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All Journal JUSIFO : Jurnal Sistem Informasi Sistemasi: Jurnal Sistem Informasi Tech-E JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal Journal of Social Science Jurnal Teknik Informatika (JUTIF) Jurnal Abmas Negeri (JAGRI) Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Jurnal Algoritma Journal of Social Science IWJ : Inland Waterways Journal ITIJ The Indonesian Journal of Computer Science Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat
Nouval Trezandy Lapatta
Universitas Tadulako
Religion Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Social Sciences Transportation Other

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Analysis of the Use of MTCNN and Landmark Technology to Improve the Accuracy of Facial Recognition on Official Documents Chandra, Ferri Rama; Ngemba, Hajra Rasmita; Hamid, Odai Amer; Lapatta, Nouval Trezandy; Hendra, Syaiful; Nugraha, Deny Wiria; Syahrullah, Syahrullah
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8814

Abstract

A face recognition system consists of two stages: face detection and face recognition. Detection of features such as eyes and mouth is important in facial image processing, especially for official documents such as identity cards. To ensure identification accuracy, this research applies facial landmark extraction technology and MTCNN (Multi-Task Cascaded Convolutional Neural Network). The purpose of this research is to evaluate the accuracy of MTCNN in detecting facial features at the Department of Population and Civil Registration (dukcapil) Palu City, using facial landmarks and waterfall methods as an application development methodology. The evaluation results show that MTCNN has high face recognition accuracy and good positioning ability regardless of what GPU in use as long have right CPU and System Operation. In comparison, the Viola-Jones algorithm is effective for high-speed applications, while SSD offers balanced performance with GPU device requirements for optimal performance. While MTCNN proved to be effective, challenges still exist, such as false positives and false negatives, especially in poor lighting conditions and extreme poses. Image and camera quality, including resolution and facial expression, also affects detection accuracy. These findings suggest that the application of MTCNN can improve face recognition accuracy for official documents, although it requires addressing existing challenges. With this technology, it is expected that errors in facial recognition can be minimized, resulting in more reliable data that meets the standards for issuing identity documents. This research contributes to the development of a more accurate and efficient face recognition system for personal identification applications.
Optimization of Urban Waste Collection Routes Using the Held-Karp Algorithm in a Web and Mobile-Based System Arsita, Tiara Juli; Lapatta, Nouval Trezandy; Joefri, Yuri Yudhaswana; Angreni, Dwi Shinta; Pratama, Septiano Anggun
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8832

Abstract

In 2023, the Environmental Agency of Palu City recorded a total waste production of 97,492 tons, of which 10.4% was plastic waste. The Palu City Government operates a fleet of garbage trucks on a predetermined collection schedule. However, garbage bins frequently overflow before their scheduled pickup, resulting in extended waste accumulation and inefficiency. This study proposes a web and mobile-based system to enhance waste management by integrating bin condition reporting and shortest route calculation for collecting full bins. The Held-Karp algorithm is utilized to address the Travelling Salesman Problem (TSP) for determining optimal collection routes. The system was developed using Golang, Flutter, ReactJS, and a MySQL database. API functionality was validated using Postman, and overall system functionality was tested using the black-box method. A case study involving 8 test points (1 starting point, 10 waste collection points, and 1 endpoint) demonstrated that the proposed system reduces travel time by up to 21.74%, costs by 22.29%, fuel consumption by 21.16%, and distance traveled by 21.16% compared to conventional methods. These results highlight the potential of the system to significantly optimize waste collection operations and support sustainable urban waste management practices.
KLASIFIKASI JENIS KAYU BERDASARKAN CITRA SERAT KAYU MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Dwimanhendra, Muhammad Rifaldi; Syahrullah, Syahrullah; Joefrie, Yuri Yudhaswana; Angreni, Dwi Shinta; Azhar, Ryfial; Nugraha, Deny Wiria; rezandy Lapatta, Nouval; Najar, Abdul Mahatir
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5726

