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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Annual Research Seminar Journal of Information Technology and Computer Science INTEGER: Journal of Information Technology AkMen JURNAL ILMIAH Jurnal Riset Informatika JSAI (Journal Scientific and Applied Informatics) Jurnal Pengabdian Masyarakat Bumi Raflesia Jurnal Sistem Komputer dan Informatika (JSON) Journal Informatic, Education and Management (JIEM) Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS The Indonesian Journal of Computer Science Buffer Informatika
Ali Ibrahim
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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SISTEM PEMBELAJARAN DENGAN E-LEARNING UNTUK PERSIAPAN UJIAN NASIONAL PADA SMA PUSRI PALEMBANG Nyimas Sriwihajriyah; Endang Lestari Ruskan; Ali Ibrahim
Jurnal Sistem Informasi Vol 4, No 1 (2012)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1152.76 KB) | DOI: 10.36706/jsi.v4i1.941

Abstract

AbstrakE-learning merupakan suatu jenis belajar mengajar yang memungkinkan tersampaikannya bahan ajar ke siswa dengan menggunakan media Internet, Intranet atau media jaringan komputer lain. Saat ini konsep E-learning sudah banyak diterima oleh masyarakat dunia, terbukti dengan maraknya implementasi E- Learning di lembaga pendidikan (sekolah, training dan universitas) maupun industri (Cisco System, IBM, HP, Oracle, dsb). Pengembangan E-learning tidak semata-mata hanya menyajikan materi online saja, namun harus komunikatif dan menarik. Materi pelajaran didesain seolah peserta didik belajar di hadapan pengajar melalui layar komputer yang dihubungkan melalui jaringan internet. Dengan adanya sistem aplikasi E-learning berbasis online ini maka akan membantu para siswa dan guru dalam belajar mengajar bisa efektif dan efisien dimana para siswa dan guru tidak harus bertatap muka atau langsung datang kesekolah untuk latihan soal dan bimbingan belajar akan tetapi bisa menggunakan aplikasi berbasis online ini di luar lingkungan sekolah. Penelitian ini bertujuan untuk membantu belajar para siswa karena terdapat beberapa fungsi diantaranya download materi, mengerjakan latihan, ujian dan dapat berkomunikasi langsung dengan guru melalui forum diskusi, sehingga para siswa tidak perlu lagi belajar dengan cara konvensional karena semua data yang dibutuhkan oleh siswa sudah disediakan. E-learning ini dibangun dengan menggunakan bahasa pemrograman PHP dengan didukung basis data MySQL.Kata kunci: WAP, Sistem Informasi, Perpustakaan Digital
Analisis Pengaruh Strategi Konten Sosial Media Terhadap Aplikasi Layanan Streaming Khairunnisa; Dedy Kurniawan; Ali Ibrahim; Endang Lestari Ruskan
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3597

Abstract

Social media marketing is becoming a key strategy for streaming applications. This study analyzes the content strategy of the Instagram account @Netflixid and its impact on customer loyalty. The study uses a quantitative approach with an online survey as a data collection method and Structural Equation Modeling (SEM)-Partial Least Squares (PLS) as a research method. The results show that content that reflects the behavior of followers and is animated is preferred by Netflixid audiences. This content strategy also has a positive impact on customer loyalty.
PELATIHAN PENINGKATAN PENGUASAAN TEKNOLOGI INFORMASI DIGITAL GUNA MASYAKARAT MARIANA ILIR Ali Ibrahim; Ermatita, Ermatita; Abdiansah, Abdiansah; Ahmad Fali Oklilas; Al Farissi; Rizka Dhini Kurnia; Afrina, Mira; Utama, Yadi
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 2 No. 1 (2024): Februari
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v2i1.237

Abstract

Mariana Ilir merupakan salah satu kelurahan yang ada di kecamatan Banyuasin I yang mempunyai potensi yang cukup besar untuk dikembangkan, namun selama ini penggunaan teknologi informasi dalam penyebaran informasi masih belum dapat dimanfaatkan secara optimal dikalangan pemerintahan khususnya di pedesaan, hal ini disebabkan karena terbatasnya sarana dan prasarana serta sumber daya manusia yang memiliki kemampuan dan keahlian dibidang ilmu komputer dan teknologi informasi. Pada kegiatan ini akan dilaksanakan sesuai dengan kesepakatan antara tim pelaksana dengan kelurahan mariana ilir. Khalayak yang akan ikut dalam kegiatan ini berjumlah 20 orang. Kegiatan PkM akan dilaksanakan secara luring. Hasil yang di harapkan dari kegiatan Pk adalah bertambahnya keterampilan apparat kelurahan dan masyarakat tentang IT. Selaian itu PkM ini memiliki luaran seperti Lapoaran PkM dan Publikasi karya ilmiah pada jurnal nasional. Kegiatan PkM Peningkatan Keterampilan Teknologi Informasi Digital Untuk Masyakarat dan Aparat Kelurahan Mariana Ilir Kecamatan Banyuasin Ilir, Kabuaten Banyuasin Sumatra Selatan terlaksana sesuai dengan rencana yang sudah disepakati oleh tim pelaksana dengan tim pelaksana dari kelurahan. Peserta sangat antusias dengan mengikuti kegiatan PkM, Harapan peserta untuk tetap diadakan kegiatan Kembali tahun selanjutnya.
Mengungkap Hubungan Antara Infrastruktur Layanan Publik dan Kinerja Pemerintah Daerah di Indonesia Muhamad Lutfi Azizan; Septiano Alvian Ismau; Rizki Artinio Permana Putra; Putri Amalia; Ali Ibrahim; Zurnan Alfian
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 5 No. 3 (2025): November: Jurnal Ilmiah Teknik Informatika dan Komunikasi 
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v5i3.1368

Abstract

Local government performance and the availability of public service infrastructure are two important indicators in assessing the success of regional development. This study aims to examine the relationship between the number of post offices as an indicator of public service infrastructure and the performance scores of provincial governments in Indonesia. The data used are from the 2007 Transportation Statistics (number of post offices per province) and the 2016 Ministry of PAN-RB report (local government performance scores). The results of the analysis indicate that provinces with better public service infrastructure tend to have higher government performance scores. Although not all correlations are strong and significant, these findings indicate the importance of equal infrastructure to support effective governance.
Implementasi Algoritma K-Means Dalam Analisis Distribusi Pangkalan LPG 3kg Di Kota Palembang Shofi Salsabila; Fathoni; Mutia Sahira; Adella Salsabila; Aulia Najibah Putri; Ali Ibrahim
Buffer Informatika Vol. 11 No. 2 (2025): Buffer Informatika
Publisher : Department of Informatics Engineering, Faculty of Computer Science, University of Kuningan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/buffer.v11i2.385

Abstract

Pada 1 Februari 2025, pemerintah Indonesia menetapkan kebijakan pembatasan distribusi LPG 3 kg yang hanya boleh disalurkan melalui pangkalan resmi. Kebijakan ini bertujuan agar subsidi tepat sasaran, tapi juga menimbulkan kekhawatiran soal akses, terutama di wilayah padat dan pinggiran kota seperti Palembang. Penelitian ini menganalisis dampak kebijakan tersebut terhadap aksesibilitas LPG 3 kg serta mengelompokkan kecamatan berdasarkan kecukupan jumlah pangkalan menggunakan algoritma K-Means. Data yang digunakan meliputi jumlah pangkalan LPG dari MyPertamina dan data penduduk dari BPS periode 2019–2021. Setelah data dibersihkan dan dinormalisasi, dilakukan eksplorasi dan implementasi K-Means untuk mengidentifikasi kecamatan dengan distribusi pangkalan yang kurang, cukup, atau berlebih. Hasil clustering menunjukkan bahwa beberapa kecamatan padat seperti Sukarami memiliki rasio pangkalan yang belum ideal dibandingkan jumlah penduduknya, sehingga perlu perhatian khusus dalam perencanaan distribusi. Penelitian ini menunjukkan bahwa penerapan algoritma machine learning seperti K-Means dapat membantu pengambilan keputusan berbasis data untuk mendukung distribusi subsidi LPG yang lebih merata dan efisien.
Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode AHP dan TOPSIS Nyimas Diah Permata Sari; Ali Ibrahim; Fathoni
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9359

