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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) SITEKIN: Jurnal Sains, Teknologi dan Industri JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Inotera JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Cerdas Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Indonesian Journal of Data and Science Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer Indonesian Journal of Informatic Research and Software Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science CONSEN: Indonesian Journal of Community Services and Engagement Journal of Informatics, Electrical and Electronics Engineering The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Pengabdian Masyarakat Berdampak
Inggih Permana
Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Pemanfaatan Google Earth Imagery untuk Segmentasi Lahan Hijau Nesdi Evrilyan Rozanda; Ismail Marzuki; Inggih Permana
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2012: SNTIKI 4
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (701.494 KB)

Abstract

Google Earth merupakan sebuah virtual globe yang merekam hasil rekaman satelit secara langsung. Citra permukaan bumi ditampilkan oleh aplikasi Google Earth dengan resolusi yang berbeda sesuai dengan kepentingan dan interest points penggunanya. Salah satu pemanfaatan citra hasil rekaman Google Earth ini sudah dimanfaatkan untuk kepentingan penelitian.Para peneliti menggunakan Google Earth untuk beragam bidang penelitian karena kemudahan dan originalitas citra yang diberikan. Pada penelitian ini, pemanfaatan Google Earth imagery digunakan untuk proses segmentasi lahan hijau di Kota Pekanbaru dengan teknik pengolahan citra yang mengimplemtasikan metode K-Means Clustering. Jumlah cluster yang diharapkan ada dua, yaitu cluster sebaran lahan hijau dan cluster tidak lahan hijau. Hasil yang diperoleh adalah bahwacitra Google Earth terbukti dapat dijadikan sebagai bahan penelitian untuk segmentasi citra dengan menggunakan metode K-Means Clustering. Dua cluster output yang diharapkan berhasil di cluster dengan metode ini.
COMPARISON OF BOOK SHOPPING PATTERNS BEFORE AND DURING THE COVID-19 PANDEMIC USING THE FP-GROWTH ALGORITHM AT ZANAFA BOOKSTORES Dessi Cahyanti; Inggih Permana
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 2 (2022): JUTIF Volume 3, Number 2, April 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.2.211

Abstract

The high number of active cases of the Corona virus (Covid-19) has a major impact on the trade sector, namely a decrease in sales turnover, causing a decrease in income by business actors and a decrease in people's purchasing power. This study aims to compare shopping patterns before and during the pandemic in Zanafa bookstores. The method used in the study is a qualitative approach related to the assessment of attitudes, opinions and behavior. In this study the attribute used is the name of the item / product, these attributes are categorized based on the shelves that there are 40 categories of bookshelves. Testing dataset using FP-Growth algorithm in tools with support value of 3% and confidence value of 10% and the pattern used is a pattern that has lift Ratio >1. Based on the results of the analysis, it was found that the rules before the pandemic pandemic many items were purchased simultaneously, that is, if the purchase of science would buy school books with the highest lift ratio of 2.9537, while during the pandemic many items were purchased simultaneously, that is, if the purchase of politics, it would buy the Qur'an with the highest lift ratio from the test results of 2.6165. This can be used by TBZ to get recommendations as promotional materials to increase profits and as a sales strategy on TBZ.
Optimization Learning Vector Quantization Using Genetic Algorithm for Detection of Diabetics Inggih Permana; Nesdi Evrilyan Rozanda; Fadhilah Syafria; Febi Nur Salisah
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1111-1116