Abstract

Kayu merupakan sumber daya alam yang sangat penting bagi industri mebel atau furnitur. Pemilihan jenis kayu yang tepat sangat krusial dalam industri mebel untuk menentukan kualitas hasil produksi. Pemilihan kayu secara manual memiliki risiko kesalahan yang dapat berdampak negatif pada kualitas akhir produk mebel. Oleh karena itu, diperlukan penerapan teknologi untuk meminimalkan kesalahan pemilihan jenis kayu dan meningkatkan efisiensi proses produksi. Penelitian ini bertujuan membangun model klasifikasi jenis kayu (nantu, palapi, dan uru) berbasis Convolutional Neural Network (CNN) menggunakan citra serat kayu. Dataset terdiri dari 1.584 citra yang dibagi menjadi 80% data pelatihan dan 20% data pengujian. Arsitektur model CNN terdiri dari 4 lapisan konvolusi, 4 lapisan pooling, dan 2 lapisan fully-connected. Hasil pelatihan mencapai akurasi 97,06%, sedangkan hasil pengujian dan evaluasi menggunakan matriks konfusi mencapai akurasi 95,56%. Penelitian ini membuktikan bahwa CNN dapat digunakan secara efektif untuk klasifikasi jenis kayu dengan tingkat akurasi yang tinggi, sehingga dapat membantu meningkatkan efisiensi proses produksi mebel.
DESIGN OF QUEUING SYSTEM USING PRIORITY QUEUE ALGORITHM AND MULTI CHANNEL MULTI PHASE METHOD AT WEBSITE-BASED PATIENT REGISTRATION SECTION (CASE STUDY OF DONGGALA HEALTH CENTER) Anita, Ayu; Ardiansyah, Rizka; Lapatta, Nouval Trezandy; Angreni, Dwi Shinta; Laila, Rahmah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6290

Abstract

This research was conducted to regulate the queuing process which is often longer than the service standards set in the Decree of the Minister of Health Number 129 / Menkes / SK / II / 2008 stipulates that the waiting time for outpatients is equal to 60 minutes or less than 60 minutes, This study aims to design and build a website-based electronic queuing system at Puskesmas Donggala using the Priority Queue algorithm and the Multi Channel Multi Phase method. This system is designed to improve the efficiency of patient registration by reducing waiting time and providing priority for patients with emergency conditions. The research method includes data collection through observation and interviews, as well as system testing through simulation. The results show that the proposed system can reduce waiting time and increase patient satisfaction. The implementation of this system is expected to provide an effective solution to queuing problems in health facilities.
Implementasi Algoritma Rivest-Shamir-Adleman (RSA) pada Sistem Monitoring Potensi Bahaya dan Kecelakaan Kerja di PT Citra Palu Minerals Darojah, Murtafiatun; Lapatta, Nouval Trezandy; Azhar, Ryfial; Angreni, Dwi Shinta; Laila, Rahmah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6241

Abstract

Penelitian ini berfokus pada pembuatan sistem yang dapat memonitoring potensi bahaya kecelakaan kerja di PT Citra Palu Minerls, membuat arsip data perlaporan lebih administratif dan keamanan pada data pribadi pelapor. Penelitian ini bertujuan untuk mempermudah dalam pembuatan pelaporan potensi bahaya kecelakaan kerja serta implementasi algoritma RSA pada sistem. Penelitian ini menggunakan metode kualitatif dengan observasi, wawancara, dan dokumentasi. Penelitian ini melibatkan wawancara dengan Kepala Departemen Health, Safety, and Environment (HSE), Departemen Elektrik, dan beberapa karyawan yang ada di PT Citra Palu Minerals sebagai gambaran yang akurat sesuai kebutuhan pengguna. Sistem monitoring ini bernama HIAS (Hazard Information and Suggestion) dibuat menggunakan bahasa pemrograman React js membangun antarmuka pengguna (UI) dan Express js sebagai perancang sistem atau logika back-end pada aplikasi. Hasil pengujian menggunakan metode EUCS untuk menunjukkan tingkat ketidakpuasan sebelum adanya sistem monitoring dengan skor rata-rata 1,58. Sementara itu, untuk pengujian tingkat kepuasan setelah sistem monitoring, dengan skor rata-rata 4,6. Hal ini menunjukkan bahwa setelah adanya sistem monitoring, keberhasilan dalam membangun sistem ini sesuai dengan kebutuhan dan permasalahan yang ada.
Interaksi Augmented Reality Menggunakan Boxcollider Dalam Aplikasi Pembelajaran Bahasa Inggris Zulkifli, Zulkifli; Joefrie, Yuri Yudhaswana; Nugraha, Deny Wiria; Lapatta, Nouval Trezandy; Syahrullah, Syahrullah; Angreni, Dwi Shinta
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6248

