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All Journal Journal of Information Systems Engineering and Business Intelligence INFORMAL: Informatics Journal Jutech: Jurnal Teknologi Informasi Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Waradin Sewagati Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat
Rafi, Haris
Bakrie University
Arts Humanities Computer Science & IT Education Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Perbandingan Metode Analytical Hierarchy Process (AHP) dan Himpunan Keanggotaan Fuzzy pada Penilaian Kinerja Dosen Noni Namida Oliviani; Haris Rafi; Mochammad Febri Hariyadi; Nova El Maidah
INFORMAL: Informatics Journal Vol 3 No 2 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i2.9985

Abstract

Utilization of artificial intelligence has been imposed into many things, one of them on the assessment of lecturer's performance, one of them on the lecturer's performance assessment. Artificial intelligence can help and facilitate a person to solve a particular problem. In general, the purpose of lecturer performance assessment is to determine the best lecturer's order through predetermined criteria. Decision Making Method (AHP) and Function Membership Fuzzy is a method often used to determine lecturer performance assessment. There is a method that is a form of calculation whose output is the value of several lecturers who entered the assessment list. The purpose of the comparison is to know which artificial intelligence method is best applied to the lecturer's performance assessment. The method used to test the artificial intelligence applied to the lecturer's performance assessment is to use a comparison scenario. Based on the analysis that has been done, the result that artificial intelligence using AHP method and Membership Sets Fuzzy have balanced result. Based on the document can be concluded that in this study AHP method is a superior method in terms of accuracy, while the Fuzzy method is superior in terms of effectiveness.
Peningkatan Penjualan Produk UMKM Mysneakersby melalui Platform E-Commerce dengan Pendekatan Sistem Dinamik Erma Suryani; Rully Agus Hendrawan; Serra Charisma Viontita; Hanifan Muhayat; Faiq Najib Al-Aziz; Haris Rafi; Achmad Mufliq; Alvisi Aura Chandra
Sewagati Vol 7 No 5 (2023)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v7i5.684

Abstract

Saat ini UMKM terus bersaing dalam memberikan pelayanan yang maksimal. Salah satu upaya dalam memberikan pelayanan dilakukan menggunakan teknologi informasi. Sehingga saat ini teknologi informasi juga digunakan dalam kegiatan promosi hingga perhitungan keuntungan penjualan. Namun saat ini masih terdapat kurangnya pengetahuan pengelolaan teknologi informasi khususnya sosial media dalam pemanfaatannya untuk meningkatkan penjualan produk UMKM. Sehingga pada kegiatan pengabdian masyarakat ini akan mengukur keuntungan UMKM saat ini dengan menggunakan model sistem dinamik dikembangkan dengan menggunakan aplikasi Ventana Simulation (Vensim), dan simulasi dilakukan untuk memvalidasi model yang telah dibangun. Hasil simulasi digunakan untuk menyusun skenario-skenario kebijakan yang dapat mendukung peningkatan penjualan di masa depan. Manfaat dari kegiatan ini termasuk terciptanya modul penggunaan teknologi untuk peningkatan penjualan serta strategi peningkatan penjualan berdasarkan model simulasi sistem dinamik. Dampak yang diharapkan adalah peningkatan penjualan melalui pemanfaatan teknologi sebagai alat bantu dalam mempercepat dan memperluas jangkauan konsumen, serta memberikan rekomendasi strategi yang efektif dalam meningkatkan penjualan bisnis Mysneakersby. Hasil kegiatan pengabdian masyarakat ini menunjukkan bahwa terdapat faktor-faktor yang signifikan yang mempengaruhi tingkat penjualan produk Mysneakersby, yaitu promo, harga produk, keragaman produk, dan pelayanan toko.
Pelatihan Penggunaan Aplikasi Mobile Standar Akuntansi Keuangan Entitas Mikro, Kecil, dan Menengah di Galleries Abata Dita Nurmadewi; Jurica Lucyanda; Anastasya Andriarti; Haris Rafi; Ni Kadek Srimanik; Komang Ayu Sumariasih
Jurnal Pengabdian Masyarakat Waradin Vol. 5 No. 3 (2025): September : Jurnal Pengabdian Masyarakat Waradin
Publisher : Sekolah Tinggi Ilmu Ekonomi Pariwisata Indonesia Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/wrd.v5i3.786

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play an important role in supporting the national economy, yet they still face challenges, particularly in maintaining financial records and reporting in accordance with the Financial Accounting Standards for Micro, Small, and Medium Entities (SAK EMKM). Abata Galleries MSME, as the partner in this activity, previously did not have a structured financial recording system, thus requiring technology-based assistance. This training activity aims to strengthen financial literacy and bookkeeping skills through the use of the KASIU mobile application based on SAK EMKM. The methods applied included a pre-test, material presentation, hands-on practice with the application, a post-test, and an evaluative discussion. The results of the activity indicate a significant improvement in participants’ understanding of SAK EMKM as well as their skills in preparing financial reports in accordance with the standards using the KASIU application. Participants who previously had no knowledge of SAK EMKM are now able to comprehend and implement standardized financial recording. This activity also fostered behavioral changes, particularly the awareness of the importance of maintaining structured daily records, thereby supporting transparency, accountability, and business sustainability.
Model-based Decision Support System Using a System Dynamics Approach to Increase Corn Productivity Suryani, Erma; Rafi, Haris; Utamima, Amalia
Journal of Information Systems Engineering and Business Intelligence Vol. 10 No. 1 (2024): February
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.10.1.139-151

Abstract

Background: As the population increases, the need for corn products also increases. Corn is needed for various purposes, such as food consumption, industry, and animal feed. Therefore, increasing corn production is crucial to support food availability and the food industry. Objective: The objective of this project is to create a model to increase corn farming productivity using scenarios from drip irrigation systems and farmer field school programs. Methods: A system dynamics approach is utilized to model the complexity and nonlinear behaviour of the corn farming system. In addition, several scenarios are formulated to achieve the objective of increasing corn productivity. Results: Simulation results showed that adopting a drip irrigation system and operating a farmer field school program would increase corn productivity. Conclusion: The corn farming system model was successfully developed in this research. The scenario of implementing a drip irrigation system and the farmer field school program allowed farmers to increase corn productivity. Through the scenario of implementing a drip irrigation system, farmers can save water use, thereby reducing the impact of drought. Meanwhile, the scenario of the farmer field school program enables farmers to manage agriculture effectively. This study suggests that further research could consider the byproducts of corn production to increase the profits of corn farmers.   Keywords: Corn Farming, Decision Support System, Modeling, Simulation, System Dynamics
Perbandingan Support Vector Machine dan Naïve Bayes untuk Klasifikasi Sentimen Ulasan E-Commerce: Comparison of Support Vector Machine and Naïve Bayes for E-Commerce Review Sentiment Classification Nurmadewi, Dita; Jailani, Zakiul Fahmi; Rafi, Haris; Anggoro, Dimas Aryo; Setiowati, Dewi
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 2 (2026): MALCOM April 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i2.2648

Abstract

Ulasan pelanggan di platform e-commerce memuat informasi penting tentang pengalaman pengguna terhadap produk dan layanan. Namun, mengingat jumlahnya sangat besar, analisis manual tidak efisien. Klasifikasi sentimen berbasis machine learning dapat secara otomatis mengidentifikasi opini dari teks ulasan. Penelitian ini ingin melakukan perbandingan antara performa Support Vector Machine (SVM) dan Naïve Bayes dalam melakukan klasifikasi sentimen pada ulasan di platform e-commerce. Dataset terdiri atas 11.606 ulasan pelanggan yang bersumber dari repositori dataset publik. Tahap pra-pemrosesan mencakup case folding, tokenization, penghilangan stopword, serta stemming. Fitur teks ditampilkan memakai Term Frequency–Inverse Document Frequency (TF-IDF). Kinerja model dievaluasi berdasarkan skema 5-fold cross-validation menggunakan metrik accuracy, precision, dan recall, serta F1-score. Hasil eksperimen menemukan algoritma Support Vector Machine mempunyai performa lebih unggul jika dibandingkan dengan Naïve Bayes, di mana perolehan nilai accuracy masing-masing mencapai 0.8717 dan 0.8555. Temuan ini sekaligus menunjukkan Support Vector Machine mempunyai kemampuan generalisasi yang lebih baik dalam membedakan kelas sentimen pada data ulasan e-commerce berbasis teks.
Predictive Maintenance Berbasis Machine Learning dalam Smart Manufacturing Haris Rafi
Jurnal Teknologi Informasi (JUTECH) Vol. 6 No. 2 (2025): JUTECH: Jurnal Teknologi Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jutech.v6i2.3333

