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All Journal Elkom: Jurnal Elektronika dan Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL PENDIDIKAN TAMBUSAI JURNAL KAJIAN TEKNIK MESIN INTI Nusa Mandiri Zonasi: Jurnal Sistem Informasi JTIK (Jurnal Teknik Informatika Kaputama) E-Link: Jurnal Teknik Elektro dan Informatika Jurnal Infortech Unri Conference Series: Community Engagement KLIK: Kajian Ilmiah Informatika dan Komputer JUSTIAN - Jurnal Sistem Informasi Akuntansi Profitabilitas Indonesian Journal of Networking and Security - IJNS JAPI: Jurnal Akses Pengabdian Indonesia Jurnal Komputer Antartika I'thisom: Jurnal Ekonomi Syariah Bhumiputra: Jurnal Penelitian dan Pengabdian Masyarakat Global
Muhammad Rifqi Firdaus
Universitas Bina Sarana Informatika
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Nursing Public Health Social Sciences Other

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Edukasi Pemanfaatan Tanaman Di Bantaran Sungai Sebagai Alternatif Obat Bagi Warga Kampung Hijau, Kelurahan Sungai Bilu, Kalimantan Selatan Komaliya, Risyda; Audina, Mia; Firdaus, Muhammad Rifqi; Ipnas, Rini Ardila; Aisyiyah, Siti; Meliyani, Tri
JAPI (Jurnal Akses Pengabdian Indonesia) Vol 9, No 3 (2024)
Publisher : Universitas Tribhuwana Tunggadewi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/japi.v9i3.6166

Abstract

Tanaman bantaran sungai memiliki potensi besar sebagai alternatif obat, namun kurangnya pengetahuan dan keterampilan warga Kampung Hijau, Kelurahan Sungai Bilu, Kalimantan Selatan dalam memanfaatkannya menjadi salah satu permasalahan utama di daerah ini. Untuk mengatasi permasalahan tersebut, dilakukan kegiatan pengabdian warga dengan tujuan meningkatkan pengetahuan warga dalam pemanfaatan tanaman obat. Metode yang digunakan dalam kegiatan ini adalah diskusi kelompok yang melibatkan 19 warga Sungai Bilu dengan media leaflet sebagai sarana edukasi. Selain itu, pretest dan posttest digunakan untuk mengukur efektivitas kegiatan dalam meningkatkan pengetahuan warga. Data yang diperoleh dari pretest dan posttest dianalisis untuk melihat peningkatan pemahaman peserta mengenai manfaat dan cara penggunaan tanaman obat. Hasil perbandingan sebelum dan sesudah kegiatan memberikan gambaran yang jelas mengenai efektivitas materi dan metode yang digunakan. Kegiatan Pengabdian Kepada Masyarakat ini berhasil meningkatkan pengetahuan dan keterampilan warga Kampung Hijau dalam memanfaatkan tanaman di bantaran sungai sebagai alternatif obat.
Application of the Finite State Automata (FSA) Method in Indonesian Stemming using the Nazief & Adriani Algorithm fitriana, lady agustin; Mustopa, Ali; Firdaus, Muhammad Rifqi; Dahlia, Rizka
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.4038

Abstract

Language is a communication tool commonly used in everyday life. Each country has a different language with predetermined rules. For instance, in the Indonesian language, there are approximately 35 official affixes mentioned in the Big Indonesian Dictionary. These affixes include prefixes (prefixes), infixes (insertions), suffixes (suffixes), and confixes (a combination of prefixes and suffixes). In Information Retrieval, there is a stemming process, which is the process of converting a word form into a base word or the process of transforming variant words into their base form. The theory of language and automata is the foundation of the computer science field that provides the basis for ideas and models of computer systems. In the implementation of the research, several stages were carried out, such as explaining the Nazief & Adriani stemming algorithm, finite state automata, creating pseudocode, and testing using a web-based system, resulting in affixed words becoming the correct base words with 20 affixed words. The results obtained from reading this web-based system, the base word "cinta" (love) used as a test yielded accurate results in accordance with the concept of the Nazief & Adriani stemming algorithm. There are some weaknesses in stemming from suffixes, and the solution is to perform stemming from the prefix position (Prefix).
ANALISIS PENGUKURAN KUALITAS WEBSITE CAKRAWALAMEDIA.CO.ID DENGAN MENGGUNAKAN METODE WEBQUAL 4.0 Firdaus, Muhammad Rifqi; Purnia, Dini Silvi; Handayani, Kartika; Julianto, Muhamad Fahmi
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 4 No. 1 (2020): Volume 4, Nomor 1, Januari 2020
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v4i1.633

