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Application of the Steepest Ascent Hill Climbing (SAHC) Algorithm for Mobile-based Shortest Route Search Mhd Furqan; A Armansyah; Razzaq H. Nur Wijaya
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v4i1.88

This study aims at early to determine the application of algorithms Steepest Ascent Hill Climbing (SAHC) for finding the shortest route-based Mobile in Humbang Hasundutan. Based on the results of the application of algorithms Steepest Ascent Hill Climbing (Sahc) To search based Shortest These Mobile in Humbang Hasundutan. So it can be concluded that the search for the shortest route based on Mobile can be solved using the Steepest Ascent Hill Climbing algorithm. In the manual calculation process using the Steepest Ascent Hill Climbing algorithm at the node from Humbang, there is a heuristic value of 0.0896184808, at the node from which the three intersections are originated there is a heuristic value of 0.1693780561, at the node from which there is a heuristic value of 0.367474152, at the node from which the waterfall falls sibabo has a heuristic value of 0.3823982675. Then the result of the shortest route from Sipinsur Geosite (F) to Simolap Waterfall (B) is F èD èB (Sipinsur GeoSite - intersection 4 - Simolap Waterfall) the total distance is 51 km and the time is 1 hour 34 minutes. So that the test results of the Steepest Ascent Hill Climbing algorithm process with the system in accordance with the manual calculation process of the Steepest Ascent Hill Climbing algorithm.

Classification of Tomato Leaf Based on Gabor Filter Extraction And Support Vector Machine Algorithm Mhd. Furqan; A Armansyah; Lely Sahrani
IJISTECH (International Journal of Information System and Technology) Vol 4, No 2 (2021): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v4i2.173

Tomato production in Indonesia is reduced because tomato leaves are stricken with disease. The main disease that often attacks tomato leaves is rotten leaves and bacterial patches or commonly called dry patches. Identification of tomato leaf disease is still done manually with human vision. The shortcomings of the method manually required a technology that is able to extract the texture of tomato leaf disease. One of them is by the process of extracting the texture of leaves with gabor filters, namely by using frequency and orientation parameters. Based on the results of the experiment obtained that the input parameter gabor filter with orientation of 90o with a combination of frequency 4 produces a fairly clear contrast. The process of extracting the texture of the leaf aims to get the magnitude value of the tomato leaf that will be used as inputs for the classification process. The svm algorithm grouped data that had the same characteristics into one class. Training data used 42 images and test data used 30 images, with the success rate of 83.33%.

Prototipe Jaringan Syaraf Tiruan Multilayer Perceptron Untuk Prediksi Mahasiswa Dropout Armansyah Armansyah
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 4, No 4 (2021): Agustus 2021
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v4i4.3171

Abstrak-- Adanya data mahasiswa yang tidak aktif, yang dipandang sebagai mahasiswa dropout yang secara kuantitas mengalami kenaikan dari tahun ketahun membuat penulis merasa perlu melakukan penelitian ini. Dimana, tingkat mahasiswa dropout merupakan satu indikator penurunan kualitas institusi perguruan tinggi. Jika ini dibiarkan, jumlah mahasiswa dropout akan bertambah bilamana tidak dicari solusinya. Penelitian ini bertujuan memprediksi mahasiswa yang berpotensi putus sekolah dengan pendekatan jaringan syaraf tiruan. Dengan mengamati 13 variabel yang mempengaruhi, dan 1 variabel keluaran yang akan dilatih dengan model multi layer perceptron, diharapkan dapat menghasilkan kinerja prediksi dengan nilai 0, untuk mahasiswa berpotensi dropout, dan 1 untuk mahasiswa yang tetap melanjut hingga akhir, dengan menunjukkan hasil komputasi tingkat akurasi setidaknya 96,90% dan tingkat error yang rendah.Kata kunci : Prediksi, Dropout, Jaringan Syaraf Tiruan, Multi-Layer Perceptron.

Disease in Corn Leafe Using Gabor Wavelet and K-Means Clustering Algorithm Mhd Furqan; Armansyah Armansyah; Nurhasanah Nurhasanah
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study aims to develop a system to classify diseases that attack corn leaves. This study used four types of disease, namely: leaf blight (Helminthosporium turcicum), leaf spot (Bipolaris maydis syn), leaf rust (Puccinia polysora) and downy mildew (Peronosclerospora maydis). This study uses 52 data in the form of images. Every image is changed into vector data using Gabor wavelet filter. This study uses the K-Means Clustering method for disease grouping. The data in this study are vector data. This research process goes through the stages of preprocessing, clustering, and accuracy testing. Preprocessing includes Gabor wavelet filters to extract vector data from the original image. Clustering uses K-Means by determining the starting point manually and calculating similarity using Euclidean Distance. Independent testing of accuracy by comparing the system and manual. The highest accuracy is 98% of the 51 correct data using 52 data with 4 data cluster labels.

Application of the Steepest Ascent Hill Climbing (SAHC) Algorithm for Mobile-based Shortest Route Search Mhd Furqan; A Armansyah; Razzaq H. Nur Wijaya
IJISTECH (International Journal of Information System and Technology) Vol 4, No 1 (2020): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

This study aims at early to determine the application of algorithms Steepest Ascent Hill Climbing (SAHC) for finding the shortest route-based Mobile in Humbang Hasundutan. Based on the results of the application of algorithms Steepest Ascent Hill Climbing (Sahc) To search based Shortest These Mobile in Humbang Hasundutan. So it can be concluded that the search for the shortest route based on Mobile can be solved using the Steepest Ascent Hill Climbing algorithm. In the manual calculation process using the Steepest Ascent Hill Climbing algorithm at the node from Humbang, there is a heuristic value of 0.0896184808, at the node from which the three intersections are originated there is a heuristic value of 0.1693780561, at the node from which there is a heuristic value of 0.367474152, at the node from which the waterfall falls sibabo has a heuristic value of 0.3823982675. Then the result of the shortest route from Sipinsur Geosite (F) to Simolap Waterfall (B) is F èD èB (Sipinsur GeoSite - intersection 4 - Simolap Waterfall) the total distance is 51 km and the time is 1 hour 34 minutes. So that the test results of the Steepest Ascent Hill Climbing algorithm process with the system in accordance with the manual calculation process of the Steepest Ascent Hill Climbing algorithm.

Classification of Tomato Leaf Based on Gabor Filter Extraction And Support Vector Machine Algorithm Mhd. Furqan; A Armansyah; Lely Sahrani
IJISTECH (International Journal of Information System and Technology) Vol 4, No 2 (2021): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Tomato production in Indonesia is reduced because tomato leaves are stricken with disease. The main disease that often attacks tomato leaves is rotten leaves and bacterial patches or commonly called dry patches. Identification of tomato leaf disease is still done manually with human vision. The shortcomings of the method manually required a technology that is able to extract the texture of tomato leaf disease. One of them is by the process of extracting the texture of leaves with gabor filters, namely by using frequency and orientation parameters. Based on the results of the experiment obtained that the input parameter gabor filter with orientation of 90o with a combination of frequency 4 produces a fairly clear contrast. The process of extracting the texture of the leaf aims to get the magnitude value of the tomato leaf that will be used as inputs for the classification process. The svm algorithm grouped data that had the same characteristics into one class. Training data used 42 images and test data used 30 images, with the success rate of 83.33%.

Analisis Kemampuan Akademik Mahasiswa Berdasarkan Latar Belakang Keluarga, Tempat Tinggal, Pertemanan, Sikap Belajar, Konsep Diri, Iklim Kampus, Dan Tenaga Pengajar Dengan Jaringan Syaraf Tiruan Backpropagation Armansyah*, Guntur Armasyah Armansyah; Guntur Syahputra; Moch Iswan Perangin-angin
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 19, No 1 (2020): Februari 2020
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v19i1.227

Dalam hal akademis, Indeks Prestasi Kumulatif (IPK) merupakan tolok ukur prestasi pelajar termasuk mahasiswa. IPK itu sendiri adalah produk hasil dari proses belajar yang diperoleh dari berbagai bentuk evaluasi. Tingginya perolehan IPK mahasiswa kemudian menganggap bahwa mahasiswa dipandang memiliki kemampuan yang baik pula dalam setiap perkuliahan. Namun ternyata anggapan tersebut tidak sepenuhnya benar. Penelitian ini bertujuan untuk memprediksi tingkat kemampuan mahasiswa dalam perkuliahan, terutama untuk matakuliah program studi, khususnya pemrograman. Parameter yang disoroti pada penelitian ini adalah latar belakang keluarga, tempat tinggal, lingkungan pertemanan, sikap belajar, konsep diri, iklim kampus dan tenaga dosen. Kami berpendapat bahwa ketujuh komponen tersebut jika relevan dengan diri mahasiswa dapat memengaruhi tingkat kemampuan mahasiswa. Jaringan Syaraf Tiruan Backpropagation digunakan untuk melatih dan menguji data dari hasil kuesioner berdasarkan ketujuh komponen diatas. Dari beberapa percobaan, keluaran dan target sangat mendekati dengan tingkat akurasi mencapai 99,50% dengan nilai MSE paling kecil 10-7 atau 0,0000001.

