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All Journal Komunikasi Fisika Indonesia Journal of Aceh Physics Society Jurnal Edu Research Jurnal Penelitian Sains JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Teori dan Aplikasi Fisika Jurnal Kewarganegaraan

Minarni Minarni

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Author-ID : 546471

Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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ANALISA SENSITIVITAS SENSOR TGS PADA HIDUNG ELEKTRONIK UNTUK IDENTIFIKASI GANODERMA DI BAGIAN AKAR KELAPA SAWIT Mhd Feri Desfri; Minarni Minarni; Dewi Laila Sari; Dewi Anjarwati Mahmudah; Ihsan Okta Harmailil; Irfan Cahyadi
Komunikasi Fisika Indonesia Vol 19, No 1 (2022)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.19.1.1-6

Palm oil is one of the main commodities for Indonesia. It is important to identify the disease-causing the decline in productivity. Root rot disease that causes total damage to oil palm plants due to fungal infection G. boninense sp has volatile organic compounds that can be detected using an electronic nose. The electronic nose system is designed with 6 sensor arrays, namely TGS 2612, TGS 822, TGS 2611, TGS 2610, TGS 813, and TGS 2620 which are sensitive to certain VOC compounds. The sample used was infected and uninfected oil palm seedlings aged 4 months. The detection process is carried out on plant roots. Python program is used as a data acquisition system in voltage retrieval. The obtained voltage is processed and further analyzed using a trapezoidal area to determine the sensor response in the identification of Ganoderma. The results of processing using a trapezoidal plane show that TGS 2611 has a very good response. The TGS 2611 sensor has a higher trapezoidal area in identifying oil palm plants that are attacked by Ganoderma with 4 classifications, namely healthy, moderate, sick, and severe.

PEMBUATAN ALAT LABORATORIUM UNTUK PRAKTIKUM OPTIK GEOMETRI TINGKAT SMA BERBASIS LASER DIODA Alexander Nasution; Minarni Minarni; Rakhmawati Farma; Sinta Afria Ningsih
Komunikasi Fisika Indonesia Vol 18, No 2 (2021)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.18.2.137-145

Peningkatan literasi sains siswa Indonesia membutuhkan metode pembelajaran yang standar, salah satunya mengunakan metode pembelajaran dengan alat demo atau alat laboratorium. Namun penyediaan alat tersebut oleh sekolah belum optimal karena pendanaan yang kurang. pelajaran Fisika tingkat SMA khususnya kelas X atau XI membahas tentang optik geometri. Kit alat optik geometri yang ekonomis diperlukan untuk menunjang hasil belajar siswa pada materi tesebut. Penelitian ini bertujuan untuk membuat kit optik geometri yang ekonomis dan sederhana berbasis laser untuk percobaan optik geometri. Kit tersebut yang terdiri dari laser dioda dengan panjang gelombang 650 nm dan daya 5 mW, tangki pembiasan akrilik, skala sudut berbentuk melingkar. Percobaan yang dilakukan adalah pengunaan Hukum Snelius pada medium udara-air, menentukan indek bias cairan, dan sudut kritis. Pada penelitian ini, modul percobaan digunakan pada siswa MAN 1 Padang Lawas, Kecamatan Barumun, Sumatera Utara. Beberapa uji yang dilakukan yaitu uji kelayakan alat, uji praktikalita kit optik geometri, dan uji efektifitas penggunaan Kit Terhadap Hasil Belajar Siswa Kelas X. Hasil rata-rata semua aspek uji kelayakan menghasilkan skor 96,25%. Hasil uji praktikalitas adalah 85,00 %. Untuk uji efektifitas penggunaan kit adanya perbedaan hasil pre-test dan post-test pada kelas eksperimen dan kelas kontrol dimana pada kelas eksperimen rata-rata nilai siswa dari 32,83 pada saat pre-test menjadi 73 setelah post-test, sementara hasil pre-test kelas kontrol dari rata-rata 31,83 menjadi 68 setelah dilakukan post-test

IMPLEMENTASI JARINGAN SYARAF TIRUAN (JST) DAN PENGOLAHAN CITRA UNTUK KlASIFIKASI KEMATANGAN TBS KELAPA SAWIT Minarni Minarni; Roni Salumbae; Zilhan Hasbi
Komunikasi Fisika Indonesia Vol 15, No 1 (2018)
Publisher : Universitas Riau

The clasification of ripeness stages of oil palm fresh fruit bunches (FFBs) can be done using color parameters. These parameters are often evaluated by human vision, whose degree of accuracy is subjective which can cause doubt in judgement. Automatic clasifications offreshfruit bunches (FFBs) based on color parameters can be done using computer vision. This method is known as a nondestructive, fast and cost effective method. In this research, a MATLAB computer program has been developed which consists of RGB and HSV GUI which is used to record, display, and process FFB image data. The backpropagation artificial neural network (ANN) program is also developed which is used to classify the oil palm fruit fresh bunches (FFBs). Samples are fresh fruit bunches (FFB) of oil palm varieties of Tenera which comprise of Topaz, Marihat, and Lonsum clones. Each clone composed of three levels of ripeness represented by five fractions. The measurements were started by capturing images of oil palm, extracting RGB and HSV values, calculating weight values from the image database to make anANN program, preparing grid programs for oil palm FFBs, and comparing grading levels of oil palm FFBs using program and by harvester. This program successfully classified oil palm (FFBs) into three categories of ripeness which are unripe (F0 and F1), ripe (F1 and F1) and over ripe (F4 and F5). The RGB and HSV programs successfully classified 79 out of 216 FFBs or 36.57% and 106 out of 216 TBS or 49.07%. Respectively the HSV program is better than RGB program because the representation of HSV color space are more understood by human perception hence can be used in calibration and color comparison.

ANALISA CITRA HIPERSPEKTRAL DAUN DARI TANAMAN KELAPA SAWIT YANG MENGALAMI KEKURANGAN AIR MENGGUNAKAN PROGRAM MATLAB JR Lessy Eka Putri; Minarni Minarni; Feri Candra; Herman Herman
Komunikasi Fisika Indonesia Vol 16, No 2 (2019)
Publisher : Universitas Riau

The hyperspectral imaging method has been widely and intensively used in agriculture to find out various problems that occur in plants. Image processing is very important step in an imaging method. This research aims to create Matlab based program to be used to analyze the leaf image of oil palm plants that has experienced water deficiency. Reflectance intensity values were extracted from the process. The hyperspectral imaging system consisted of a 650 nm diode laser, a spectrograph, monochrome CMOS camera, and Matlab image processing program. The samplesused were 8 month old Tenera variety of oil palm seedlings which were treated to simulate water deficiency in the form of variations in the volume of water, namely 0 mL (without watering), 1000 mL, 2000 mL, and 3000 mL (normal), 3 duplicates for each volume. The samples were given water volume of 1000 mL and 2000 mL for every 7 days in 21 days, while the sampleswith 3000 mL of water were watered every day. Image recording was done on the 21st day for detached leaves at the the bottom part.The results showed that the Matlab program was able to separate each row from 15 images, each of which had a pixel size of 1280 × 1024 and merge each of the same lines into 1024 images with a pixel size of 1280 × 15. The reflectance intensity values were then obtained. The results showed that higher levels of water deficiency in plants produce increasing reflectance intensity values.

APLIKASI PROGRAM MATLAB UNTUK ANALISA CITRA HYPERSPECTRAL PADA AKAR DARI TANAMAN KELAPA SAWIT YANG MENGALAMI KEKURANGAN AIR Mailestari Wina Yance; Minarni Minarni; Feri Candra; Herman Herman
Komunikasi Fisika Indonesia Vol 16, No 2 (2019)
Publisher : Universitas Riau

Hyperspectral images are three dimensional images which have two dimension spatial information and one dimension spectral information. Hyperspectral image processing using Matlab program is preferable because it is more adaptive for many analysis purposes. This research was aimed to construct Matlab to process and analyze the hyperspectral images of the roots of oil palm plants that have experienced water deficiency. The program was designed and constructed using a GUI . The use of a GUI aims to combine each pixel of the same line from each sample to produce a new image. The samples were roots of oil palm plants that experienced simulated water deficiency by giving different water volumes of 0 mL, 1000 mL, 2000 mL and 3000 mL (normal). The optical method used in this study is a hyperspectral imaging method which has 650 nm diode laser as the light source , spectrograph Specim Imspector V10 , and a monochrome CMOS as a detector. Reflectance intensity versus wavelength was extracted from each images and analyzed. The results showed that the Matlab GUI program that had been constructed was able to produce 1024 new images that had a pixel size of 15× 1280 from each sample. The results also show that the reflectance intensity values are higher at higher water deficiency of the oil palm roots.

PENGUNAAN PENCITRAAN MULTISPEKTRAL PADA PANJANG GELOMBANG 520 NM DAN 800 NM UNTUK MENGEVALUASI TINGKAT KEMATANGAN TBS KELAPA SAWIT Sinta Afria Ningsih; Minarni Shiddiq; Dodi Sofyan Arief; Ikhsan Rahman Husein
Komunikasi Fisika Indonesia Vol 17, No 3 (2020)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.17.3.144-149

Oil palm fresh fruit brunch (FFB) are the main source of crude palm oil (CPO). Sorting and grading FFB are important in order to obtain high quality CPO. Multispecral imaging has been purposed to be implemented in high speed sorting machines due to less wavelength bandwidths used hence less processing time. This study was aimed to evaluate the ripeness levels of oil palm FFB based on relative reflectance intensity and fruit firmness. Multispectral images were acquired using two bandpass filters mounted in a filter wheel with wavelengths of 520 nm and 800 nm respectively. The image acquisition and processing were controlled using python based program. The samples consisted of 30 oil palm FFBs of Tenera varieties with three ripeness levels as unripe, ripe, and overripe. The result showed that the relatif reflectance intensity at wavelength of 520 nm is inversely proportional to the maturity level, on the other hand, relatif reflectance intensity at wavelength of 800 nm is directly proportional to the maturity level. The relation between the firmness and ripeness level are inversely proportional. Relative reflectance intensity of the multispectral images at the wavelength of 800 nm had a better correlation to the palm fruit firmness than the image at the wavelength of 520 nm with the correlation coefficient (r) of -0.0198 at 520 nm and -0.8594 at 800 nm. it can be shown that the multispectral imaging is potensial to be implemented for FFB ripeness evaluation.

ANALISIS PENGARUH SUHU TERHADAP SENSITIVITAS SENSOR PADA HIDUNG ELEKTRONIK UNTUK KEMATANGAN BUAH KELAPA SAWIT Minarni Shiddiq; Dian Eka Rachmawati
Komunikasi Fisika Indonesia Vol 19, No 2 (2022)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.19.2.57-64

Electronic noses have been developed for decades in many fields. Recently, electronic nose has been used in agriculture to detect the ripeness of fruits because fruits also produce volatile gas during ripening. Oil palm fresh fruit bunches (FFB) is the main source of crude palm oil, its quality depends on the ripeness levels of oil palm FFB. Therefore, electronic detections of oil palm FFB ripeness need to be developed. This study was aimed to investigate the effect of temperature variation on the sensitivity of gas sensors in an electronic nose designed for detecting the ripeness of oil palm FFB. The electronic nose used in this study consisted of 4 sensors which were TGS 2611, TGS 2620, TGS 813 and TGS 822. Samples were peeled fruitlets of ripe oil palm FFB which were heated to temperatures of 30°C, 45°C, and 60°C. Response of each sensor was represented as a trapezoid area of voltage versus time for convenience. The results showed that there was a significant difference in the output voltage of each sensor when the sample temperatures were varied. Fruitlets of oil palm FFB heated at 60°C resulted in higher trapezoid area which mean more volatile gas released. Based on the resulted trapezoid area for each sensor. Sensors of TGS 2611 and TGS 822 are the most sensitive which have higher trapezoid area for the variation of the temperatures.

ANOTASI CITRA BERBASIS PYTHON UNTUK RANCANG BANGUN PERANGKAT LUNAK DETEKSI OBJEK PADA TANDAN BUAH SEGAR KELAPA SAWIT CACAT Minarni Shiddiq; Muhammad Ikhsan Hamid; Vicky Vernando Dasta; Yohanes Dwi Saputra; Dewi Anjarwati Mahmudah; Dinda Kamia Evkha Putri; Annisya Madani; Ihsan Okta Harmailil
Indonesian Physics Communication Vol 20, No 2 (2023)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.20.2.135-140

Object detection can determine the existence of an object, scope and image. Object detection begins with the introduction of an object. This method can be used to automate the process of sorting and grading oil palm fresh fruit bunches (FFB) at palm oil mills, which are still done manually. Image annotations are needed in building the software so that the software can identify object features in an image, especially imager in video frames. This study aims to annotate images of oil palm FFB into 2 categories, namely normal palm and abnormal palm. This category is the standard regulation of the Minister of Agriculture No. 14 of 2013. Image acquisition is carried out by varying the position of each oil palm FFB with the top and bottom position of the fruit which is then augmented 4 times which function to multiply the image data model to be annotated. Annotation is done using the python program application, namely Labelimg. The amount of image data that has been annotated is 200 images consisting of 100 normal palm images and 100 abnormal palm images.

Classification of maturity levels of oil palm fresh fruit bunches using LED-based multispectral imaging methods and principal component analysis Mohammad Fisal Rabin; Minarni Shiddiq; Rahmondia Nanda Setiadi; Ihsan Okta Harmailil; Ramdani Ramdani; Dedi Permana
Indonesian Physics Communication Vol 21, No 1 (2024)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.21.1.91-98

Multispectral imaging (MSI) is one of the optical methods used for the classification of fruits and vegetables based on ripeness levels. MSI is simpler than hyperspectral imaging due to fewer wavelength bands used hence less processing time. In this study, MSI is used to classify the ripeness of oil palm fresh fruit bunch (FFB). The MSI system consists of three main components, namely a VIS-NIR camera, a camera lens, an LED array, and a current control unit. The use of the LED array as a light source in the MSI system aims to minimize the use of bandwidth filters. The LEDs used are arranged in a circular pattern with 8 wavelengths, namely 680, 700, 750, 780, 810, 850, 880, and 900 nm. FFB samples were recorded using the MSI system and then processed using Python language to obtain relative reflectance intensity values. The purposes of this research are to analyze the relationship between relative reflectance intensity and wavelength and to classify the ripeness level of oil palm FFB using principal component analysis (PCA). We used two categories of ripeness, unripe and ripe FFBs.The results of the PCA analysis showed that the classification carried out was able to group into two levels of ripenesses with a total variant percentage value for PC1 and PC2 of 90.95%.

Co-Authors Alexander Nasution Annisa Fadillah Annisa Fadlillah Annisya Madani Aswandi Bahar Daeng Ayub Dedi Permana Dewi Anjarwati Mahmudah Dewi Laila Sari Dian Eka Rachmawati Dina Veranita Dinda Kamia Evkha Putri Dodi Sofyan Arief, Dodi Sofyan Feri Candra Hefniati Ishak Herman Herman Ihsan Okta Harmailil Ihsan Okta Harmailil Ikhsan Raahaman Husein Ikhsan Rahman Husein Irfan Cahyadi JR Lessy Eka Putri Lentina Br Sitohang Mailestari Wina Yance Maksi Ginting Mhd Feri Desfri Mohammad Fisal Rabin Mohammad Fisal Rabin Muhammad Ikhsan Hamid Nadia Zakyyah Yasmin Nadia Zakyyah Yasmin Nurmaya Sari Purnama - Rahmondia Nanda Setiadi Rakhmawati Farma Ramdani Ramdani Ramma Hayu Fitra Ramma Hayu Fitra Reza Umami Ria Fitriani Roni Salumbae Saktioto Saktioto Sinta Afria Ningsih Sri Hermonica Titi Maemunaty Tomy Suherly Tri Handoko Vicky Vernando Dasta Walfred Tambuhan Yohanes Dwi Saputra Zilhan Hasbi

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