Abstract

Evaluasi kinerja karyawan memegang peranan penting dalam menentukan kualitas sumber daya manusia suatu perusahaan. Namun, metode evaluasi manual seringkali subjektif dan memakan waktu, sehingga menghasilkan hasil yang kurang akurat. Untuk mengatasi keterbatasan tersebut, penelitian ini mengembangkan Sistem pendukung keputusan untuk memilih karyawan terbaik dengan mengintegrasikan Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Metode AHP digunakan untuk memberikan nilai bobot pada setiap kriteria evaluasi, sedangkan TOPSIS diterapkan untuk memeringkat karyawan berdasarkan kedekatannya dengan solusi positif dan negatif yang ideal. Kriteria evaluasi tersebut meliputi kinerja, loyalitas, disiplin, kerja sama tim, dan jumlah tugas yang belum selesai. Hasil pengujian menunjukkan bahwa Consistency Ratio sebesar 0,0834 (<0,1), yang menunjukkan bahwa proses pembobotan telah konsisten. Berdasarkan perhitungan, karyawan dengan nilai preferensi tertinggi adalah Salma Nurhaliza, dengan skor 0,842882. Studi ini menunjukkan bahwa integrasi metode AHP dan TOPSIS dapat menghasilkan hasil evaluasi yang lebih objektif, tepat, dan efisien, menjadikannya alat yang dapat diandalkan bagi perusahaan untuk menentukan karyawan terbaik secara transparan dan terukur.
Analysis of E-Commerce and Fintech Trends in the Digital Economy Ecosystem Redha Bayu Anggara; Asyrof Fitrah; Ali Ibrahim; Mira Afrina
Journal Informatic, Education and Management (JIEM) Vol 8 No 1 (2026): FEBRUARY (CALL FOR PAPERS)
Publisher : STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61992/jiem.v8i1.249

Abstract

The rapid expansion of e-commerce and fintech has significantly shaped the digital economy ecosystem in Indonesia. This study analyzes key trends, behavioral patterns, and the evolving dynamics within these sectors as digital adoption continues to accelerate. The increasing volume and complexity of digital transactions demand advanced analytical approaches capable of identifying hidden patterns and potential anomalies. To address this need, the study employs a Convolutional Neural Network (CNN) model to extract deep feature representations from transaction data and classify emerging behavioral trends. The proposed method demonstrates strong accuracy, achieving 91.25%, indicating its ability to capture non-linear relationships that traditional methods often overlook. The findings highlight several major trends, including shifting consumer behavior, increasing transaction frequency, and the growing prominence of digital financial services. Practically, this research provides valuable insights for enhancing risk mitigation, fraud detection, and real-time monitoring in digital platforms. Academically, it contributes to the understanding of deep learning applications in digital economic analysis and opens avenues for further research on hybrid models and multi-source data integration within the digital economy ecosystem.
Sentiment Analysis of JMO Application Reviews on the Google Play Store Using BERT Hendi Putra Wijaya; Adhityah Anugrah; Mira Afrina; Ali Ibrahim
Journal Informatic, Education and Management (JIEM) Vol 8 No 1 (2026): FEBRUARY (CALL FOR PAPERS)
Publisher : STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61992/jiem.v8i1.250

Abstract

The development of digital technology has encouraged increased use of online-based public service applications, including the JMO (Jamsostek Mobile) application developed by BPJS Ketenagakerjaan to provide easy access for its participants. This application has received many user reviews on the Google Play Store, reflecting the level of satisfaction and public perception of service quality. However, the large and unstructured volume of comments makes manual analysis difficult. This study aims to conduct sentiment analysis on user comments about the JMO application on the Play Store using the Bidirectional Encoder Representations from Transformers (BERT) model. The research method involves collecting comments through web scraping, text preprocessing (such as data cleaning, normalization, and tokenization), and sentiment labeling (positive, negative, and neutral). Evaluation using precision, recall, and F1-score is employed to describe the results. The study is expected to identify patterns of user sentiment and public perceptions of the JMO application. It is also expected to serve as an evaluation material and input for developers to improve service quality and user experience.
Analisis Sentimen Aplikasi MPStore Menggunakan Algoritma Logistic Regression dan LDA Tia Arlin Dita; Ali Ibrahim; Rizka Rahmadhani; Mira Afrina
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9557

Abstract

The rapid growth of the digital economy encourages user satisfaction as the key to successful application innovation. Within technopreneurship, understanding user sentiment is essential for sustainable product development. This study aims to analyze sentiment and identify the deter-minants of user satisfaction regarding the MPStore application based on reviews from the Google Play Store. Review data were collected via scraping and analyzed using Logistic Regression (LR) for sentiment classification (positive, negative, neutral) also Latent Dirichlet Al-location (LDA) for satisfaction topic extraction. The result shows that the LR model achieved an accuracy of 88.5%. The LDA analysis also successfully revealed eight main topics, includ-ing ease of use, transaction speed, and technical obstacles (errors, login, balance issues). Over-all, a majority of users hold a positive perception of MPStore's efficiency and ease of transac-tions. This study concludes that the combination of sentiment analysis and topic modeling is effective for explaining the level of user satisfaction and providing a strategic foundation for digital application developers.
The Sentiment Analysis Of Indonesian Startup Application Reviews Using TF-IDF+SVM and FastText: A Comparative Study Aini Nabilah; Nurlayli Indah Sari; Mira Afrina; Ali Ibrahim
Journal of Information Technology and Computer Science Vol. 10 No. 3: Desember 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025103807

Abstract

The rapid rise of startups in Indonesia makes user reviews on the Google Play Store a valuable data source for understanding user perceptions and satisfaction. These unstructured reviews contain insights supporting product development and business strategies. This study analyzes sentiments in Indonesian startup app reviews and compares two classification methods: TF-IDF + Linear SVM and fastText, implemented using Google Colab. Reviews were collected in September 2025 using google-play-scraper; 4,000 reviews were retrieved and refined into 3,152 unique reviews after cleaning and preprocessing. Sentiment labeling used ratings (1–2 negative, 4–5 positive); because the neutral class was limited, this study focuses on balanced binary classification with 1576 positive and 1576 negative reviews. The process involves data scraping, text preprocessing, model training, and evaluation using accuracy, precision, recall, and F1-score metrics, with Linear SVM chosen as an efficient baseline for high-dimensional sparse TF-IDF features. Results show that fastText achieves 91.88% accuracy and an F1-macro of 0.9184, slightly outperforming TF-IDF + SVM (F1-macro 0.9103), suggesting that the embedding-based approach better captures semantic nuances of Indonesian text. Future work may extend this study to ABSA to assess sentiments toward price, UI/UX, and customer service for deeper technopreneurship insights in Indonesia.
Co-Authors Abdiansah, Abdiansah Adella Salsabila Adhityah Anugrah Ahmad Fali Oklilas Aini Nabilah Akbar Al Zaini Al Farissi Albert Amadeus Valentino Ali Bardardi Alya Nurseptiani Andi Marlinah Apriansyah Putra - Asyrof Fitrah Aulia Najibah Putri Beriadi Agung Nur Rezqe Dwi Citra Hartini Dwi Rosa Indah Endang Lestari Ruskam Endang Lestari Ruskan Endang Lestari Ruskan Ermatita - Fathoni Fathoni - Hedi Yunus Hendi Putra Wijaya Jaidan Jauhari Ken Dihta Tania Khairunnisa Larasathi Jiwany Lay Kodri MGS. Afriayan Firdaus Michelle Liu Mira Afrina Muhamad Lutfi Azizan Muhammad Farisan Zhafiri Mutia Sahira Nadya Angelia Nurlayli Indah Sari Nyimas Diah Permata Sari Nyimas Sriwihajriyah Ovi Dyantina Putri Amalia Rafika Maulindah Redha Bayu Anggara RIA ANGGRAINI Rizka Dhini Kurnia Rizka Rahmadhani Rizki Artinio Permana Putra Ruth Christin Aprilia Situmorang Salsabila, Unik Hanifah Septiano Alvian Ismau Shofi Salsabila Tia Arlin Dita Tumpol S Simarmata Vira Putri Rahmadini Wira Islamiansyah Yadi Utama Yadi Utama Yadi Utama, Yudha Pratomo Zurnan Alfian