Implementation of Naïve Bayes Method in Classification of Nutritional Status of Toddlers at Pasar Ujungbatu Sosa Public Health Center Heri Santoso; A Armansyah; Fitri Handayani Siregar
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.254

Health is a very important field in human life, there have been many studies or studies conducted in the health sector, for example nutrition problems. Nutrients are needed by humans to live healthy in order to be able to move and carry out daily activities. For the fulfillment of nutrition in toddlers is usually influenced by social and economic factors of the family. Toddlers' bodies need balanced nutrition to be able to grow and develop properly. The results of the SSGI in 2021 the stunting rate nationally decreased by 1.6% per year from 27.7% in 2019 to 24.4% in 2021. The data used in this study was 1114 toddler data. From the results of training and data testing consisting of 5 attributes, namely gender, age, weight, height, and upper arm circumference and there are 4 classes for class division, namely over nutrition, good nutrition, less nutrition and poor nutrition. And it is known that the accuracy by using 10 data samples gets an accuracy value of 80%. Thus, the system built using the Naive Bayes method is considered successful in classifying the nutritional status of children under five

Analisis Sentimen Mahasiswa Terkait Pembelajaran Tatap Muka Menggunakan Metode Naive Bayes Classifier Heri Santoso; Armansyah Armansyah; Dita Desliani
Techno.Com Vol 21, No 3 (2022): Agustus 2022
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/tc.v21i3.6262

Pemerintah Indonesia melalui 4 kementerian yaitu Menteri Kesehatan, Menteri Dalam Negeri, Menteri Agama serta Menteri Pendidikan dan Kebudayaan, menerbitkan surat keputusan bersama mangenai Panduan Penyelenggaraan Pembelajaran Di Masa Pandemi Coronavirus Disease 2019. Berdasarkan SKB, pemerintah memfasilitasi pelaksanaan pembelajaran jarak jauh dan pembelajaran tatap muka terbatas disemua tingkatan pendidikan. Keputusan pemerintah tersebut ditanggapi beragam oleh masyarakat, termasuk mahasiswa yang terlibat langsung dalam penerapan kebijakan ini. Banyak mahasiswa yang menyampaikan pendapat terkait kebijakan ini, baik pendapat positif ataupun negatif. Pada penelitian ini, dilakukan analisis sentimen yang bertujuan untuk mengetahui sentimen yang diberikan mahasiswa terkait penerapan pembelajaran tatap muka tahun ajaran 2021/2022 diperoleh melalui kuisioner (angket) serta menerapkan metode Nave Bayes Classifier. Menggunakan dataset sebanyak 5350 opini yang berasal dari 1070 responden. Berdasarkan proses analisis sentimen yang dilakukan, dapat disimpulkan bahwa mahasiswa/i dari Universitas Islam Negeri Sumatera Utara Medan mendukung penerapan pembelajaran tatap muka (PTM) dilingkungan UIN-SU Medan pada semester genap tahun ajaran 2021/2022. Akurasi yang dihasilkan oleh metode Nave Bayes Classifier saat melakukan klasifikasi sentimen (opini) dapat dikatakan baik, yaitu sebesar 84%. Setelah melakukan proses validasi sistem dengan menerapkan K-Fold Cross Validation, nilai K=10 ternyata metode Nave Bayes Classifier berhasil memperoleh akurasi yang baik, dengan rata – rata akurasinya sebesar 83%. Kata kunci: analisis sentimen, nave bayes classifier, k-fold cross validation, pembelajaran tatap muka

Implementation of Naïve Bayes Method in Classification of Nutritional Status of Toddlers at Pasar Ujungbatu Sosa Public Health Center Heri Santoso; A Armansyah; Fitri Handayani Siregar
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.254

Health is a very important field in human life, there have been many studies or studies conducted in the health sector, for example nutrition problems. Nutrients are needed by humans to live healthy in order to be able to move and carry out daily activities. For the fulfillment of nutrition in toddlers is usually influenced by social and economic factors of the family. Toddlers' bodies need balanced nutrition to be able to grow and develop properly. The results of the SSGI in 2021 the stunting rate nationally decreased by 1.6% per year from 27.7% in 2019 to 24.4% in 2021. The data used in this study was 1114 toddler data. From the results of training and data testing consisting of 5 attributes, namely gender, age, weight, height, and upper arm circumference and there are 4 classes for class division, namely over nutrition, good nutrition, less nutrition and poor nutrition. And it is known that the accuracy by using 10 data samples gets an accuracy value of 80%. Thus, the system built using the Naive Bayes method is considered successful in classifying the nutritional status of children under five

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