analysis by comparing the estimated map with the reference map. The maps generated using various thresholds were compared, and the best result was provided by the threshold of the 3rd quartile, with S-NPP and NOAA-20 FRP threshold values of 27.2 and 27.9 MW/pixel, respectively, with overall accuracy reaching 97%. The higher threshold reduced the overestimated lava location represented by a false positive (FP) value. The results show that the active lava originated from the summit caldera, and the eruptive fissure on the northeast flank extended to the northeastern area with an estimated daily distance reaching about 18 km from a certain reference point. This preliminary lava flow map can provide general information regarding areas prone to lava flows, especially around Mauna Loa, and support related parties in updating hazard zones rapidly. The findings should help make immediate decisions for evacuation routes and public warnings when an eruption occurs without visiting the volcanic area directly.
Co-Authors A. Handjoko Permana Achmad Fadhlih Saldy Saputra Achmad Samsudin Achmadi, Ridho Adindya Giovanni Afifah Trie Lestari Agus Setyo Budi Ahmad Aminudin Ahmad Zatnika Purwalaksana Aisah Anggiyansah Sitompul Ariyanti, Shallu Fidhah Axel Nathanael Bahagia, Marthin Virgo Bambang Heru Iswanto Bambang. H. Iswanto Budi Mulyanti Cecep E. Rustana Cecep E.Rustana Chayani Sarumaha Dadan Sumardani Dadang Wihana Danang Trihatmoko, Danang Desriyan Lestari Destiana Rachmawati Dewanti, Kunti Dewi Muliyati Dias Prima Fadilla Dila Sabila Dina Ramadhini Rinaldy Donna Rajagukguk Eka Pawinanto, Roer Erfan Handoko Esmar Budi Esmar Budi Esmar Budi Esmar Budi Fadilla, Dias Prima Fathir Fajar Sidiq Fathul Arifin Fauzi Bakri Febrianti, Yana Feby Dwitri Putri Ferdy Alfian Indra Prasetya Fitri Sakinah Ghina Muqita, Saffanah Habiburosid Hadi Nasbey Halimah, Nova Nur Hani Harjayanti Hani Harjayanti Hansel Muhammad Falah Haris Suhendar Heri Firmansyah Heri Firmasyah Hermanta, Catur Anthony Hersaputra, Nugraha I Made Astra Ida Hamidah Iip Wahyuni Inggrid Ayu Putri Isnaini, I Gusti Ayu Iwan Setiawan Iwan Sugihartono Jumril Yunas, Jumril Juniastel Rajagukguk Khan, Shak Rhuk Lee, Chang-Wook Leni Andayani Lestari, Intan Rachmawati Lilik Hasanah Lutvi Vitria Kadarwati Mangasi Alion Marpaung Martalia Andayani Melia Vivi Ningrum Mimin Iryanti Mitra Djamal Mitra Djamal Muhammad Yusuf Muqita, Saffanah Ghina Muthiah, Alya Nadya Hidayatie Novita Fitriani Nurul Fitri, An Nisa Nuvus, Afiva Riyatun Pintor Simamora Putri, Feby Dwitri Rafiudin, Rafiudin Raharjo Raharjo Rahmondia N. Setiadi Rahmondia Nanda Rahmondia Nanda Rahmondia Nanda Setiadi Rama, Gusti Ramadhani, I Gusti Ayu Isnaini Fatha Ramayanti, Suci Ramdhan, Muhammad Rofiid Rappel Situmorang RATNA KOMALA DEWI Rifqi Md Zain, Ahmad Risanti, Risanti Riser Fahdiran Riski Amelia, Riski Sabila, Dila Sahari, Siti Kudnie Saldy Saputra, Achmad Fadhlih Setyo Nugroho, Harbi Shak Rhuk Khan Siswoyo Siswoyo Siti Chaerijah Aurijah SUBEKTI, FAJAR Sugandi, Gandi Supriyadi, Rizky Tsaniya Mukarromah Umiatin, Umiatin Valendio Febriano Wahyu Dwi Meilianto Wahyuni, Iip Wisnu Satria Budi Wulandari, Chandra Yasnita Yasnita Yetti Supriyati, Yetti Yolanda Natasya Mega Stella Yulkifli Yulkifli Zannuraini Zannuraini Zulfiah Ayu Kurnia Sari Zulfikar Zulfikar Zulmi, Febrian