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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab SMARTICS Journal Syntax Literate: Jurnal Ilmiah Indonesia JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Edukasi Islami: Jurnal Pendidikan Islam JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research METIK JURNAL Jurnal Informatika Kaputama (JIK) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Ilmu Komputer dan Bisnis Jurnal Teknologi Informasi dan Multimedia Jurnal Ekonomi Manajemen Sistem Informasi Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Computer and Information System (IJCIS) International Journal of Engineering, Science and Information Technology Jurnal Tika Instal : Jurnal Komputer Dirgamaya: Jurnal Manajemen dan Sistem Informasi Jurnal Minfo Polgan (JMP) Jurnal Teknik Mesin Mechanical Xplore Abdimas Jurnal Sistem Informasi STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Jitu: Jurnal Informatika Utama VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Hananto, Agustia
Fakultas Ilmu Komputer, Program Studi Sistem Informasi, Universitas Buana Perjuangan Karawang, Karawang, Indonesia
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ANALISIS USER SENTIMENT APLIKASI GOOGLE MAPS, MAPS.ME DAN WAZE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE Ilham Fariz Asya Mubarok; Baenil Huda; Agustia Hananto; Tukino Tukino; Huban Kabir
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 1 (2023): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i1.3020

Abstract

Nowadays, the routing app is often used by many people, this app is very useful for users to find the best route by just entering the address code, this app can provide travel routes which can be taken by different kinds of vehicles. In Indonesia itself, there are several widely used route guidance apps with various positive and negative reviews. In this study, different types of apps namely Google Maps, Maps.me and Waze were used and the data is from user feedback through an online survey. The purpose of this study is to find out the users' ratings for each application which was used as the material for the study. Support Vector Machine method was used to process the data. For each app, 750 comments were received and the final result of maps.me was the app with the highest score based on 86.40% accuracy, 86.55% precision and 99.69% recall. The maps.me app received 68% positive reviews, followed by Waze with 29% and Google Maps with 3%. This makes maps.me the app with the highest score based on positive reviews.
Penerapan Metode K-Nearest Neighbor pada Sentimen Analisis Pengguna Twitter terhadap KTT G20 di Indonesia Herda Andriana; Shofa Shofia Hilab; Agustia Hananto
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5427

Abstract

Indonesia will host the KTT (Konferensi Tingkat Tinggi) G20 summit on the island of Bali on November 15, 2022. The G20 was formed with one goal in mind: to boost the global economy, which had just entered a period of crisis. However, Indonesia's participation as a full member of the Group of Twenty (G20) has sparked controversy among the country's general populace and the population of Indonesia itself, necessitating a thoughtful analysis of the group's motives. Sentiment analysis was gleaned from tweets on KTT G20 posted on the social media platform Twitter. Data scraping yielded a total of 2,500 tweets for inclusion in the collection. Methods for classifying tweets into positive, neutral, and negative groups are required because of the large amount of data that has already been collected. The purpose of this study was to analyze public opinion on Twitter during the KTT G20. The data was processed using the Orange neural network using a number of tools and the K-Nearest Neighbor method, yielding a total of 1,107 tweets that were successfully added to the original set, with an average recall and precision of 99%. According to the analysis of sentiment, there were 89 negative tweets, 614 neutral tweets, and 404 positive tweets, with the most common emotions being happiness, surprise, and fear
Strategi Promosi untuk Meningkatkan Penjualan Kedai Kopi Desimal Menggunakan Algoritma K-Medoids Clustering Anggi Octa Fadilah; Baenil Huda; Agustia Hananto; Tukino Tukino
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5561

Abstract

The Decimal coffee shop is a coffee shop located in the city of Karawang and is a coffee shop that is already busy with many customers, the Decimal coffee shop has been established since 2020 until now. Decimal coffee shop offers 35 diverse menu items, and sales can fluctuate, sometimes increasing and sometimes decreasing in the quality of the menu items sold. In this problem, sales data at Decimal coffee shops is not used to improve sales quality, the sales data is only used as an archive for the coffee shop, if the data is analyzed properly, it will be useful to determine which menu items are selling well and which are not selling well. By analyzing sales data, it will be possible to determine which menu needs to be improved in terms of sales. This information can then be used by the coffee shop as a reference in developing a promotional strategy aimed at increasing sales of the menu product. To find out how many menus are sold at Decimal coffee shops, a clustering study was carried out. This research was conducted by analyzing sales data in excel form, the K-Medoids method was used to create clusters based on product sales data that had been obtained from the Decimal Coffee Shop. From the clustering results, there are 3 clusters which are classified as high, medium, and low, and the accuracy is determined using the RapidMiner tool. Of the 35 items analyzed, the first cluster contains 18 items which are rated the highest, the second cluster contains 12 items which are classified as moderate, and the third cluster contains 5 items which are classified as the lowest. From these results there are 5 items on sales that are classified as low, therefore a promotional strategy is needed to increase the menu product.
Perbandingan Algoritma Naive Bayes Dan SVM Dalam Sentimen Analisis Marketplace Pada Twitter Indra Kurniawan; April Lia Hananto; Shofa Shofia Hilabi; Agustia Hananto; Bayu Priyatna; Aviv Yuniar Rahman
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3582