Abstract

Teknologi Augmented Reality (AR) telah menjadi salah satu inovasi terdepan dalam meningkatkan pengalaman belajar interaktif. Penelitian ini mengkaji penggunaan AR dalam aplikasi pengenalan bahasa Inggris dengan memanfaatkan fitur BoxCollider untuk interaksi pengguna. Ap-likasi ini dirancang untuk membantu pengguna, terutama pelajar, dalam mengenali dan memahami kosakata bahasa Inggris melalui pengalaman visual dan interaktif. BoxCollider digunakan untuk mendeteksi interaksi antara pengguna dan objek virtual yang ditampilkan di layar, memung-kinkan respons langsung terhadap tindakan pengguna seperti menyentuh atau menggerakkan objek. Hasil penelitian menunjukkan bahwa penggunaan BoxCollider dalam AR meningkatkan keterlibatan pengguna dan memudahkan proses belajar. Pengguna dapat berinteraksi dengan berbagai objek yang mewakili kata-kata bahasa Inggris, sehingga mem-berikan konteks visual yang kuat dan mendukung pemahaman kosakata secara lebih efektif. Aplikasi ini diharapkan dapat menjadi alat bantu yang efektif dalam pengajaran bahasa Inggris, menawarkan metode bela-jar yang lebih menarik dan interaktif dibandingkan dengan metode kon-vensional
IMPLEMENTASI SVM DAN SMOTE PADA ANALISIS SENTIMEN MEDIA SOSIAL X TERHADAP PELANTIKAN AGUS HARIMURTI YUDHOYONO Fajriyah, Nurul; Lapatta, Nouval Trezandy; Nugraha, Deny Wiria; Laila, Rahmah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6246

Abstract

Pelantikan Agus Harimurti Yudhoyono sebagai Menteri Agraria dan Tata Ruang/Badan Pertanahan Nasional (ATR/BPN) telah memicu berbagai reaksi publik yang terekam dalam media sosial X. Penelitian ini bertujuan untuk menganalisis sentimen publik terhadap pelantikan tersebut menggunakan algoritma Support Vector Machine (SVM) dan teknik Synthetic Minority Oversampling Technique (SMOTE). Data yang digunakan dalam penelitian ini diambil dari komentar masyarakat di media sosial X, yang kemudian diolah untuk membedakan antara sentimen positif, negatif, dan netral. Dalam proses analisis, data awal yang diperoleh cenderung tidak seimbang, dengan jumlah data sentimen negatif yang lebih banyak dibandingkan dengan sentimen positif dan netral. Oleh karena itu, teknik SMOTE diterapkan untuk mengatasi ketidakseimbangan kelas dan meningkatkan performa model. Algoritma SVM kemudian digunakan untuk melakukan klasifikasi sentimen. Hasil penelitian menunjukkan bahwa model SVM yang diimbangi dengan SMOTE memiliki tingkat akurasi yang tinggi dalam mengklasifikasikan sentimen publik dibandingkan dengan model tanpa SMOTE dengan akurasi sebesar 0.93, presisi sebesar 0.93 dan recall sebesar 0.93.
E-SKHBK untuk Optimalisasi Pemutusan Hubungan Kerja di PT Sumber Alfaria Trijaya Tbk: Optimizing Termination of Employment: Implementation of Personal Extreme Programming and Evaluation of EUCS PIECES Adhira Putri, Dhivanny; Trezandy Lapatta, Nouval
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2248

Abstract

For 24 years of operation, Alfamart has always upheld the company’s values to provide customer satisfaction. However, efforts to manage human resources as the main asset are needed to support the company’s values in achieving its goals. One of the crucial aspects in this effort is the Personnel Division, which is responsible for employee administration. Unfortunately, the process of terminating employment is still done manually and conventionally. This research explores the development of the Employment Termination Letter (e-SKBHK) website as a solution to optimize the termination process by enhancing efficiency, minimizing paper usage, and ensuring letter security through QR codes. The website development is carried out using the Personal Extreme Programming method, adapted from Extreme Programming but tailored for a single developer. This website development uses PHP language with Laravel 10 framework that applies Model View Controller architecture pattern. The test results using the EUCS method show that users are satisfied with the website developed with an average score of 4.3. While testing with the PIECES method shows a significant increase from a score of 1.96 on the current mail management system to 4.07 on the developed website. This confirms the successful implementation of the website in the aspects of performance, information, economy, control, efficiency, and service in mail management.
Penerapan Algoritma K-Means Clustering Dalam Pengelompokkan Kepadatan Penduduk: Application of K-Means Clustering Algorithm in Population Density Grouping Delia, Fenita; Rasmita Ngemba, Hajra; Hendra, Syaiful; Syahrullah, Syahrullah; Trezandy Lapatta, Nouval
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2270

