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All Journal International Journal of Electrical and Computer Engineering Jurnal Buana Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Sistem Informasi dan Bisnis Cerdas EMITTER International Journal of Engineering Technology KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian Polinema Kepada Masyarakat Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Jurnal INFOTEL Jurnal Informatika Polinema (JIP)
Vivi Nur Wijayaningrum
Politeknik Negeri Malang
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Public Health Other

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Forecasting Model of Staple Food Prices Using Support Vector Regression with Optimized Parameters Mungki Astiningrum; Vivi Nur Wijayaningrum; Ika Kusumaning Putri
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 3 (2021): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i3.22010

Abstract

The large number of Indonesians who consume rice as their primary food makes rice price a benchmark for determining the other staple food prices. The instability of rice prices due to climate change or other uncontrollable factors makes it difficult for Indonesians to estimate the rice prices, especially for the poor. This study proposes the usage of the Improved Crow Search Algorithm (ICSA) to optimize the Support Vector Regression (SVR) parameter in building a regression model to predict the price of staple foods. The forecasting process is carried out based on time series data of 11 staples for four years. The proposed ICSA optimizes the six parameters used in the SVR to form a regression model, consisting of lambda, epsilon, sigma, learning rate, soft margin constant, and the number of iterations. Algorithm performance is measured using MAPE and NRMSE by comparing the actual price of staple foods and forecasting results to get the error rate. With this parameter optimization mechanism, the forecasting results given are good enough with a small error value, in the form of MAPE of 17.081 and NRMSE of 1.594. A MAPE value between 10 and 20 indicates that the forecasting result is acceptable, while an NRMSE value of less than 10 indicates that the forecasting accuracy is excellent. The improvised technique on Crow Search Algorithm is proven to improve the performance of Support Vector Regression in forecasting the price of staple foods.
Jatropha Curcas Disease Identification using Random Forest Triando Hamonangan Saragih; Vivi Nur Wijayaningrum; Muhammad Haekal
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.20141

Abstract

As one of the most versatile plants, Jatropha curcas is spread in various regions around the world because of the great benefits it provides. However, Jatropha curcas is easily attacked by viruses which then cause damage to the plant, such as yellowing leaves and secreting sap, making it necessary to identify Jatropha curcas disease to deal with the problem as early as possible so that the losses incurred are not too large. An expert system was built to be able to identify Jatropha curcas disease by adopting expert knowledge. The use of the Random Forest algorithm as one of the classification algorithms was applied in this study. By using a random forest, several disease prediction classes are generated by each decision tree that has been formed. The disease class with the most votes was used as the final result. In this study, the data used were 166 data with 9 diseases and 30 symptoms. The results showed that Random Forest outperformed other algorithms such as Fuzzy Neural Network and Extreme Learning Machine with an accuracy of 98.002% using the composition of training data and test data of 70:30.
An Improved Crow Search Algorithm for Data Clustering Vivi Nur Wijayaningrum; Novi Nur Putriwijaya
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.498

Abstract

Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. This problem often occurs in optimization cases involving high dimensions such as data clustering. Imbalance of the exploration and exploitation process is the cause of this condition because search agents are not able to reach the best solution in the search space. In this study, the problem is overcome by modifying the solution update mechanism so that a search agent not only follows another randomly chosen search agent, but also has the opportunity to follow the best search agent. In addition, the balance of exploration and exploitation is also enhanced by the mechanism of updating the awareness probability of each search agent in accordance with their respective abilities in searching for solutions. The improve mechanism makes the proposed algorithm obtain pretty good solutions with smaller computational time compared to Genetic Algorithm and Particle Swarm Optimization. In large datasets, it is proven that the proposed algorithm is able to provide the best solution among the other algorithms.
OPTIMASI PENDISTRIBUSIAN BARANG FARMASI MENGGUNAKAN ALGORITMA GENETIKA Febri Ramadhani; Ficry Agam Fathurrachman; Restu Fitriawanti; Angki Christiawan Rongre; Vivi Nur Wijayaningrum
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 5, No 2 (2018)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v5i2.151

Abstract

Distribution is an activity of distributing goods from factory to agents. Distribution process is considered efficient if the process of distribution of goods done with a minimal distance, so that the time and cost required for the distribution process will also be smaller. Genetic algorithm is used to optimize the pharmaceutical goods distribution process by finding the order of agents that each vehicle must visit during the distribution process. The data used is the cost and distance data between factory and each agent. One-cut point method is used for crossover process, reciprocal exchange method is used for mutation process, and elitism method for selection process. Based on the test result that has been done, the optimal parameters which are used to produce the best solution, such as the population size is 45, the generation number is 70, and the combination of cr and mr is 0.8 and 0.3. By using the best parameters, the resulting fitness value is in the range 0.014909 up to 0.017642. Keywords: Genetic Algorithm, Distribution, Pharmaceutical, Optimization Distribusi merupakan kegiatan menyalurkan barang dari pabrik ke agen. Proses distribusi dianggap efisien jika proses penyaluran barang dilakukan dengan jarak yang minimal, sehingga waktu dan biaya yang dibutuhkan untuk proses distribusi juga akan semakin kecil. Algoritma genetika digunakan untuk melakukan optimasi pada proses distribusi barang farmasi dengan mencari solusi berupa urutan agen yang harus dikunjungi oleh setiap kendaraan saat proses distribusi. Data yang digunakan adalah data biaya dan jarak antara pabrik dengan masing-masing agen. Metode one-cut point digunakan untuk proses crossover, metode reciprocal exchange digunakan untuk proses mutasi, dan metode elitism untuk proses seleksi. Berdasarkan hasil pengujian yang telah dilakukan, parameter optimal yang digunakan untuk menghasilkan solusi terbaik, antara lain ukuran populasi sebanyak 45, generasi sebanyak 70, serta kombinasi cr dan mr yaitu 0.8 dan 0.3. Dengan menggunakan parameter terbaik tersebut, nilai fitness yang dihasilkan berada pada rentang 0.014909 sampai dengan 0.017642. Kata kunci: Algoritma Genetika, Distribusi, Farmasi, Optimasi
Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi Anggi Mahadika Purnomo; Davia Werdiastu; Talitha Raissa; Restu Widodo; Vivi Nur Wijayaningrum
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (219.705 KB) | DOI: 10.14710/jtsiskom.7.1.2019.1-6

Abstract

Hypertension can be prevented and handled by eating nutritious foods with the right composition. The genetic algorithm can be used to optimize the food composition for people with hypertension. Data used include sex, age, weight, height, activity type, stress level, and patient hypertension level. This study uses a reproduction method that is good enough to be applied to integer chromosome representations so that the search results provided are not local optimum solutions. The testing results show that the best genetic algorithm parameters are as follows population size is 15 with average fitness 20.97, the generation number is 40 with average fitness 50.10, and combination crossover rate and mutation rate are 0.3 and 0.7 with average fitness 41.67. The solution obtained is the optimal food composition for people with hypertension.
PELATIHAN PENGENALAN RAMBU-RAMBU LALU LINTAS DAN PRIORITAS PENGGUNA JALAN MENGGUNAKAN MEDIA INTERAKTIF Eka Larasati Amalia; Vivin Ayu Lestari; Mustika Mentari; Farida Ulfa; Vivi Nur Wijayaningrum; Chintya Puspa Dewi; Dimas Shella Charlinawati; Ermi Pristiyaningrum
Jurnal Pengabdian Polinema Kepada Masyarakat Vol. 8 No. 2 (2021): Jurnal Pengabdian Polinema Kepada Masyarakat
Publisher : UPT Penelitian dan Pengabdian Kepada Masyarakat Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jppkm.v8i2.93