Abstract

This study proposed the method to improve the result of Learning Vector Quantization (LVQ) by optimizing the weight vectors using a genetic algorithm (GA) to detect the diabetics. Initial value of individuals for GA is taken from weight vectors which come from the last m iterations of LVQ training result. The result of experiment showed that there is a significant increase in sensitivity level, however there is a significant decrease in specificity level. It means the proposed method success in improving the LVQ ability to recognized the diabetics, but it lowers the ability of LVQ to recognize the people unaffected by diabetes.This study proposed the method to improve the result of Learning Vector Quantization (LVQ) by optimizing the weight vectors using a genetic algorithm (GA) to detect the diabetics. Initial value of individuals for GA is taken from weight vectors which come from the last m iterations of LVQ training result. The result of experiment showed that there is a significant increase in sensitivity level, however there is a significant decrease in specificity level. It means the proposed method success in improving the LVQ ability to recognized the diabetics, but it lowers the ability of LVQ to recognize the people unaffected by diabetes.
A comparative Study on Similarity Measurement in Noisy Voice Speaker Identification Inggih Permana
Indonesian Journal of Electrical Engineering and Computer Science Vol 1, No 3: March 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v1.i3.pp590-596

Abstract

One of important part on speaker identification is the measurement of sound similarity. This study has compared two of the similarity measurement techniques in the noisy voice. First technique is done by using smallest vector sum of pairs and second technique is done by using frequency of occurrence of smallest vector pairs. Noise in the voice can reduce accuracy of speaker identification significantly. To overcome this problem, the two of similarity measurement was combined with Least Mean Square (LMS) for remove noise. Results of the experiments showed that the use of LMS can improve the accuracy of speaker identification at the two of similarity measurement techniques. Second technique produces better accuracy than first technique. Experimental result also showed improvement of LMS learning rate can improve the accuracy of speaker identification.
Similarity Measurement for Speaker Identification Using Frequency of Vector Pairs Inggih Permana; Agus Buono; Bib Paruhum Silalahi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp6205-6210

Abstract

Similarity measurement is an important part of speaker identification. This study has modified the similarity measurement technique performed in previous studies. Previous studies used the sum of the smallest distance between the input vectors and the codebook vectors of a particular speaker. In this study, the technique has been modified by selecting a particular speaker codebook which has the highest frequency of vector pairs. Vector pair in this case is the smallest distance between the input vector and the vector in the codebook. This study used Mel Frequency Cepstral Coefficient (MFCC) as feature extraction, Self Organizing Map (SOM) as codebook maker and Euclidean as a measure of distance. The experimental results showed that the similarity measuring techniques proposed can improve the accuracy of speaker identification. In the MFCC coefficients 13, 15 and 20 the average accuracy of identification respectively increased as much as 0.61%, 0.98% and 1.27%.
Sosialisasi Penggunaan Teknologi Informasi Untuk Kegiatan Belajar dan Mengajar pada SMP Negeri XYZ: Socialization of the Use of Information Technology for Learning Activities at SMP Negeri XYZ Inggih Permana; Idria Maita Idria; Zarnelly Zarnelly
CONSEN: Indonesian Journal of Community Services and Engagement Vol. 2 No. 1 (2022): Consen: Indonesian Journal of Community Services and Engagement
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/consen.v2i1.487

Abstract

Sekolah Menengah Pertama (SMP) Negeri XYZ merupakan salah satu lembaga pendidikan formal yang ada di Provinsi Riau. Berdasarkan observasi awal, SMP Negeri XYZ belum memanfaatkan teknologi informasi secara maksimal. Contohnya adalah belum menggunakan e-learning dalam pembelajaran dan belum memanfaatkan video pembelajaran. Oleh sebab itu pengabdian ini menyosialisasikan penggunaan teknologi informasi untuk kegiatan belajar dan mengajar. Sosialisasi dilakukan dengan metode ceramah. Materi yang ada tiga, yaitu: (1) perkenalan e-learning; (2) pembuatan video pembelajaran; dan (3) internet sehat dan aman. Melalui sosialisasi yang dilakukan, guru dan siswa mendapatkan pengetahuan untuk memanfaatkan e-learning dan pembuatan video pembelajaran. Selain itu, siswa mendapat pengetahuan tentang internet sehat dan aman.
Penerapan Algoritma FP-Growth Dalam Pencarian Hubungan Antara Waktu Pembelian Dan Barang yang Dibeli Untuk Strategi Promosi Penjualan Tasya Marzuqah; Inggih Permana; M Afdal
JURIKOM (Jurnal Riset Komputer) Vol 10, No 3 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i3.6347