Abstract

The development of Information Technology has triggered the emergence of many online media. The cakrawalamedia.co.id website is an online media portal that utilizes these updates. Cakrawalamedia.co.id presents the focus of news around West Java especially the City of Tasikmalaya. The problem related to this research is whether the quality of cakrawalamedia.co.id website influences the readers' satisfaction. This study focuses on user satisfaction with the webqual method which consists of 3 variables, namely usability, information quality and interaction quality. The data used are primary data, namely by distributing questionnaires using a Likert scale with 22 questions to 133 respondents. Data obtained and processed using multiple linear regression analysis techniques using SPSS 16 software. Based on webqual variables, the results of the analysis state the quality of usability, information quality and interaction quality affect user satisfaction.
ANALISIS SENTIMEN TWITTER TERHADAP MENTERI INDONESIA DENGAN ALGORITMA SUPPORT VECTOR MACHINE DAN NAIVE BAYES Siti Nurhasanah Nugraha; Rangga Pebrianto; Abdul Latif; Muhammad Rifqi Firdaus
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 17 No. 1: Mei 2022
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v17i1.3965

Abstract

Kabinet Indonesia Maju adalah kabinet pemerintahan Indonesia pada pimpinan Presiden JokoWidodo dan Wakil Presiden Ma’ruf Amin. Dengan dilantiknya para menteri di Kabinet IndonesiaMaju, tokoh politik yang memiliki jabatan dan tanggung jawab sebagai menteri dalammelaksanakan tanggung jawabnya tak lepas dari berbagai opini. Salah satu metode untukmengelompokkan kategori opini pengguna media sosial adalah sentiment analyst. Penelitian inimenggunakan dataset hasil crawling dari twitter dengan kata kunci “Menteri”. Hasil crawlingdiolah menggunakan kedua model algoritma yaitu Support Vector Machine (SVM) dan Naïve Bayes.Penelitian ini membandingkan hasil cross validation algoritma SVM dengan Naïve Bayes. Hasilcross validation dari algoritma SVM menunjukkan nilai accuracy sebesar 89,60%, recall 90,91%,precission 97,64%. untuk algoritma Naïve Bayes dihasilkan accuracy sebesar 85,74%, recall85,74%, precission 100,00%. SVM bekerja memaksimalkan margin antara dua kelas yang berbeda,Naïve Bayes sederhana menerapkan teori probabilitas untuk mencari kemungkinan terbesar dariklasifikasi. Dari hasil tersebut dapat disimpulkan kedua algoritma yang digunakan memberikansolusi untuk masalah klasifikasi dalam kasus analisis sentimen menteri, terlepas dari SVMmenghasilkan akurasi yang lebih baik.
Analisis Kualitas Layanan Website Atap Rupa-Rupa Menggunakan Metode Webqual 4.0 Andini Mutiara; Mozadilla Sabina; Hesti Septiani; Ahmad Ishaq; Muhammad Rifqi Firdaus
PROFITABILITAS Vol 5 No 2 (2025): JURNAL PROFITABILITAS
Publisher : Sistem Informasi Akuntansi Kampu Kabupaten Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/profitabilitas.v5i2.11648

Abstract

Penelitian ini bertujuan untuk mengevaluasi kualitas layanan Website Atap Rupa Rupa menggunakan metode Webqual 4.0 yang mencakup empat dimensi utama: usability, information quality, service interaction quality, dan user satisfaction. Webqual 4.0 dipilih karena mampu memberikan kerangka evaluasi yang komprehensif dalam menilai persepsi dan kepuasan pengguna terhadap layanan digital. Pengumpulan data dilakukan melalui kuesioner yang disebarkan kepada responden kemudian dianalisis secara kuantitatif menggunakan uji validitas, reliabilitas, dan analisis regresi linear berganda untuk mengetahui pengaruh masing-masing dimensi terhadap kepuasan pengguna. Hasil penelitian menunjukkan bahwa seluruh dimensi berpengaruh signifikan terhadap kepuasan pengguna, dengan dimensi information quality memberikan kontribusi paling dominan. Temuan ini memberikan implikasi strategis bagi pengelola Website dalam merancang perbaikan berkelanjutan yang berorientasi pada pengalaman pengguna. Penelitian ini diharapkan dapat menjadi referensi akademik sekaligus praktis dalam pengukuran kualitas layanan berbasis digital.
Penerapan Metode EDAS dalam Sistem Pendukung Keputusan untuk Pemilihan Software Akuntansi Lady Agustin Fitriana; Badariatul Lailiah; Rabiatus Saadah; Rizka Dahlia; Muhammad Rifqi Firdaus
Jurnal Sistem Informasi Akuntansi Vol 7 No 1 (2026): : Periode Maret 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/justian.v7i1.12522

Abstract

Selecting appropriate accounting software is a significant challenge for organizations due to diverse functional attributes. Suboptimal choices can adversely affect operational efficiency and financial management quality. This study develops a Decision Support System (DSS) using the Evaluation Based on Distance from Average Solution (EDAS) method to determine the optimal software choice among five alternatives: Zahir, Accurate, Mekari Jurnal, SAP Business One, and Kledo. Data were collected via questionnaires from 30 respondents, including accounting practitioners and active users. The evaluation focused on five key criteria: software pricing, ease of use, feature completeness, system integration, and technical support. The EDAS method evaluated these alternatives by calculating their deviation from the average solution through Positive Distance from Average (PDA) and Negative Distance from Average (NDA), resulting in a final Appraisal Score for ranking. The results show that EDAS produces a clear, discriminative ranking. Zahir achieved the highest score (0.798), followed by Mekari Jurnal (0.779), SAP Business One (0.553), Kledo (0.500), and Accurate (0.444). These findings demonstrate that the EDAS approach effectively supports objective multi-criteria decision-making and possesses strong potential for implementation in digital-based recommendation systems for accounting software selection, ensuring businesses make data-driven, efficient choices.
PENERAPAN HYPERPARAMETER MACHINE LEARNING DALAM PREDIKSI GAGAL PINJAM Dinar Ismunandar; Muhammad Rifqi Firdaus; Yuris Alkhalifi
INTI Nusa Mandiri Vol. 19 No. 1 (2024): INTI Periode Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i1.5612

Abstract

Loans or credit are one of the key factors in advancing the economy. One of them is encouraging business expansion which will have a direct impact on a country's economic growth. Banks and other financing institutions must be able to evaluate the borrower's ability to pay their debts based on the inherent risks to reduce the possibility of default. To this end, machine learning (ML) has emerged as a revolutionary tool in using advanced prediction methods to examine historical data based on customer behavior. This research investigates the application of ML in predicting loan outcomes by optimizing parameters in the Machine Learning algorithm. The ML algorithms examined in this research are Logistic Regression (LR), K-Nearest Neighbor (KNN), Random Forest (RF), Decision Tree (DT), and XGBoost (XGB). Meanwhile, the technique used in hyperparameter tuning is Grid Search Cross Validation (CV). The results show that the algorithm's performance is more optimal than before, it can be seen that the LR algorithm experienced an increase in accuracy of 5%, KNN by 4%, RF by 3%, DT by 3%, and XGB by 2%. By including a default dataset based on customer behavior and optimized algorithm parameters, apart from being able to answer the alignment in previous literature in providing a deeper understanding of loan estimation, this research can also provide an understanding that hyperparameter techniques are worth trying to improve the performance of ML algorithms. So, it will be easier for financing institutions to determine the right loan scenario.
ANALISIS KUALITAS WEBSITE PORTAL MEDIA ONLINE MILENIANEWS.COM MENGGUNAKAN STANDAR ISO 9126 Muhammad Rifqi Firdaus; Yuris Alkhalifi; Dinar Ismunandar; Oky Kurniawan
INTI Nusa Mandiri Vol. 19 No. 2 (2025): INTI Periode Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i2.6218

Abstract

Software quality can be assessed based on two main criteria, namely conformance to specifications and the ability to meet user needs. One of the international standards used to assess software quality is ISO 9126, which includes six main aspects: functionality, reliability, usability, efficiency, maintainability, and portability. In this journal, four aspects are taken to examine the quality of an online media portal website milenianews.com. The research methods include black-box testing for functionality, stress testing for reliability, Likert Scale-based questionnaire for usability, and GTMetrix for efficiency. The results showed that the functionality aspect scored 100%, indicating that all functions run according to specifications. The reliability aspect shows a 100% success rate on sessions, pages, and hits, indicating excellent performance under high usage conditions. Usability scored 79%, which falls into the good category, reflecting an interface that is easy to use and understand by users. The efficiency aspect obtained grade B with a performance score of 75% and structure 91%, indicating quite good performance, although there is room for improvement, especially in the load time of 2.5 seconds and total blocking time of 192 ms. Overall, the milenianews.com online media portal has met ISO 9126 quality standards and is declared suitable for use. These results show the importance of implementing international standards-based quality testing to ensure an optimal user experience.
PENERAPAN MODEL TRANSFORMER INDOBERT UNTUK ANALISIS SENTIMEN PADA ULASAN APLIKASI TWITCH Rizky Gunawan; Rizka Dahlia; Muhammad Rifqi Firdaus; Lady Agustin Fitriana
ZONAsi: Jurnal Sistem Informasi Vol. 8 No. 2 (2026): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Mei 2026
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/nw62kn64

