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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) Voice Of Informatics Jurnal Informasi dan Komputer METIK JURNAL Progresif: Jurnal Ilmiah Komputer E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Journal of Information Systems and Informatics Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pendidikan dan Teknologi Indonesia ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Jurnal Minfo Polgan (JMP) Jurnal Pengabdian Literasi Digital Indonesia Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi)
Kirana, Chandra
ISB Atma Luhur
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Social Sciences Other

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Analisis Efisiensi Waktu Bubble, Insertion, Merge, Dan Quick Sort Menggunakan Python Sutanto, Daniel Septhiady; Chandra, Chandra Kirana; Wahyuningsih, Delpiah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1053

Abstract

Sorting is a fundamental process in data processing that plays an important role in increasing the efficiency of other algorithms. This study aims to conduct a comparative analysis of four classic sorting algorithms: Bubble Sort, Insertion Sort, Merge Sort, and Quick Sort. The comparison is based on three main paRAMeters: Execution time, algorithm Complexity. Testing was carried out experimentally using small to large random Datasets with test scenarios of 100, 150, 300 using the Python progRAMming language. The results showed that Merge Sort is the most efficient algorithm in terms of time because the average time required is 0.000165 seconds.
Implementation of the Complaint Service Application at the Human Resources Bureau Division of the Bangka Belitung District Police Based on Android Pratama, Hafish Mairendra; Kirana, Chandra; Wahyuningsih, Delpiah
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.906

Abstract

Digital transformation in human resource (HR) management within government institutions requires innovative solutions to enhance efficiency and transparency. The HR Bureau Division of the Bangka Belitung Islands Police (Polda Kep. Bangka Belitung) currently faces challenges with its manual complaint management system, leading to delays in grievance handling. This study aims to develop and implement an Android-based complaint service application to facilitate effective reporting and monitoring of complaints. The system development methodology employs the Software Development Life Cycle (SDLC), encompassing planning, requirement analysis, design, implementation, testing, and maintenance phases. The results indicate that the developed application successfully meets user needs with key features such as complaint submission, complaint history, and user guidelines. Blackbox testing confirms that all functions operate as expected. This application is expected to improve accountability and efficiency in the complaint handling process within the HR Bureau Division, while also supporting e-government policies.
Deteksi Anomali Polusi Udara Menggunakan Algoritma Isolation Forest tanpa Label pada Dataset Kualitas Udara Torino Amanda, Reffi; Helmud, Ellya; Kirana, Chandra
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.950

Abstract

Polusi udara merupakan masalah masalah lingkungan yang berdampak langsung pada Kesehatan dan kualitas hidup manusia. Tujuan dari penelitian ini adalah untuk menggunakan algoritma Isolation Forest berbasis Unsupervised Learning, untuk menemukan anomali dalam data kualitas udara dan mengetahui situasi yang tidak normal dengan cepat dan akurat tanpa memerlukan label. Isolation forest dipilih karena efisien dalam menangani data yang besar dan bekerja dengan cepat dalam ruang fitur tinggi dibandingkan dengan algoritma yang lain. Penelitian ini mengimplementasikan algoritma isolation forest untuk dilakukannya identifikasi outlier pada data kualitas udara, khususnya parameter karbon monoksida (CO), nitrogen dioksida (NO?), nitrogen oksida (Nox), dan benzene (C6H6) dari dataset UCI Air Quality. Penelitian ini dilakukan dengan studi literatur, pengumpulan data, preprocessing (pembersihan data dan penanganan nilai hilang), analisis eksploratif, implementasi algoritma, serta visualisasi hasil. Hasilnya, dari total 9357 data, terdeteksi 468 anomali (5%) dengan karakteristik lonjakan nilai ekstrim seperti CO 8.1 mg/m³ dan NO? 187 µg/m³. Visualisasi grafik temporal dan boxplot memperkuat penelitian ini, dengan menunjukkan distribusi anomali yang tersebar. Sehingga, pendekatan ini bisa digunakan sebagai sistem peringatan dini terhadap lonjakan polusi udara yang berbahaya, sehingga berkontribusi dalam sistem monitoring kualitas udara otomatis yang lebih adaptif dan real-time.
Expert System for Early Childhood Talent Detection Using Certainty Factor and Dempster Shafer Algorithms Supardi, Supardi; Kirana, Chandra; Ferdian, Ferdian
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1283

Abstract

Early life is a crucial window for recognizing children’s interests and talents that shape later development. This study implements and compares two reasoning algorithms—Certainty Factor (CF) and Dempster–Shafer Theory (DST)—within a rule-based expert system designed to determine early-childhood interests and talents. Observable “symptoms” (behavior, preferences, and responses to stimuli) are mapped to potential talents, including linguistic, musical, logical-mathematical, and kinesthetic intelligences. The CF module computes confidence values from expert-assigned belief weights, yielding a single interpretable score per talent; the DST module aggregates evidence while explicitly representing uncertainty through basic probability assignments over the frame of discernment. We evaluate both methods in the deployed application with respect to accuracy, decision consistency, and response speed. Results show that, for the representative trait set aligning with linguistic indicators, CF produced the highest agreement with expert judgment 84% confidence while DST assigned 65% mass to the same singleton hypothesis, reserving the remainder for competing hypotheses and ignorance. These findings indicate that CF offers a more decisive signal under congruent evidence, whereas DST contributes caution by quantifying residual uncertainty. Together, the dual approach supports transparent and scalable screening of early talents, enabling caregivers and educators to act when support is strong and seek additional observations when uncertainty persists.
Pengembangan Sistem Web Survei Indeks Kepuasan Masyarakat Pada BAPPERIDA Kota Pangkalpinang anggi rahma anggraini; Delpiah Wahyuningsih; Chandra Kirana
Progresif: Jurnal Ilmiah Komputer Vol 22, No 2 (2026): April
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v22i2.3644