Abstract

Ledimart is a mini market that sells daily necessities. Ledimart is located in Pangkalan Kerinci District, Pelalawan Regency, Riau. The problem faced by the Ledimart minimarket is that this minimarket does not know when is the right time to carry out a promotion. To overcome these problems, this study conducted Association Rule Mining (ARM), in order to find out the relationship between the time of purchase and the goods purchased. The ARM algorithm used is the FP-Growth Algorithm. Based on the experimental results in December 2021, 6 rules were obtained, in January 2022, 6 rules were obtained, and in Ramadan 2022, 12 rules were obtained. By knowing this pattern, it is hoped that it can help Ledimart know when it is the right time to carry out promotions
Analisis Sentimen pada Ulasan Aplikasi Maxim di Google Play Store dengan K-Nearest Neighbor Restu Ramadhan; M Afdal; Inggih Permana; Muhammad Jazman
JURIKOM (Jurnal Riset Komputer) Vol 10, No 3 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i3.6396

Abstract

Online transportation is an innovation in emerging technology to solve various problems that arise in conventional public transportation such as in the ease of ordering, availability, and digitization of payments. Maxim is an online transportation company that has been operating since 2018 in Indonesia. As the number of users of the maxim application increases, demands for the quality of application service also increase. In the Google Play Store, reviews and information about an app are stored in text form. One of the processes of extracting text mining information in the text category is Sentiment Analysis to see the tendency of a sentiment or opinion whether it is positive, neutral, or negative at the Maxim application user reviews. The sentiment classification process using the K-NN algorithm produces accuracy, precision, and recall of 90.23%; 90.23%; and a recall value of 72.38% with an experiment using 90% training data, 10% test data, and a value of k = 5.
Perbandingan Algoritma NBC, KNN, dan C4.5 Untuk Klasifikasi Penerima Bantuan Program Keluarga Harapan Aulia Dina; Inggih Permana; Fitriani Muttakin; Idria Maita
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6316

Abstract

One of the strategic programs in Indonesia to tackle poverty is the Family Hope Program (PKH) which is carried out by the government by providing cash to very poor families. The problem that occurs in PKH is the distribution of aid that is still not on target. Therefore this study aims to create a classification model for PKH beneficiaries to overcome these problems. The algorithms used to create a classification model are the Naïve Bayes Classifier (NBC), K-Nearest Neighbor (K-NN), and C4.5. The validation method used is K-Fold Cross Validation (K = 10). The number of attributes used is 33 attributes. The data used to construct the classification model (data after pre-processing) is as much as 378 data on prospective PKH beneficiaries. Based on the experimental results the NBC algorithm produces an accuracy value of 77.51%, the K-NN algorithm (K = 3) produces an accuracy value of 76.72%, the C4.5 algorithm produces an accuracy value of 80.16%. In addition, the C4.5 algorithm succeeded in reducing the number of attributes, from 33 attributes to just 8 attributes, namely: number of household members, fasbab, other houses, gold, fridge, number of rooms, walls, and excreta disposal. This reduces the complexity of the classification model generated by the C4.5 algorithm.
Analisis Sentimen Pengguna Transportasi Online Maxim Pada Instagram Menggunakan Naïve Bayes Classifier dan K-Nearest Neighbor Dzul Asfi Warraihan; Inggih Permana; Mustakim Mustakim; Rice Novita
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6336