Abstract

Pemahaman terhadap persepsi publik terhadap aplikasi Twitch menjadi penting karena ulasan pengguna mencerminkan pengalaman penggunaan, kualitas layanan, serta berbagai permasalahan yang dihadapi pengguna. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna aplikasi Twitch berbahasa Indonesia dengan menerapkan model Transformer IndoBERT (indobert-base-p1) melalui proses fine-tuning. Dataset diperoleh dari Google Play Store menggunakan google-play-scraper, kemudian dipraproses melalui cleaning, case folding, normalisasi, tokenisasi, stopword removal, dan stemming. Pelabelan data dilakukan menggunakan pendekatan lexicon-based sebagai ground truth dengan tiga kelas sentimen, yaitu positif, netral, dan negatif. Selanjutnya data digunakan untuk melatih model IndoBERT dengan konfigurasi learning rate 2e-5, batch size 8, dan lima epoch. Evaluasi dilakukan menggunakan accuracy, precision, recall, dan F1-score. Hasil pengujian menunjukkan bahwa model terbaik diperoleh pada epoch ke-4 dengan akurasi sebesar 89% dan weighted average F1-score sebesar 89%. Analisis confusion matrix memperlihatkan bahwa model memiliki performa terbaik pada kelas negatif dan netral, sedangkan kelas positif masih mengalami sejumlah kesalahan klasifikasi ke kelas netral. Temuan ini menunjukkan bahwa IndoBERT mampu memahami konteks bahasa informal pada ulasan aplikasi berbahasa Indonesia dan layak digunakan sebagai pendekatan analisis sentimen untuk mendukung evaluasi kualitas layanan Twitch.
Co-Authors Abdul Latif Abdul Latif Abdul Latif Adinda Thalia Salsa Bela Ahmad Ishaq Ainun Defrilia Ali Mustopa, Ali Alif, Muhammad Naufal Amalia Nuril Hidayati Amin Nur Rais Andini Mutiara Anjelli, Risfa Arief Rama Sena Athaillah, Dea Badariatul Lailiah Dinar Ismunandar Dinar Ismunandar Dinar Ismunandar Dini Silvi Purnia, Dini Silvi Elah Nurlelah Erika Mutiara Erni Ermawati Faizi, Ahlan Fuad Nur Hasan Gata, Windu Hanif, Dhestra Amanullah Hanifi, Rizal Hesti Septiani Ipin Sugiyarto Ipnas, Rini Ardila Irwan Herliawan Irwan Herliawan - Universitas Nusa Mandiri Ishaq, Ahmad Julianto, Muhamad Fahmi Jumaida, Cut Kardiman Kartika Handayani Khairunnisa Khairunnisa Khoirunnisa, May Hanny Komaliya, Risyda Lady Agustin Fitriana Lifia Revanata Lisnawanty M. Ridwan Meliyani, Tri Mia Audina, Mia Mozadilla Sabina Muhamad Abdul Ghani Muhamad Fahmi Julianto Muhammad Ifan Rifani Ihsan Mutmainah, Mutiara Nila Hardi Oky Kurniawan Oky Kurniawan Popon Handayani Prameswari, Regita Nur Pratama, Muhammad Rehan Putra, Akhmal Arya Rabiatus Saadah Rangga Pebrianto Rizka Dahlia Rizkhi, Miftahul Rizky Gunawan Salsha Putri Aisyah N Sandi Saputri, Rizka Sari, Elen Retno Siti Aisyiyah, Siti Siti Nurhasanah Nugraha Subhan, Daris Tania, Mira Tedjakusuma, Arya Ditama Umniyah, Alya Wasalma, Ahwa Rizki Wijaya, Hany Duta Windu Gata Wulandari, Sri Astuti Yuris Alkahfi Yuris Alkhalifi Yusnarida Eka Nizmi