Abstract

Online buying and selling transactions are increasing in Indonesia due to the ease of using marketplace platforms, and online shopping saves more time than offline shopping. Each marketplace has advantages and disadvantages, this affects customer sentiment who have made transactions on the marketplace platform. This research uses customer opinion from tweet data based on positive or negative sentiments to compare the Naive Bayes (NB) and Support Vector Machine (SVM) classification algorithms with the aim of finding out the best classification algorithm based on the accuracy value for sentiment analysis using the marketplace platform. The tweet data in this study was taken from October 18 to November 11, 2022. To test the performance of the NB and SVM classification algorithms using the Cross Validation method and from the results of the comparison test that the SVM algorithm has the best accuracy value compared to the NB algorithm. Where the accuracy value of Tokopedia uses the NB algorithm is 85.34%, and the accuracy value uses SVM 86.82%, the accuracy value for Shopee uses NB is 80.04%, and the accuracy value uses SVM 80.91%. and Lazada which uses the NB algorithm has an accuracy value of 83.52%, while the accuracy value uses SVM 88.93%, which means that the use of the SVM algorithm has the best level of accuracy.
ALGORITMA C4.5 DALAM MENGUKUR TINGKAT PENGETAHUAN SISWA TERHADAP PELAJARAN BAHASA INGGRIS Witulas Ambang Cahyati; Shofa Shofia Hilabi; Agustia Hananto; Tukino Tukino
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.11

Abstract

This study aims to categorize the level of students' knowledge of English lessons. To understand the lesson, the teaching and learning process is certainly very important for a student. Achievement of student knowledge is the main function of the existence of an educator. The large number of vocabulary that often sounds foreign to the ear makes it difficult for students to solve English questions because it is difficult to translate. The data source was obtained from students of class VII (seven) at SMP N 03 West Karawang who filled out an English knowledge questionnaire. The C4.5 algorithm is the classification method that is used, and is assisted by the RapidMiner application. The attributes used are student learning methods, learning tools, teacher teaching methods and student interest and student ambition. The results obtained from this study, the value of gain and entropy attributes obtained 23 English knowledge decision rules where the understanding status totaled 12 rules, the status did not understand totaled 11 rules. The accuracy resulting from classification modeling using the C4.5 Algorithm from RapidMiner is 78.12%. The application of the Algorithm C4.5 classification method can be implemented in order to provide new information related to the concept of students' knowledge of English lessons.
Clustering User Sentiment Transportasi Online Gojek Dan Grab Dengan Metode K-Means Dyno Syaiful Annam; Agustia Hananto; Fitria Nurapriani; Tukino Tukino
Jurnal Tika Vol 8 No 2 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i2.2165

Abstract

As an online transportation service, people often discuss it by sharing their opinions through various social media platforms, one of which is Google Play reviews. The opinions given by the public regarding online transportation services are diverse. Users provide reviews about the application, and naturally, users will choose an application with good reviews. However, monitoring the opinions of the general public is not easy, given the large volume of data to be processed. Therefore, the researcher aims to obtain accurate and precise information from user reviews of Gojek and Grab using clustering techniques, specifically the K-means method, using the RapidMiner application. The results of the testing of both applications can be summarized as follows: Gojek and Grab receive reviews that are not significantly different, although Grab's reviews are slightly better. The classification using the K-Means method offers a solution to the issue of sentiment analysis in user reviews of online transportation applications.
Sistem Informasi Geografis Pariwisata Gunung Berbasis Android Di Karawang Fizra Firdaus Nillan; Tukino Tukino; Fitria Nurapriani; Agustia Hananto
Innovative: Journal Of Social Science Research Vol. 3 No. 4 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i4.4505

Abstract

"Karawang terkenal bukan hanya karena sektor industri dan produksi padi, tetapi juga karena keindahan destinasi pariwisatanya dan warisan seni serta budayanya yang kaya. Di kota ini, yang terletak di Jawa, terdapat banyak keajaiban alam seperti air terjun, pantai, dan pegunungan. Selain itu, terdapat berbagai tujuan wisata alam yang menarik. Potensi pariwisata di wilayah ini dapat mempromosikan kekayaan lokal dan memberikan dorongan ekonomi pada tingkat lokal. Meskipun ada banyak tempat wisata yang tersedia, sebagian besar belum terungkap karena kurangnya akses informasi, terutama dalam hal objek wisata pegunungan di Karawang. Di era digital seperti saat ini, informasi seharusnya mudah ditemukan melalui berbagai media, baik itu media cetak maupun media elektronik. Terlebih lagi, kemajuan teknologi saat ini, terutama dalam bentuk ponsel pintar seperti smartphone, telah membuat masyarakat sangat bergantung pada teknologi ini karena kenyamanan penggunaannya. Smartphone, yang menjalankan sistem operasi Android yang bersifat open-source, memungkinkan pengguna untuk berkontribusi dalam pengembangan dan perluasan aplikasi serta perangkat lunaknya. Untuk mengatasi masalah kurangnya informasi tersebut, sebuah aplikasi Sistem Informasi Geografis (SIG) telah dikembangkan. Aplikasi ini dengan mudah dan aman dapat menyediakan informasi kepada masyarakat umum tentang destinasi wisata pegunungan, manfaat pendakian, perkiraan cuaca, serta faktor keamanan, sesuai dengan temuan dari penelitian ini. Dengan adanya aplikasi ini, para wisatawan dapat memperoleh informasi tentang destinasi wisata pegunungan di Karawang secara cepat, sederhana, dan efisien".
Penerapan Sistem Informasi Pengelolaan Perpustakaan Berbasis Website: (Studi Kasus pada SMK Bhinneka Karawang) Rati Ratnasari; Agustia Hananto
Jurnal Pendidikan Umum Vol 1 No 1 (2023): Jitu: Jurnal Informatika Utama
Publisher : CV. Astina Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55903/jitu.v1i1.72

Abstract

Penelitian ini bertujuan untuk: Mengembangkan sistem informasi perpustakaan yang dapat mengatasi permasalahan yang terjadi di perpustakaan SMK BHINEKA KARAWANG Melakukan uji kelayakan sistem informasi perpustakaan SMK BHINEKA KARAWANG dengan standar ISO 25010 pada aspek functional suitability, reliability, usability, dan portability. Metode penelitian yang digunakan adalah metode waterfall, yang terdiri dari tahapan analisis, desain, implementasi, dan pengujian. Pengujian kualitas dilakukan untuk mengetahui kualitas sistem informasi yang dikembangkan menggunakan standar kualitas ISO 25010 pada aspek functional suitability, reliability, usability, dan portability. Hasil penelitian ini adalah Penerapan Sistem Informasi Pengelolaan Perpustakaan berbasis Website Studi Kasus Pada SMK BHINEKA KARAWANG yang dikembangkan dengan framework dapat digunakan untuk mengatasi masalah pengelolaan perpustakaan yang masih menggunakan metode konvensional karena telah memiliki fitur-fitur yang telah disesuaikan dengan kebutuhan-kebutuhan dari pengguna sistem informasi, yakni mengelola data buku, data anggota, transaksi peminjaman buku, transaksi pengembalian buku, data keuangan, dan laporan perpustakaan.
Seleksi Penerimaan Bantuan Internet Gratis dengan Metode AHP Agustia Hananto; Muhamad Rizky Arfani; Saefil Aripiyanto
Jurnal Pendidikan Umum Vol 1 No 1 (2023): Jitu: Jurnal Informatika Utama
Publisher : CV. Astina Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55903/jitu.v1i1.73

Abstract

Internet kini telah menjadi kebutuhan penting karena diperlukan untuk komunikasi, hiburan dan pekerjaan. Virus corona telah menyebar secara luas di Indonesia. Melihat perubahan pola belajar saat ini, terdapat hambatan yang dirasakan oleh pelajar terutama dalam pembelajaran mengharuskan proses belajar mengajar antara pengajar serta peserta didik dilaksanakan secara jarak jauh (daring).Maka harus dibutuhkan sebuah sistem pendukung keputusan buat menentukan seleksi penerimaan bantuan internet gratis menggunakan prosedur pemecahan Analytical Hierarchy Process (AHP). Metode ini digunakan buat membuat perangkingan buat memilih penerima internet gratis, dimana nilai tertinggi yang dihasilkan berdasarkan dari kriteria terbaik Hasil dari perhitungan dengan metode ini. Dimana dengan dibuatnya sistem pendukung keputusan agar mencengah kesalahan dalam menentukan kriteria yang layak mendapatkan bantuan internet gratis.
Sistem Pendukung Keputusan Pemilihan Supplier Obat Menggunakan Metode Simple Additive Weighting Erlyta Hares; Shofa Shofia Hilabi; Agustia Hananto
Jurnal Accounting Information System (AIMS) Vol. 6 No. 1 (2023)
Publisher : Ma'soem University