Abstract

Online transportation is a form of internet-based transportation that covers all aspects of the transaction process, including booking, route tracking, payment, and service assessment of the online transportation. Maxim is one of the popular online transportation providers in Indonesia so it will continue to improve its services to serve the needs of the entire community. In making developments, Maxim needs user opinions regarding its application or services. This research conducts sentiment analysis of Maxim users' opinions on Instagram using Naive Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms. Opinions are divided into 3 classes: negative, neutral, and positive. This research also uses the Random Over Sampling method and data sharing with 10-Fold Cross Validation. The accuracy results on sentiment data related to applications using the NBC algorithm are 81.03% and in the KNN algorithm with a value of k = 3 which is 80.72%. Meanwhile, sentiment data related to services produces an accuracy value in the NBC algorithm, namely 94% and the KNN algorithm with k = 3, namely 84%. It can be concluded that the NBC model is better than the KNN model in testing application-related sentiment data and service-related sentiment data after the Random Over Sampling method.
Co-Authors Aditya Nugraha Yesa Agus Buono Ahsyar, Tengku Khairil Al Kiramy, Razanul Alfakhri, Rezky Andaranti, Arifah Fadhila Andi Darlianto Andriyani, Dwi Ratna Anggi Widya Atma Nugraha Anggia Anfina Anisah Fitri Anjani, Yulia Merry Annisa Ramadhani Aprijon Arif Marsal Arif Marsal Arifin, Abdullah Aufa Zahrani Putri Aulia Dina Bib Paruhum Silalahi Dedi Pramana Dessi Cahyanti Detha Yurisna Detha Yurisna Dzul Asfi Warraihan Eka Pandu Cynthia, Eka Pandu Eki Saputra Eki Saputra Endah Purnamasari Esis Srikanti Fadhilah Syafria Fadil Rahmat Andini Farahdina Risky Ramadani Febi Nur Salisah Fiki Fikri, M. Hayatul Fitriah, Ma’idatul Fitriah, Ma’idatul Fitriani Muttakin Fitriani Muttakin Gurning, Umairah Rizkya Hafiz Aryan Siregar Hasbi Sidiq Arfajsyah Hendri, Desvita Hilda Mutiara Nasution Husaini, Fahri Idria Maita Idria Idriani R, Nova Ikhsani, Yulia Imam Muttaqin Intan, Sofia Fulvi Ismail Marzuki Jazman , Muhammad Jazman, Muhammad Kusuma, Gathot Hanyokro M Afdal M Afdal M Zaky Ramadhan Z M. Afdal M. Afdal M. Afdal M. Afdal M. Afdal Maulana, Rizki Azli Megawati Megawati - Mona Fronita, Mona Muhammad Afdal Muhammad Fikry Muhammad Jazman Muhammad Jazman Muhammad Naufal, Muhammad Muhammad Zacky Raditya Mukmin Siregar Mundzir, Mediantiwi Rahmawita Munzir, Medyantiwi Rahmawita Mustakim Mustakim Mustakim Mustakim Mustakim Mustakim Mutia, Risma Muttakin, Fitriani Nabillah, Putri Nardialis Nardialis Nasution, Nur Shabrina Naufal Fikri, R. Adlian Negara, Benny Sukma Nesdi Evrilyan Rozanda Nesdi Evrilyan Rozanda Nisa', Sayyidatun Norhavina Norhavina Nunik Noviana Kurniawati Nurainun Nurainun Nuraisyah Nuraisyah Nurfadilla, Nadia Nurkholis Nurkholis nursalisah, febi Octavia, Sania Fitri Pratama, Arya Yendri Priady, Muhamad Ilham Pristiawati, Andani Putri Puput Iswandi Putra, Moh Azlan Shah Putra, Tandra Adiyatma Rahman, Eman Rahmawita M, Medyantiwi Rangga Arief Putra Rayean, Rival Valentino Restu Ramadhan Ria Agustina Rice Novita Rice Novita Rizka Fitri Yansi Rizki Pratama Putra Agri Rozanda, Nesdi Evrilyan Sabillah, Dian Ayu Saeed, Alabbas Hussein Salisah, Pebi Nur Sania Fitri Octavia Sanusi Shir Li Wang Siti Monalisa Susanti, Pingki Muliya Tasya Marzuqah Tengku Khairil Ahsyar Triningsih, Elsa Tshamaroh, Muthia Uci Indah Sari Ula, Walid Alma Vicky Salsadilla Wenda, Alex Wido Purnama Winda Wahyuti Windy Amelia Putri Wira Mulia, M. Roid Yusmar Yusmar Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly