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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Applied Information, Communication and Technology (JAICT) Prosiding Konferensi Nasional PKM-CSR Jurnal Nasional Teknik Elektro dan Teknologi Informasi Tematik
Sri Heranurweni
Universitas Semarang
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Nursing Public Health Social Sciences

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Kelompok Ternak Bioenergi Di Dukuh Wunut, Desa Tangkisan, Kec.Bayan Kab. Purworejo Jawa Tengah Iswoyo Iswoyo; Harmini Harmini; Sri Heranurweni
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 2 (2019): Peran Perguruan Tinggi dan Dunia Usaha dalam Mempersiapkan Masyarakat Menghadapi Era I
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.213 KB) | DOI: 10.37695/pkmcsr.v2i0.490

Abstract

Kelompok ternak Bina Lestari terletak di Dukuh Wunut Desa Tangkisan Bayan Purworejo yang terdiri dari 12 Kepala Keluarga dan mempunyai kandang dua tingkat dengan jumlah sapi 18 ekor. Saat ini telah terbangun satu unit biodigester dengan ukuran 8 m3 oleh kelompok ternak sapi Bina Lestari. Biodigester tersebut saat ini hanya dapat dimanfaatkan untuk 7 KK. Berdasarkan hal tersebut perlu dilakukan pengembangan untuk membangun biodigester agar warga yang belum mendapatkan supply biogas dapat teratasi. Permasalahan prioritas yang dihadapi mitra dalam segi sosial, mutu layanan dan kehidupan bermasyarakat adalah masih ada 5 kepala keluarga (KK) yang belum mendapatkan supply biogas untuk memasak sehingga kelima KK masih mengkonsumsi LPG tabung 3 Kg dan juga masih menggunakan kayu bakar. Limbah biodigester dapat dimanfaatkan untuk diolah menjadi pupuk. Solusi yang ditawarkan untuk menyelesaikan permasalahan mitra adalah membangun biodigester tambahan dengan kapasitas 12 m3. Kapasitas tersebut dapat digunakan untuk 12 KK. Limbah dari biodigester diolah menjadi pupuk. Hasil dari pengabdian ini adalah telah terbangunnya biodigester dengan kapasitas 12 m3 untuk kelompok ternak Bina Lestari Dukuh Wunut Desa Tangkisan Bayan, Purworejo. Sejumlah 12 KK telah dapat memanfaatkan bioenergi tersebut. limbah dari bioenergi dimanfaatkan sebagai pupuk yaitu pupuk cair dan pupuk padat yang digunakan untuk memupuk lahan pertanian
VEGETABLE TYPE CLASSIFICATION USING NAIVE BAYES ALGORITHM BASED ON IMAGE PROCESSING Hanny Nurrani; Andi Kurniawan Nugroho; Sri Heranurweni; Eko Supriyanto; Generousdi -
JAICT Vol 7, No 2 (2022)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v7i2.3762

Abstract

There are so many different varieties of vegetables in Indonesia that the sorting procedure presents difficulties. In an effort to expedite the introduction of smart farming in Indonesia, more agricultural assistance techniques will be created. Utilizing the Naive Bayes algorithm is one way that may be used to advance agriculture in Indonesia. Image processing consists of converting RGB images to grayscale images, segmenting images using the thresholding method, collecting image features based on the HSV average value and object area, and classifying pictures using the Naive Bayes algorithm. This research seeks to use image processing technologies to agricultural products, particularly vegetables. The system is comprised of a single picture captured by a digital camera. There were eight varieties of vegetables employed for the picture data, with a total of eighty consisting of 64 training data and 16 test data. Spinach, green chilies, red chilies, chayote, cucumber, eggplant, tomatoes, and carrots were the vegetables categorized. The categorization findings indicate that 87.5 % of the test values produced using this approach are accurate. This study demonstrates that the Naive Bayes method has a high degree of accuracy for the categorization of vegetables based on image processing. It is anticipated that the findings of this study would promote the implementation of smart farming 4.0 in Indonesia.
Image Classification of Vegetable Quality using Support Vector Machine based on Convolutional Neural Network Hanny Nurrani; Andi Kurniawan Nugroho; Sri Heranurweni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4715

Abstract

As part of an effort to develop intelligent agriculture, new methods for enhancing the quality of vegetables are being continually developed. In recent years, the Convolutional Neural Network (CNN) has shown to be the most successful and extensively used approach for identifying the quality of pre-trained vegetables. However, this method is time-consuming due to the scarcity of truly large, significant datasets. Using a pre-trained CNN model as a feature extractor is a straightforward method for utilizing CNNs' capabilities without investing time in training. While, Support Vector Machine (SVM excels at processing data with tiny dimensions and significantly larger instances. SVM more accurately classifies the flatten/vector feature supplied by the CNN fully connected layer with small dimensions. In addition, implementing Data Augmentation (DA) and Weighted Class (WC) for data variety and class imbalance reduction can improve CNN-SVM performance. The research results show highest accuracy during training always achieves 100% across all experimental options. With an average accuracy of 69.66% in the testing process and 92.51% in the prediction process for all data, the experimental findings demonstrate that CNN-SVM outperforms CNN in terms of accuracy performance in all possible experiments, with or without WC and or DA approach.
PELATIHAN MIKROKONTROLLER ARM Cortex-M0 NUVUTON BAGI SISWA SMPN 23 KOTA SEMARANG Sri Heranurweni; Budiani Destyningtias
TEMATIK Vol 3, No 1 (2021): Juni (2021)
Publisher : TEMATIK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/tmt.v3i1.3519

Abstract

Mikrokontroler AVR merupakan salah satu jenis arsitektur mikrokontroler yang menjadi andalan Atmel. Arsitektur ini dirancang memiliki berbagai kelebihan dan merupakan penyempurnaan dari arsitektur mikrokontroler- mikrokontroler yang sudah ada. Semakin berkembangnya teknologi terutama di bidang kendali dan kurangnya pemahaman siswa SMPN 23 Semarang dalam bidang mikrokontroler menjadikan alasan untuk diadakannya pelatihan Mikrokontroler ARM Cortex MO Nuvuton di kota Semarang. Pelatihan ini sudah terlaksana pada hari Selasa 5 Januari 2021 sevara daring dengan menggunakan oom meeting diikuti oleh peserta 4 siswa.
Analisa Kinerja Multiple Input Multiple Output Jaringan Sensor Nirkabel dengan Demodulasi Terdistribusi Ari Endang Jayati; Sri Heranurweni; M. Sipan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 3 No 4: November 2014
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (180.384 KB)

Abstract

Wireless Sensor Network has some weaknesses, such as limited power, memory and communication. Sensor is supplied with a very limited power batery. Besides, Wireless Sensor Network should also consider the available bandwidth, range sensor and sensor communication range. The main objective of this study is to analyze the performance of linear demodulation named Zero Forcing (ZF) and Minimum Mean Squared Error (MMSE) in wireless sensor network using Multiple Input and Multiple Output (MIMO) system with Signal to Noise Ratio (SNR) and Bit Error Rate (BER) as the parameter to measure the performance of endurance to noise. The application of ZF and MMSE linear demodulation with MIMO configuration to Wireless Sensor Network is constantly good, the performance of ZF to reach BER 10-3 needed SNR 21 dB, while the performance of MMSE to reach BER 10-3 needed SNR 18 dB.
Co-Authors Andi Kurniawan Ari Endang Jayati Budiani Destyningtias Eko Supriyanto Generousdi - Hanny Nurrani Harmini Harmini Iswoyo Iswoyo M. Sipan