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All Journal Proceedings of KNASTIK CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JISA (Jurnal Informatika dan Sains) Instrumentasi International Journal of Research in Community Services International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research
Prihastuti Harsani
Universitas Pakuan
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Transportation Other

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Aplikasi Diagnosis Penyakit Sapi Menggunakan Metode Certainty Factors Berbasis Android Rahman, Indra Fauzi; Harsani, Prihastuti; Qurania, Arie
KOMPUTASI Vol 13, No 2 (2016): JURNAL KOMPUTASI
Publisher : KOMPUTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.641 KB)

Abstract

Sejak tahun 1950 perkembangan aplikasi dengan basis sistem pakar sangat diminati. Untuk mempersingkat waktu dalam mengambil keputusan diperlukan sistem pakar. Bisnis peternakan sangat menjanjikan, akan tetapi memerlukan perhatian yang sangat tinggi terhadap adanya serangan penyakit, seperti halnya sapi yang sangat rentan terhadap berbagai penyakit. Dengan adanya aplikasi system pakar yang dapat mendiagnosa secara cepat, akurat dan tepat terhadap penyakit dini yang ditimbulkan maka diharapkan dapat membantu peternak dalam memperkecil angka kematian disebabkan oleh penyakit yang mengakibatkan kerugian. Diperlukan ketepatan dan keakuratan perhitungan dalam mendiagnosis gejala penyakit sehingga menyimpulkan hasil dengan menggunakan metode certainty factors. Metode Certainty Factors sering diterapkan dalam banyak permasalahan nyata.
SISTEM INFORMASI ON-LINE SEBAGAI MEDIA PROMOSI POTENSI “KAMPUNG WISATA HOME INDUSTRY’’ CIKARET KECAMATAN BOGOR SELATAN Tosida, Eneng Tita; Harsani, Prihastuti; Andria, ferdi
KOMPUTASI Vol 9, No 1 (2012): Komputasi
Publisher : KOMPUTASI

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Abstract

Kompepar merupakan salah satu model pemberdayaan masyarakat yang telah diterapkan di Kelurahan Cikaret Bogor Selatan dalam promosi dan pengelolaan potensi wisata, namun dalam operasionalnya belum berjalan secara optimal. Salah satu penyebabnya adalah belum tersedianya media sosialisasi dan promosi yang efektif. Oleh karena itu perlu dibangun Sistem Promosi On-Line yang mampu memberikan informasi yang interaktif mengenai potensi wisata di Cikaret, yang didukung oleh pemberdayaan kompepar kan KIM Bogor Selatan selaku pengguna sekaligus pengelola sistem on-line tersebut melalui kegiatan pelatihan penglolaan sistem. Pembangunan Sistem On-Line dilakukan dengan metode System Development Life Cycle (SDLC) dan metode pelatihan menggabungkan antara tutorial dan praktek disertai dengan evaluasi dan pendampingan yang berjenjang. Keberhasilan pemberdayaan Kompepar dan KIM Bogor Selatan dalam Upaya pengembangan potensi wisata home industri tidak akan terlepas dari sinergi antar dinas dan pihak yang terkait langsung (stakeholders), baik dalam han perbaikan infrastruktur, pembangunan fasilitas umum, maupun kebijakan yang mampu mendukung dan meningkatkan kemampuan Kompepar dalam berkreasi menciptakan kemasan paket wisata yang menarik dan mampu divisualisasikan dalam sistem on-line.
PREDIKSI CURAH HUJAN BULANAN MENGGUNAKAN TIME SERIES (SINGLE EXPONENTIAL SMOOTHING) DAN KNN (STUDI KASUS : KABUPATEN PADANG PARIAMAN) Harsani, Prihastuti; Mulyana, Iyan; Ofik Hidayat, Ade
Proceedings of KNASTIK 2012
Publisher : Duta Wacana Christian University

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Abstract

Climate is average condition for certain time period. The one of few factors influencethe climate is rainfall. This research develops a system which can predict and giveinformation of monthly rainfall prediction and also for the next few months.Climatology data from BMKG from 2000 to 2009 is need in this research. The dataconsist of seven variable which are temperature, sunlight condition, air pressure,humidity, wind speed, wind direction and evaporate. This research uses ExponentialSmoothing for rainfall prediction and K-Nearest Neighbor that need for rainfallprediction classified. The result shows that the prediction accuracy is 58, 33%.
Color Extraction and Edge Detection of Nutrient Deficiencies in Cucumber Leaves Using Artificial Neural Networks Qur'ania, Arie; Harsani, Prihastuti; Triastinurmiatiningsih, Triastinurmiatiningsih; Wulandhari, Lili Ayu; Gunawan, Alexander Agung Santoso
CommIT (Communication and Information Technology) Journal Vol 14, No 1 (2020): CommIT Vol. 14 No. 1 Tahun 2020
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.5952