Abstract

Tingginya minat anak-anak terhadap teknologi menyebabkan pentingnya dilakukan pengarahan agar anak-anak dapat memanfaatkan teknologi untuk kegiatan pembelajaran secara positif. Anak-anak sebagai generasi penerus bangsa harus dapat dididik secara benar untuk menjadi generasi yang berkualitas melalui berbagai kegiatan seperti stimulasi, pengasuhan, pendampingan, dan pelatihan yang bertujuan untuk mengembangkan potensi dan pengetahuan anak-anak agar dapat berkembang secara optimal. Kegiatan pengabdian kepada masyarakat dianggap perlu dilakukan untuk memperkenalkan penggunaan teknologi yang bermanfaat kepada anak-anak di Taman Baca Galeri Kreatif. Kegiatan ini dikemas dalam bentuk pelatihan melalui sebuah aplikasi permainan tentang rambu-rambu lalu lintas dan prioritas pengguna jalan. Berdasarkan hasil uji coba permainan rambu-rambu lalu lintas dan prioritas pengguna jalan untuk anak-anak di Taman Baca Galeri Kreatif, diketahui minat dan antusias mereka dalam proses pembelajaran sangat tinggi. Hal ini dibuktikan dengan tingginya partisipasi para peserta didik untuk berpartisipasi dalam menjawab soal yang berkaitan dengan rambu-rambu lalu lintas secara tepat.
SISTEM INFORMASI MANAJEMEN PEMESANAN USAHA KATERING DI PANTI ASUHAN PUTRI AISYIYAH MALANG Eka Larasati Amalia; Mustika Mentari; Vivin Ayu Lestari; Farida Ulfa; Vivi Nur Wijayaningrum; Widiareta Safitri; Naufal Yukafi Ridlo; Nabilah Argyanti Ardyningrum
Jurnal Pengabdian Polinema Kepada Masyarakat Vol. 8 No. 2 (2021): Jurnal Pengabdian Polinema Kepada Masyarakat
Publisher : UPT Penelitian dan Pengabdian Kepada Masyarakat Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jppkm.v8i2.103

Abstract

Pembekalan keterampilan pada anak-anak asuh di Panti Asuhan merupakan sebuah hal penting yang dapat mereka gunakan sebagai bekal di masa depan. Panti Asuhan Putri Aisyiyah Malang memberikan para anak asuhnya dengan keterampilan berwirausaha melalui usaha katering bernama PAP’A. Seiring berkembangnya usaha katering PAP’A tersebut, jangkauan pelanggan yang melakukan pemesanan juga semakin bertambah, sehingga diperlukan adanya manajemen pemesanan yang baik. Sayangnya, katering PAP’A tidak memanfaatkan teknologi untuk melakukan manajemen pemesanan yang dilakukan oleh pelanggan. Mereka hanya mencatat transaksi pemesanan yang dilakukan melalui telepon, WhatsApp, atau SMS ke dalam sebuah buku. Hal inilah yang menyebabkan seringnya terjadi human error dan berimbas pada kerugian di pihak pelanggan maupun pihak katering PAP’A. Oleh karena itu, pada kegiatan pengabdian kepada masyarakat ini, diusulkan sebuah sistem informasi dalam bentuk website yang dikembangkan untuk memudahkan pihak katering PAP’A dalam melakukan manajemen pemesenan. Dengan adanya sistem informasi ini, pihak katering PAP'A dapat melakukan pengelolaan daftar pesanan, daftar produk makanan, dan pembayaran secara lebih terstruktur. Adanya fitur pembayaran juga memberikan kemudahan bagi pihak katering PAP'A untuk menghasilkan nota bukti pembayaran yang dilakukan oleh pelanggan.
Optimization of Ship’s Route Scheduling Using Genetic Algorithm Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 1: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i1.pp180-186

Abstract

Route scheduling is a quite complicated process because it involves some determinant factors. Several methods have been used to help resolve the NP-hard problems. This research uses genetic algorithm to assist in optimizing ship scheduling, that where there are several ports to be visited by some ships. The goal is to divide the ship to go to a specific port so that each port is only visited by one ship to minimize the total distance of all ships. The computational experiment produces optimal parameters such as the number of popsize is 30, the number of generations is 100, crossover rate value is 0.3 and mutation rate values is 0.7. The final results is an optimal ship route by minimizing the distance of each ship.
Offline Signature Recognition using Back Propagation Neural Network Asyrofa Rahmi; Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy; Andi Maulidinnawati A. K. Parewe
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp678-683

Abstract

The signature recognition is a difficult process as it requires several phases. A failure in a phase will significantly reduce the recognition accuracy. Artificial Neural Network (ANN) believed to be used to assist in the recognition or classification of the signature. In this study, the ANN algorithm used is Back Propagation. A mechanism to adaptively adjust the learning rate is developed to improve the system accuracy. The purpose of this study is to conduct the recognition of a number of signatures so that can be known whether the recognition which is done by using the Back Propagation is appropriate or not. The testing results performed by using learning rate of 0.64, the number of iterations is 100, and produces an accuracy value of 63%.
Automatic essay assessment in e-learning using winnowing algorithm Eka Larasati Amalia; Vivin Ayu Lestari; Vivi Nur Wijayaningrum; Ali Ar Ridla
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp572-582

Abstract

The pandemic has caused almost all educational institutions to use online learning media to support learning activities. E-learning is a technology that is widely used because it can accommodate all learning activities. However, in general, e-learning can only perform automatic assessments for multiple choice answers but not for essay answers, so that manual assessment by the teacher becomes difficult and takes a long time. In this study, the winnowing algorithm was applied to the automatic assessment process on students' essay answers by measuring their similarity to the teacher's answer key. The stages in the automatic assessment using the winnowing algorithm begin with forming a series of k-grams, calculating the hash value, forming a window from the hash value, calculating the fingerprint value, and calculating the Jaccard Coefficient to obtain the percentage of text similarity results. The test results show that the winnowing algorithm can provide good performance when the answers to questions are in the form of short entries with the number of hashes not smaller than the window value. Meanwhile, on questions with long answers, the winnowing algorithm can still work well with an average difference of 5.2% from the results of the assessment carried out by the teacher.
Co-Authors Abdillah, Muhammad Navis Ali Ar Ridla Alysha Ghea Arliana Ananta, Ahmadi Yuli Andi Maulidinnawati A. K. Parewe Anggi Mahadika Purnomo Angki Christiawan Rongre Anim Rofi’ah Annisa Puspa Kirana Annisa Puspa Kirana Astiningrum, Mungki Asyrofa Rahmi Augusta, San Sayidul Akdam Aziz, Hamim Fathul Berryl Radian Hamesha Budi Harijanto, Budi Chintya Puspa Dewi Davia Werdiastu Deatrisya Mirela Harahap Dimas Shella Charlinawati Dini, Robih Eka Larasati Amalia Ermi Pristiyaningrum Farida Ulfa Farida Ulfa Febri Ramadhani Febrianti, Yane Marita Ficry Agam Fathurrachman Gotami, Nurina Savanti Widya Haekal, Muhammad Hamim Fathul Aziz Heny Dwi Jayanti Iftitah Hidayati Ika Kusumaning Putri Ika Kusumaning Putri Ilham Sinatrio Gumelar Imam Fahrur Rozi Lia Agustina Lubis, Wahyuni M. Hasyim Ratsanjani Mamluatul Hani’ah Maulidina, Hanif Prasetyo Moch Zawaruddin Abdullah Mochammad Hairullah Muhammad Dimas Setiawan Sanapiah Muhammad Haekal Muhammad Rizki Mubarok Mustika Mentari Nabilah Argyanti Ardyningrum Naufal Yukafi Ridlo Noprianto Noprianto Noprianto Noprianto Noprianto, Noprianto Noprianto, Noprianto Novi Nur Putriwijaya Nur Khozin Nurina Savanti Widya Gotami Pambudi, Rizki Agung Putri, Ika Kusumaning Qoirul Kotimah Restu Fitriawanti Restu Widodo Robih Dini Rokhimatul Wakhidah Rudy Ariyanto San Sayidul Akdam Augusta Saputra, Firhad Rinaldi Saragih, Triando Hamonangan Talitha Raissa Vipkas Al Hadid Firdaus Vivin Ayu Lestari Wayan Firdaus Mahmudy Widiareta Safitri Yane Marita Febrianti