Abstract

This research evaluates the deployment of a web-centered platform designed to assess community satisfaction regarding public services provided by Bapperida in Pangkalpinang City. Prior to this, the survey mechanism relied on traditional methods and lacked digital integration, which led to operational bottlenecks in data handling and constrained data presentation. To address these challenges, this study focuses on designing and deploying an online survey application aimed at streamlining data gathering, processing, and reporting workflows. The methodology employs a Research and Development (R&D) approach using the Waterfall model, encompassing requirements analysis, system architecture design, implementation, and rigorous testing. The developed platform incorporates core functionalities, including digital questionnaire submission, database administration, and automated report generation. The outcomes demonstrate that the proposed system significantly enhances accessibility, operational speed, and accuracy within survey data administration. Furthermore, User Acceptance Testing (UAT) results revealed high user satisfaction scores, confirming that the system is fully viable for supporting public service quality evaluations.Keywords: Community Satisfaction Indeks; Web-Based Survey; Public Service; Information System; User SatisfactionAbstrakEvaluasi terhadap penerapan sistem digital berbasis web dilakukan dalam penelitian ini untuk mengukur sejauh mana kepuasan masyarakat terhadap pelayanan publik pada Bapperida Kota Pangkalpinang. Masalah utama bersumber dari mekanisme survei terdahulu yang masih bersifat manual dan belum terintegrasi secara digital, memicu keterlambatan pemrosesan data serta penyampaian informasi yang terbatas. Oleh karena itu, studi ini diarahkan untuk membangun sekaligus menerapkan sebuah platform survei online yang mampu mengoptimalkan tahapan pengumpulan, manajemen, hingga pelaporan data secara efisien. Pendekatan yang digunakan mengadopsi metode Research and Development (R&D) melalui kerangka kerja Waterfall, yang meliputi fase analisis kebutuhan, perancangan arsitektur, pengodean, hingga pengujian sistem. Aplikasi ini mengintegrasikan fitur-fitur utama seperti pengisian kuesioner daring, manajemen basis data, serta pembuatan laporan otomatis. Temuan penelitian menunjukkan bahwa implementasi platform ini berhasil mendongkrak aspek keteraksesan, efisiensi operasional, dan validitas pengelolaan data hasil survei. Berdasarkan hasil validasi via User Acceptance Testing (UAT), sistem memperoleh respons kepuasan yang sangat positif dari pengguna, menandakan bahwa teknologi ini sangat layak diimplementasikan demi mendukung program evaluasi mutu pelayanan publik.Kata kunci: Indeks Kepuasan Masyarakat; Survei Berbasis Web; Pelayanan Publik; Sistem Informasi; Kepuasan Pengguna
Penerapan Collaborative Filtering dalam Sistem Rekomendasi Berbasis Artificial Intelligence untuk Meningkatkan Personalisasi pada E-Commerce Harry Gentar Alam; Delpiah Wahyuningsih; Chandra Kirana
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16052

Abstract

The rapid growth of e-commerce platforms has led to an explosion in the number of available products, creating a problem of information overload for users. This situation makes it difficult for users to find products that match their personal preferences, thus reducing satisfaction and potential sales conversions. This research aims to develop an Artificial Intelligence (AI)-based recommendation system by implementing the Collaborative Filtering (CF) method to increase personalization. The research approach uses a quantitative descriptive method with a Waterfall-based Software Development Life Cycle (SDLC) system development model. The processed data consists of a user-product interaction matrix (ratings, purchase history) simulated from an e-commerce scenario. A user-based CF algorithm is implemented using cosine similarity calculations and weighted rating predictions. The implementation results show that the system is capable of generating relevant recommendations. In a simulation with a rating matrix (4 users, 6 products), the predicted rating for unrated items reached a value of up to 4.64, with the best recommendation being a product with high preference similarity among users. A simple evaluation yielded a Mean Absolute Error (MAE) of 1.0 on holdout data, demonstrating competitive accuracy compared to similar studies. This system has been shown to enhance the personalization of e-commerce services, potentially improving user experience and transaction volume.
Co-Authors Abdul Holil Agustina Mardeka Raya Amanda, Reffi anggi rahma anggraini Anisah Anisah . Anisah, A Benny Wijaya Burham Isnanto Della Puspita Delpiah Wahyuningsih Devi Irawan Dhita Heru Pambudi Donny Muda Priyangan Edi Sugianto Elly Yanuarti Ellya Helmud ellya helmud, ellya Ferdian, Ferdian Hafiz, Aliy Hamidah . Harry Gentar Alam Irawadi, Syafrul Kiswanto Wanto Lukas Tommy M. Indra Wijaya Melati Suci Mayasari, Melati Suci Okkita Rizan Parlia Romadiana Parlia Romadiana Perkasa, Eza Budi Pradana, Harrizki Arie Pradana, Harrizki Arie Pratama, Hafish Mairendra Rahmat Sulaiman Ramanda Salbiyanti Ricky Tjhin Suci Amalia Arfah Sulaiman, Rahmat - Supardi Supardi Supardi Supardi, S Susanto, Ferry Sutanto, Daniel Septhiady Vivi Lindawati Wahdaniyah, Risti Yongkie Setiawan