Abstract

The research aims to detect the combined deficiency of two nutrients. Those are nitrogen (N) and phosphorus (P), and phosphorus and potassium (K). Here, it is referred to as nutrient deficiencies of N and P and P and K. The researchers use the characteristics of Red, Green, Blue (RGB) color and Sobel edge detection for leaf shape detection and Artificial Neural Networks (ANN) for the identification process to make the application of nutrient differentiation identification in cucumber. The data of plant images consist of 450 training data and 150 testing data. The results of identifying nutrient deficiencies in plants using backpropagation neural networks are carried out in three tests. First, using RGB color extraction and Sobel edge detection, the researchers show 65.36% accuracy. Second, using RGB color extraction, it has 70.25% accuracy. Last, with Sobel edge detection, it has 59.52% accuracy.
Color Extraction and Edge Detection of Nutrient Deficiencies in Cucumber Leaves Using Artificial Neural Networks Arie Qur'ania; Prihastuti Harsani; Triastinurmiatiningsih Triastinurmiatiningsih; Lili Ayu Wulandhari; Alexander Agung Santoso Gunawan
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.5952

Abstract

The research aims to detect the combined deficiency of two nutrients. Those are nitrogen (N) and phosphorus (P), and phosphorus and potassium (K). Here, it is referred to as nutrient deficiencies of N and P and P and K. The researchers use the characteristics of Red, Green, Blue (RGB) color and Sobel edge detection for leaf shape detection and Artificial Neural Networks (ANN) for the identification process to make the application of nutrient differentiation identification in cucumber. The data of plant images consist of 450 training data and 150 testing data. The results of identifying nutrient deficiencies in plants using backpropagation neural networks are carried out in three tests. First, using RGB color extraction and Sobel edge detection, the researchers show 65.36% accuracy. Second, using RGB color extraction, it has 70.25% accuracy. Last, with Sobel edge detection, it has 59.52% accuracy.
MEDICINAL PLANT SPECIES IDENTIFICATION SYSTEM USING TEXTURE ANALYSIS AND MEDIAN FILTER Prihastuti Harsani; Arie Qurania; Triasti nurmiatiningsih
Jurnal Ilmiah Kursor Vol 8 No 4 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i4.112

Abstract

Identification of plants can be done through objects - objects in plants by asking an expert or through a specimen (herbarium) that have been identified previously. Identification is done by matching the pictures in the book of flora or monograph. Computer-aided identification can be done using digital image processing methods which utilize digital image matching object plant with a picture on the book. Identification key that is used is the image of the leaves. This study develops previous research has identified using the method of fractal and Euclidian Distance. Accuracy obtained in each of the identification system for the fractal dimension and fractal code is of 68% and 51%. Improved accuracy is the main objective of this study. The proposed method is a method of texture analysis and median filter. Texture analysis is used as feature extraction technique while the median filter is image enhancement techniques. Based on the trials, the results of the identification of texture analysis method and median filter to increase to 78%. Median filter is used as a technique to improve the image quality leaves. The use of an identification system to be tested in the web application of information systems of medicinal plants.
Empowerment of Gunung Sari Village Community Groups, to optimize the potential of the village towards the Tourism Independent Village Prihastuti Harsani
International Journal of Quantitative Research and Modeling Vol 1, No 2 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.623 KB) | DOI: 10.46336/ijqrm.v1i2.38

Abstract

The tourism sector in Gunung Sari Village, Pamijahan District, Bogor Regency, is not the main sector in its community activities. The existence of natural tourism in the form of waterfalls, camping ground and hot springs is a potential for the village to realize the Bogor Regency Mission. Existing tour operators are not residents or village communities. The active participation of village communities has not been seen in the management, operational and maintenance of tourist attractions. The tour paramilitary group 20 can be an agent for villages to empower communities in the tourism sector. Srikandi Gunung Sari group is a community group that involves mothers and produces local food products in the form of banana chips and cassava. In an effort to increase the active participation of village communities in tourism activities in Gunung Sari Village, the empowerment of the Laskar Tourism Group 20 and Srikandi Gunung Sari was carried out through education, workshops, mentoring and facilitation activities. The main target of this activity is the village community who can independently manage, maintain and improve the tourism sector in Gunung Sari village towards a sustainable tourism independent village.
Penerapan K-Nearest Neighbor (KNN) untuk Klasifikasi Anggrek Berdasarkan Karakter Morfologi Daun dan Bunga Sesilia Novita R; Prihastuti Harsani; Arie Qur’ania
KOMPUTASI Vol 15, No 1 (2018): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.749 KB) | DOI: 10.33751/komputasi.v15i1.1267