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

Abstract

Determining drug suppliers for pharmacies choosing suppliers based on the price of the goods offered, the quality of the goods while in transit, whether the goods are received according to the order or not, and whether or not the delivery time for the goods reaches the pharmacy quickly. The main problem in supplier selection is decision making in choosing a good and efficient supplier and supported by problems that usually occur when the number of drugs sent does not match what was ordered, the packaging is damaged, the date is close to the expiration date. A decision support system for selecting drug suppliers with the help of the Simple Additive Weighting (SAW) method can assist pharmacies in making the right decisions on drug supplier selection to be chosen by pharmacies. The step in solving existing problems is to choose the best supplier by using the Simple Additive Weighting (SAW) method as a support for this research, in the Simple Additive Weighting (SAW) method which has ten (10) alternative suppliers that will be used to determine the best supplier, of course only one becomes the best supplier selection decision. Of the 10 suppliers selected after determining the value, the best results were obtained at Pt. Pharmaceutical Chemistry.
Co-Authors ,, Tukino Abdul Hafiz Afif Hakim Afra, Alfina Fadhilah Agneresa Agneresa Agus Supriyanto Alfiansyah, Muhammad Rindra ali, agus alzahra, alika aziza Amir Amir Amri Abdulah Anggi Octa Fadilah Angraeni, Rahmah Nur Annam, Dyno Syaiful Apriade Voutama Apriani, Fitria April Lia Hananto Arief Wibowo Arip Solehudin Asep Permana atikah, dwi Atmaja, Rashelin Zahra Aulia, Aldi Aviv Yuniar Rahman Aviv Yuniar Rahman Awal, Elsa Elvira Azizah, Fathin Putri Baenil Huda Baenil Huda Baenil Huda Baenil Huda Bayu Priyatna Bayu Yoga Astario Cepi Budiansyah, Ade Deva Defrina Aldeana Difa Prakoso Fuadi, Muhammad Dodi Mulyadi Dodi Mulyadi Dyno Syaiful Annam Eko Pramono Elfina Novalia Elfinanovalia , Elfinanovalia Emilia Sukmawati, Cici Erlyta Hares Fatmanisa Mumpuni Delta Maharani Ferdiansyah, Indra FIKRI HAIKAL Fitria Nur Apriani Fitria Nurapriani Fitria Nurapriani Fizra Firdaus Nillan Goenawan Brotosaputro Handayani, Citra Herda Andriana Heryana, Nono Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Huban Kabir Huda , Baenil Huda, Baenil Ikhsan, Muhammad Daffa Ilham Fariz Asya Mubarok Indra Kurniawan Jasmine Dina Sabila Karyadi Karyadi Khoirudin Khoirudin Khoirudin, Khoirudin Kusnadi, Akhmad Melisa Mubarok, Piky Muhamad Mammun Muhamad Rizky Arfani Muhamad Rizky Arfani Muhammad Khaerudin Novalia, Elfina Nur Widyartha, Yogi Nurafriani, Fitria Nurajizah, Dhea Nurapriani, Fitria Nurfajria, Dera Nurhayati Paryono, Tukino Pradana Rizki Maulana Pratama, Tito Chaerul Priyatna, Bayu Priyatna, Bayu Puspita Sari, Desti Rahdiana, Nana Rahmatiani, Lusiana Rahmawati, Adila Rati Ratnasari Reswara, Hadaya Abhista Rini Mayasari Rosalina, Elsa Sabrina Amanda Salsabila Saefil Aripiyanto Salsabila, Nasya Setiawan, Pratama Wahyu Setiawan, Pratama Wahyu Shofa Shofia Hilab Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Sifa, Sifa Rismawati Sigit Budi Nugroho Silvana Nazuah Siti Masruroh Sri Wahyuni Suhara, Ade Sukarman Sukarman Sukarman Sukarman Sunarya, Edwin Yohanes Supriyanto, Danang Susilo, Hendri Tamala, Evi TARMUJI TARMUJI, TARMUJI Taufik Ulhakim, Muhamad Thoyib, Imam Nurhuda Tikamori, Ghazi Tukino Tukino Tukino Tukino Tukino Tukino, Tukino Tukino, Tukino Tukino, Tukino tukino, tukino Utomo, Ainur Alam Budi Wahyu, Pratama Widyanti, Tyas Witulas Ambang Cahyati Yoga Astario, Bayu Zein, Selmia Aulia