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All Journal JUSIFO : Jurnal Sistem Informasi Sistemasi: Jurnal Sistem Informasi JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pendidikan dan Teknologi Indonesia Malcom: Indonesian Journal of Machine Learning and Computer Science Science and Technology: Jurnal Pengabdian Masyarakat The Indonesian Journal of Computer Science
Jazman, Muhammad
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Social Sciences Other

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Pendekatan Machine Learning: Analisis Sentimen Masyarakat Terhadap Kendaraan Listrik Pada Sosial Media X Kusuma, Gathot Hanyokro; Permana, Inggih; Salisah, Febi Nur; Afdal, M.; Jazman, Muhammad; Marsal, Arif
JUSIFO : Jurnal Sistem Informasi Vol 9 No 2 (2023): JUSIFO (Jurnal Sistem Informasi) | December 2023
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v9i2.21354

Abstract

Environmental issues and the depletion of fossil fuels continue to escalate as the number of fossil fuel-based vehicle users increases in Indonesia. Electric vehicles emerge as one of the potential alternative solutions to address current environmental challenges, given their eco-friendly nature and lack of pollution emissions. Sentiment analysis is conducted to understand public responses, both supportive and opposing, towards electric vehicles. This research aims to analyze the sentiment of X-social media users regarding electric vehicles using machine learning techniques. The research stages include data collection, data selection, preprocessing, and classification using Naïve Bayes Classifier (NBC), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms. The test results show that on a balanced dataset using ROS, SVM performs the best with accuracy = 68.7%, precision = 77.9%, and recall = 68.4%. Meanwhile, NBC yields an accuracy of 60.3%, precision of 61.3%, and recall of 60.3%, while KNN has an accuracy of 53.9%, precision of 54%, and recall of 53.9%.
Analisis Kepuasan Pengguna Sistem Informasi E-Campus Menggunakan Metode E-Servqual Dan Model Kano Nurhadi, Muhammad; Hamzah, Muhammad Luthfi; Ahsyar, Tengku Khairil; Jazman, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2691

Abstract

This study aims to identify the dimensions and service attributes that need to be improved, as well as improvements related to the quality of services provided by the e-campus system to students at UIN Mahmud Yunus Batusangkar. It also aims to identify the quality of services provided by the e-campus system to students. in order to provide advice or consideration to improve the quality of the e-campus system to the campus or developer, which in turn will produce a solution to improve the quality of the e-campus system for user satisfaction. The procedures used include 5 stages are planning, gathering information processing information analysis and the latest reporting review. The research results created calculations using e-servqual procedures of 0.92 ≤ 1, showing that the quality of the services provided could be said to be unable to fulfill students' expectations. If the level of performance is met, it will bring about a very large increase in user satisfaction. But if not fulfilled, it will reduce the level of satisfaction. Whereas the canoe model gets eight attributes included in the must-be category, eight one-dimensional attributes and six attractive attributes. The ranking level obtained is a source of attributes that are prioritized to be improved. Every attribute that has a very large negative value will also be less effective in achieving user satisfaction
DIGITALISASI REKAP DATA IMUNISASI PADA PUSKESMAS BANGKINANG KOTA Fitri; Nofiar. Am, Andri; Pribadi, Antoni; Kurnia Oktorina, Fenty; Nasari, Fina; Ridwan, Muhammad; Jazman, Muhammad; Aryati, Rika
Science and Technology: Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2024): Juni
Publisher : CV. Science Tech Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69930/scitech.v1i2.34

Abstract

Posyandu yang berada dilingkungan kerja Puskesmas Bangkinang Kota masih banyak terdapat kendala dalam pengolahan informasi kepada masyarakat, karena masih menggunakan cara manual. Proses manual yang dilakukan dalam kegiatan pelayanan posyandu tersebut dimulai dari melakukan pencatatan kehadiran anak, melakukan pencatatatan data imuniasasi, melakukan penimbangan berat badan anak. Bentuk kegiatan tersebut masih dilakukan dengan pencatatan dikertas atau buku KIA, dan untuk informasi penjadwalan posyandu berikutnya belum tersedia. Kendala yang dihadapi bagi masyarakat jika ingin mendapatkan informasi secara cepat, sering terkandala dengan jam kerja pegawai Posyandu Puskesmas Bangkinang Kota dan pada saat sosialisasi yang dilakukan oleh pegawai Posyandu tidak semua masyarakat hadir atau mengetahui informasi tentang kegiatan Posyandu. Oleh karena itu solusi yang ditawarkan pada usulan program Pengabdian kepada Masyarakat yakni dengan pembuatan sistem informasi rekap data imunisasi Puskesmas Bangkinang Kota. Serta pelatihan penggunaan sistem kepada setiap petugas posyandu dilingkungan Puskesmas Bangkinang Kota.
Evaluasi Kualitas Layanan Aplikasi Airbnb di Indonesia melalui Importance Performance Analysis dan Customer Satisfaction Index Herliza, Herliza; Jazman, Muhammad; Saputra, Eki; Syaifullah, Syaifullah
Jurnal Pendidikan dan Teknologi Indonesia Vol 4 No 12 (2024): JPTI - Desember 2024
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.502

Abstract

Aplikasi Airbnb yang bertuju pada penyedia jasa akomodasi dengan tamu yang membutuhkan tempat menginap secara online, perkembangan teknologi saat ini yang mengharuskan memanfaatkan teknologi informasi manusia mulai memanfaatkan teknologi. Dengan adanya aplikasi ini, dapat memudahkan untuk memesan apa yang dibutuhkan untuk mencari penginapan yang sesuai keinginan. Terdapat beberapa permasalahan pada aplikasi Airbnb seperti, Pengguna kesulitan beberapa fitur yang susah dimengerti,  customer service ketika ada masalah, Aplikasi sering mengalami gangguan bug seperti aplikasi terkeluar sendiri saat sedang pencarian tempat penginapan dan sulitnya melakukan transaksi karena terjadi kesalahan dalam pengoperasian aplikasi tersebut sehingga dengan adanya customer service gangguan tersebut dapat diperbaiki. Tujuan dari penelitian ini adalah mengukur bagaimana kualitas aplikasi berdasarkan dari kepuasan penggunaan aplikasi Airbnb dengan menggunakan metode Importance Performance Analysis (IPA), dan Customer Satisfaction Index (CSI) dengan sampel yang diambil pada penelitian ini sebanyak 106 responden pengguna aplikasi Airbnb, dan terdapat 24 atribut dengan menggunakan 7 dimensi. Hasil penelitian ini menggunakan metode IPA yang menemukan 6 dari atribut -atribut yang mesti ditingkatkan kinerjanya, 6 atribut wajib untuk di pertahankan dalam kualitas pelayanan, 7 atribut yang setara antara tingkat kepentingan pengguna dengan kinerja aplikasi, dan 5 atribut tingkat kinerja lebih tinggi dari tingkat kepentingan pengguna. Untuk nilai yang didapat dari presentase CSI pada penelitian ini 69,62% pengguna merasakan puas dengan kualitas pelayanan Aplikasi Airbnb, dari hasil penelitian ini agar dapat melakukan peningkatan kualitas pada aplikasi Airbnb melalui metode IPA dan untuk meningkatkan nilai pada CSI agar lebih baik dari sebelumnya.
Comparative Analysis of Naïve Bayes Classifier and Support Vector Machine for Multilingual Sentiment Analysis: Insights from Genshin Impact User Reviews Aprinastya, Rachell; Jazman, Muhammad; Syaifullah, Syaifullah; Rahmawita, Medyantiwi; Siregar, Syafril; Saputra, Eki
JUSIFO : Jurnal Sistem Informasi Vol 10 No 2 (2024): JUSIFO (Jurnal Sistem Informasi) | December 2024
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v10i2.24876

Abstract

This study evaluates the performance of Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) algorithms in analyzing user sentiments regarding the popular online game Genshin Impact. The dataset comprises reviews sourced from the Google Play Store and App Store in both Indonesian and English, reflecting linguistic diversity. Preprocessing techniques such as tokenization, stemming, and Term Frequency-Inverse Document Frequency (TF-IDF) were employed to enhance data quality. Sentiments were classified as positive, neutral, or negative using TextBlob-assisted processes. Results demonstrate that NBC outperformed SVM across all metrics, with an average accuracy of 71% compared to 63%. Notably, sentiment analysis on English datasets consistently achieved higher accuracy than on Indonesian datasets, emphasizing the challenges posed by the linguistic complexity of Indonesian. This research underscores the critical role of language-specific adaptations in improving machine learning algorithms for multilingual sentiment analysis. The findings provide actionable insights for optimizing user engagement through enhanced game feedback mechanisms.
analisis Analisis Pengaruh Dimensi Budaya Terhadap Penggunaan Aplikasi Capcut Menggunakan UTAUT2 Ariyansir, Sigit; Syaifullah; Khairil Ahsyar, Tengku; Jazman, Muhammad; Marsal, Arif
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4430

Abstract

This research aims to determine the factors that influence the intention and use of the Capcut application, using Hofstede's extended UTAUT2 model with cultural variables. Data was collected through observation, interviews, document review and questionnaires. The analytical method used is PLS-SEM, with external models, internal models and hypothesis testing. The research results show that of the many hypotheses tested, only H3 (social influence on behavioral intentions), H7b (habits on usage behavior) and H14 (passion/restraint usage behavior) were accepted. Other hypotheses, such as performance expectations, effort expectations, and other cultural dimensions, did not show significant influence on usage intentions and behavior. In conclusion, habitual factors and social influence are the main drivers for adopting the Capcut application, while other factors do not have much influence in the context of this research
User Satisfaction Analysis of MyTelkomsel Application using Importance-Performance Analysis (IPA) and End-User Computing Satisfaction (EUCS) Methods Maulana, Bima; Rahmawita, Medyantiwi; Syaifullah, Syaifullah; Jazman, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): 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.v14i1.4866

Abstract

This study was conducted to analyze user satisfaction with the MyTelkomsel application using the End-User Computing Satisfaction (EUCS) and Importance-Performance Analysis (IPA) methods. The EUCS approach was employed to evaluate user satisfaction based on five key dimensions: content, accuracy, format, ease of use, and timeliness. Meanwhile, the IPA method was applied to identify features that require improvement based on the levels of importance and performance perceived by users. A quantitative method was used in this study, involving data collection through questionnaires distributed to active MyTelkomsel users. The results of the study revealed several dimensions that significantly contribute to user satisfaction, as well as areas that require prioritized improvements to enhance the quality of the application. The researchers hope that the findings of this study will assist developers in improving the application's quality to boost user satisfaction and loyalty.
Evaluation of User Satisfaction on Taxsee Driver Application using User Experience Questionnaire (UEQ) Rianda, Rahmad Didho; Rahmawita, Medyantiwi; Syaifullah, Syaifullah; Jazman, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): 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.v14i1.4868

Abstract

Technological advancements have made daily life more convenient, particularly in the field of online transportation services. To stay competitive in an increasingly tight market, companies like Maxim must continuously innovate to improve service quality. Maxim offers two applications: Maxim for passengers and Taxsee Driver for drivers. The Taxsee Driver app facilitates drivers in finding passengers, managing trips, and streamlining payment processes. However, the app still faces several technical issues, such as bugs during peak hours, fake orders, and GPS inaccuracies, which impact drivers' experiences and earnings. This study aims to evaluate the Taxsee Driver app using the User Experience Questionnaire (UEQ) to identify its strengths and weaknesses from the drivers' perspective. Through this analysis, key aspects such as interface design, responsiveness, security, and navigation integration can be assessed objectively. The evaluation results are expected to provide valuable insights for developers to enhance service quality, improve driver satisfaction and loyalty, and strengthen Maxim's position in the online transportation industry.
Implementation of Naive Bayes and Support Vector Machine Classification Algorithms for Sentiment Analysis of Bilingual Cyberbullying on X Application Sari, Novita; Jazman, Muhammad; Ahsyar, Tengku Khairil; Syaifullah, Syaifullah; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): 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.v14i1.4799

Abstract

The significant increase in social media usage has contributed to the rise in cyberbullying incidents, particularly in the context of multilingual language use. This study aims to conduct sentiment analysis to detect potential cyberbullying content on the X application using a bilingual approach (Indonesian and English) and leveraging the Naive Bayes (NB) and Support Vector Machine (SVM) algorithms. Tweets are collected and processed through a pre-processing stage to extract relevant features for sentiment analysis. Both algorithms are then applied to classify tweets into positive, negative, or neutral categories and identify indications of cyberbullying. The results of the trials indicate that the NB algorithm outperformed SVM, achieving an accuracy rate of 87%. Furthermore, in identifying cyberbullying patterns in bilingual text, NB reached the highest accuracy rate for the Indonesian language at 87%. These findings suggest that this study can serve as a reference for developing more accurate and responsive cyberbullying detection systems on bilingual social media platforms.
Analysis of User Satisfaction Levels for X Mobile Application in Pekanbaru using End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) Methods Butar Butar, Febiola Siska; Zarnelly, Zarnelly; Jazman, Muhammad; Novita, Rice; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): 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.v14i1.4851

Abstract

Mobile X is a digital innovation in banking transactions, combining mobile banking, internet banking, and e-money functions into a single platform. However, Mobile X faces several usage challenges that lead to user dissatisfaction. Therefore, an analysis of user satisfaction is essential to improve customer loyalty. The End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) methods are evaluation tools used to measure user satisfaction with an application system. This study employed a quantitative approach by distributing questionnaires to 100 respondents, determined using the Lameshow equation. The research model was analyzed through demographic analysis and model analysis using PLS-SEM, resulting in both internal and external models. The findings revealed that three hypotheses were accepted: the content variable (p-value = 0.495), the perceived usefulness variable (p-value = 0.007), and the timeliness variable (p-value = 0.001). Meanwhile, three hypotheses were rejected: the accuracy variable (p-value = 0.734), the content variable (p-value = 0.495), and the format variable (p-value = 0.184). Additionally, three user satisfaction factors were found to be significant for the accepted variables, indicating that meeting user expectations, perceived usefulness, information quality, and timeliness positively contribute to user satisfaction. This demonstrates that these factors effectively address user needs and enhance overall satisfaction with the Mobile X application.
Co-Authors Adam, A Ahsyar, T. Khairil Ahsyar, Tengku Khairil Am, Andri Nofiar Andaranti, Arifah Fadhila Anmi, Fauzi Hidayatul Anofrizen Anofrizen Aprinastya, Rachell Aqilla, Nabila Fadia Arif Marsal Ariyansir, Sigit Butar Butar, Febiola Siska Dermawan, Tri Dharmawan, Muhammad Rizky Eki Saputra Febi Nur Salisah, Febi Nur Fenty Kurnia Oktorina Fina Nasari Fitri Hamzah, Muhammad Luthfi Herliza, Herliza Inggih Permana Khairil Ahsyar, Tengku Kusuma, Gathot Hanyokro M Afdal M. Afdal MAULANA, BIMA Maulana, Rizki Azli Megawati - Mona Fronita, Mona Muhammad Ridwan Muttakin, Fitriani Novita Sari Nurhadi, Muhammad Prananda, Yaldri Oktra Praniffa, Anisya Caty Pribadi, Antoni Putri, Runi Aulia Rahmawita, Medyantiwi Raihan, Muhammad Renaldi, Rengga Rianda, Rahmad Didho Rice Novita Rika Aryati Setiawati, Elsa Siregar, Syafril Syaifullah Syaifullah Syaifullah Yulianti, Nelvi Zarnelly Zarnelly