Abstract

Sistem klasifikasi anggrek dibuat dengan menerapkan algoritma K-Nearest Neighbor dan inputan berupa teks. Sistem ini bertujuan membantu masyarakat umum dalam mengenali tanamanan anggrek berdasarkan genus dan varietasnya. Karakter morfologi yang digunakan sebagai atribut dalam klasifikasi diantaranya bentuk daun, bentuk bunga, bentuk sepal lateral, warna sepal lateral, bentuk sepal dorsal, warna sepal dorsal, bentuk petal, warna petal, bentuk ujung bibir dan corak bunga. Penerapan algoritma pada sistem klasifikasi anggrek diharapkan dapat memberikan hasil keputusan terbaik. Prinsip kerja dari algoritma K-Nearest Neighbor adalah data yang diuji diklasifikasikan berdasarkan keanggotaan terdekat yang terbanyak dari data uji. Perhitungan dilakukan dengan menghitung kuadrat jarak euclidian masing-masing objek terhadap data sampel, kemudian diurutkan dari nilai terkecil hingga terbesar dan pencarian nilai k sebagai hasil keputusan. Pengujian sistem dilakukan terhadap 15 data latih menghasilkan nilai akurasi 53,33%, dengan jumlah nilai benar 8 data dan jumlah nilai salah 7 data.Keywords: K-Nearest Neighbor (K-NN), Sistem Klasifikasi, Anggrek Kedisiplinan
KOMPUTERISASI KONVERSI BILANGAN MENGGUNAI(AN BORLAND DELPHI 7.0 Prihastuti harsani; Reni Megawali
KOMPUTASI Vol 6, No 11 (2009): Vol. 6, No. 11, Januari 2009
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.248 KB) | DOI: 10.33751/komputasi.v6i11.1767

Abstract

KOMPUTERISASI KONVERSI BILANGAN MENGGUNAI(AN BORLAND DELPHI 7.0
Aplikasi Diagnosis Penyakit Sapi Menggunakan Metode Certainty Factors Berbasis Android Indra Fauzi Rahman; Prihastuti Harsani; Arie Qurania
KOMPUTASI Vol 13, No 2 (2016): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.641 KB) | DOI: 10.33751/komputasi.v13i2.144

Abstract

Sejak tahun 1950 perkembangan aplikasi dengan basis sistem pakar sangat diminati. Untuk mempersingkat waktu dalam mengambil keputusan diperlukan sistem pakar. Bisnis peternakan sangat menjanjikan, akan tetapi memerlukan perhatian yang sangat tinggi terhadap adanya serangan penyakit, seperti halnya sapi yang sangat rentan terhadap berbagai penyakit. Dengan adanya aplikasi system pakar yang dapat mendiagnosa secara cepat, akurat dan tepat terhadap penyakit dini yang ditimbulkan maka diharapkan dapat membantu peternak dalam memperkecil angka kematian disebabkan oleh penyakit yang mengakibatkan kerugian. Diperlukan ketepatan dan keakuratan perhitungan dalam mendiagnosis gejala penyakit sehingga menyimpulkan hasil dengan menggunakan metode certainty factors. Metode Certainty Factors sering diterapkan dalam banyak permasalahan nyata.
Co-Authors Abimanyu Oki Saputra Ade Muchlis Maulana Anwar Ade Ofik Hidayat Agus Ismangil Alexander A. S. Gunawan, Alexander A. S. Alexander Agung Santoso Gunawan Amelia Rahmi Andhika Bhayangkari Andria, ferdi Anisa Intan Selatan Arie Qur’ania Aries Maesya Dadang Kurnia Deden Ardiansyah Dinar Munggaran Achmad Elly Sukmanasa Eneng Tita Tosida Erniyati Erniyati ferdi Andria Fredi Andria Gugun Adiguna Indra Fauzi Rahman Iyan Mulyana Lili Ayu Wulandhari Muhamad Sunarzi Novi Fajar Utami Rahman, Indra Fauzi Reni Megawali Salmah Salmah Sesilia Novita R Siti Warnasih Soleha Nuramanah Triasti nurmiatiningsih Triastinurmiatiningsih, - Triastinurmiatiningsih, Triastinurmiatiningsih Wulandhari, Lili Ayu Yuli Wahyuni