Abstract

The concept of predictive maintenance represents a significant change in traditional maintenance methods. The use of machine learning in manufacturing machine maintenance has the potential to offer unprecedented opportunities for predicting problems by uncovering hidden patterns in vast data sets. This study aims to examine four machine learning models in classifying maintenance needs in a smart manufacturing environment. Machine learning models such as Logistic Regression, Random Forest, XGBoost, and Multi-layer Perceptrong (MLP) are trained with 5-fold cross-validation. The dataset used is a public dataset from the kaggle website, which consists of 10000 rows and 13 features with the maintenance_required feature as the target feature. The model training results are evaluated using various metrics, such as accuracy, precision, recall, f1-score, and ROC-AUC. The test results show that Random Forest provides the best performance with an accuracy of 98.37%, precision of 99.97%, recall of 91.72%, f1-score of 95.67%, and ROC-AUC of 95.95%. The tree-based ensemble method Random Forest is able to capture patterns in the data better than linear and neural models. This indicates that Random Forest is a reliable model for detecting machine maintenance requirements. Further research can consider increasing dataset capacity, integration with deep learning techniques, examining the perspective of multivariate time-series structures.
Digitalisasi Sistem Buku Tamu Berbasis Perangkat Bergerak bagi Petugas Keamanan Perumahan Dewi Fatmawati Surianto; Haris Rafi; Dewi Fatmarani Surianto; Dary Mochamad Rifqie
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 3 Issue No. 3: June 2026
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v3i3.1712

Abstract

Perkembangan teknologi informasi mendorong transformasi tata kelola administrasi dan sistem keamanan di lingkungan perumahan. Namun, sistem pencatatan tamu di kawasan perumahan umumnya masih mengandalkan buku kertas konvensional. Metode manual ini menimbulkan risiko kerusakan dan kehilangan data, ketidakakuratan informasi, hambatan penelusuran riwayat kunjungan, serta tidak tersedianya pemantauan data secara real-time yang berpotensi memicu celah gangguan keamanan. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan menerapkan teknologi tepat guna berupa aplikasi buku tamu digital berbasis perangkat bergerak (tablet/seluler) bagi petugas keamanan perumahan. Metode pelaksanaan terdiri atas empat tahapan: identifikasi kebutuhan, implementasi dan konfigurasi aplikasi, pelatihan dan pendampingan langsung, serta monitoring dan evaluasi. Evaluasi keberhasilan program diukur menggunakan metode pre-test dan post-test dengan skala Likert 1–5. Hasil evaluasi pre-test menunjukkan efektivitas sistem pencatatan manual, kemudahan pengoperasian, serta kemampuan pengelolaan data berada pada tingkat rendah (skor rata-rata 2,00). Setelah intervensi pendampingan, hasil post-test mengalami peningkatan signifikan pada seluruh indikator: pemahaman pentingnya pencatatan dan sistem digital meningkat sebesar +1,00 menjadi 4,50, efektivitas sistem pencatatan tamu meningkat +2,50 menjadi 4,50 kemudahan pengoperasian media pencatatan meningkat +3,00 menjadi 5,00, kemampuan pengelolaan data dan pencarian riwayat meningkat +3,00 menjadi 5,00, serta kesiapan penerapan sistem secara mandiri meningkat +0,50 menjadi 5,00. Digitalisasi ini terbukti mampu mengoptimalkan efisiensi operasional petugas, meningkatkan ketertiban administrasi, serta memperkuat sistem keamanan lingkungan permukiman secara berkelanjutan.
Co-Authors Achmad Mufliq Alvisi Aura Chandra Amalia Utamima Anastasya Andriarti Dary Mochamad Rifqie Dewi Fatmarani Surianto Dimas Aryo Anggoro Dita Nurmadewi Erma Suryani Erma Suryani Faiq Najib Al-Aziz Hanifan Muhayat Jailani, Zakiul Fahmi Jurica Lucyanda Komang Ayu Sumariasih Mochammad Febri Hariyadi Ni Kadek Srimanik Noni Namida Oliviani Nova El Maidah Nurmadewi, Dita Rully Agus Hendrawan Serra Charisma Viontita Setiowati, Dewi Surianto, Dewi Fatmawati