Abstract

Uneven population density will have a negative impact if not considered. One way to tackle this problem is with population equity management planning policies. This research focuses on clustering population density areas, which is the ratio between population and area in Central Sulawesi Province. This research clustering is applied with data mining techniques, namely K-Means Clustering. The research stages are data collection, data understanding, data processing, clustering, clustering review, dashboard analysis, and accuracy testing with the tableau application in providing visualization of population density in the region. Based on the results of the algorithm calculation, it produces three clusters, cluster 0 being low population density, cluster 1 being high population density, and cluster 2 being medium population density. Cluster formation is based on the visualization produced by the research dataset through Sum Of Square Error analysis, silhouette coefficient, and elbow method. Clustering is formed, followed by dashboard visualization with the tableau application. The clustering results, based on the SSE calculation, produce a value of 4324505738.747303, meaning the determination of the number of clusters with a significant difference with the calculation of the number of previous groupings. Then the results of the silhouette analysis provide the highest average silhouette value at the number of clusters, namely 3 with a value of 0.6144435666457168, and the elbow method gives the result that the elbow point is at point 3, meaning the optimum number of clusters with 3 clusters.
Rancang Bangun Aplikasi Diagnosa Sexually Transmitted Diseases Menggunakan Algoritma Certainty Factor Mandra; Nouval Trezandy Lapatta; Syaiful Hendra; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.4293

Abstract

This research aims to design and develop an Android application that can be used to diagnose results Sexually Transmitted Diseases using algorithms Certainty Factor. Sexually Transmitted Diseases is a sexually transmitted disease that can cause serious health impacts if not immediately identified and treated appropriately. This application is designed to help users carry out initial diagnoses independently. The method used in developing this application is the Certainty Factor algorithm, which is a rule-based decision support method. This algorithm utilizes knowledge from experts in the medical field and combines it with symptom data provided by users to produce more accurate diagnoses. The app will allow users to input suggested symptoms and generate a diagnosis based on that information. It is hoped that this application will be a useful tool in a self-directed approach to diagnosis Sexually Transmitted Diseases.
Co-Authors ., Rezki Abdillah Sani, Ilham Abdul Mahatir Najar Abdullah Abdullah Adhira Putri, Dhivanny Agung Stiven Cahyati Angely Ain, Moch. Zukhruf Amriana Amriana Amriana Amriana Andhyka, Andhyka Andi Hendra Andi Hendra Angraeni, Dwi Shinta Anita Ahmad Kasim Anita, Ayu Arsita, Tiara Juli Ar Lamasitudju, Chairunnisa Asriani Asriani, Asriani Ayu Hernita Ayu Hernita Bakri Chairunnisa Ar. Lamasitudju Chandra, Ferri Rama Darojah, Murtafiatun Delia, Fenita Deni Luvi Jayanto Deny Wiria Nugraha Dessy Santi Djohari, Riyandi Dwitama Dwi Shinta Angreni Dwimanhendra, Muhammad Rifaldi Fahlevi, Mohammad Fazrin Fajar, Moh Fajriyah, Nurul Faldiansyah, Faldiansyah Firzatullah, Raden Muhamad Hajra Rasmita Ngemba Hamid, Odai Amer Hanama, Ikhsan Wahyudin Ihalauw, Sahron Angelina Ihwan, Abib Raifmuaffah Karnita Sumbaluwu, Harlin Feby Kartika, Rina Laila, Rahma Lamadjido, Moh. Raihan Dirga Putra Lamasitudju, Chairunnisa Mandra Maulana, Muhammad Syahputra Mohamad Irfan, Mohamad Mohammad Yazdi Pusadan Muhammad Akbar Muhammad Akbar Mutiara Sari Ngemba, Hajra Ningsih, Alief Surya Noel Marcell Jonathan Wongkar Noviantika, Noviantika Nurhikmah Supardi Nursiana Zasqia, Andi Nirina Pagiu, Harry T. Priska, Salsa Dilah Putra, Adhitya Pramana Qofifa, Sitti Nurlaili Rahmah Laila Rasmita Ngemba, Hajra Rasmita, Hajra Rasyid, Muh. Ashari Rinianty Rinianty Rinianty, Rinianty Rizka Ardiansyah Rizky, Moh Taufiq Ryfial Azhar Ryfial Azhar, Ryfial Saada, Rahmadian A. Sabarudin Saputra Saputra, Sabaruddin Septiano Anggun Pratama Setiawan, Dita Widayanti Siti Rahmawati Sri Khaerawati Nur Sukirman Sukirman Syahrullah Syahrullah Syahrullah Syahrullah Syahrullah Syaiful Hendra Wirdayanti Wirdayanti Wirdayanti Wongkar, Noel Marcell Jonathan Yanti, Wirda Yudhaswana, Yuri Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli