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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA IKRA-ITH Informatika : Jurnal Komputer dan Informatika Building of Informatics, Technology and Science Jurnal Mantik JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi
Chusna, Nuke L
Universitas Krisnadwipayana
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary

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Vehicle Counter in Traffic Using Pixel Area Method with Multi-Region of Interest Fachri, Moch; Hikmah, Nur; Chusna, Nuke Lu'lu ul
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3264

Abstract

Traffic density data plays an important role in decision making by the Intelligent Transportation System (ITS). This system uses this data in the process of adaptive traffic management. The inaccuracy of the data provided into the ITS system can result in errors in decision making. This study utilizes digital image engineering technology in the detection of four-wheeled vehicles in traffic traffic for the purpose of acquiring traffic density data. In this study, we propose a multi-ROI (pixel area methodRegion of Interest). This multi-ROI proposal is to be put forward to improve reading accuracy compared to just one ROI. With the use of this multi-ROI, the information obtained from the overall ROI can strengthen the accuracy of the data of vehicles passing in a lane. Our experimental results show that the use of multi-ROI with a certain amount of ROI can produce an accuracy rate of up to 88.66% compared to single-ROI which has an accuracy rate of 84.65%.
Implementasi Metode TOPSIS untuk Menentukan Karyawan Terbaik Berbasis Web Pada PT. Mun Hean Indonesia Andrian Muljadi; Ali Khumaidi; Nuke L Chusna
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 2, August 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2020.v08.i02.p04

Abstract

Dalam penentuan karyawan terbaik menjadi hal yang sulit bagi setiap perusahaan dikarenakan dalam melakukan penilaian harus berlandaskan kepada kriteria yang telah disetujui oleh masing-masing perusahaan. Banyak ditemukan pada saat penentuan karyawan terbaik kendala yang dialami adalah melakukan penilaian absensi saja tanpa melihat kriteriakriteria lain yang ada. Permasalahan pada PT. Mun Hean Indonesia adalah sulitnya pengambilan keputusan yang dilakukan secara manual mengingat setiap individu memiliki kepentingan sendiri dalam mengisi penilaian terhadap karyawan. Oleh sebab tersebut dibutuhkan sistem yang terkomputerisasi sehingga mampu menentukan karyawan terbaik menggunakan metode TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) untuk melakukan pemeringkatan alternatif-alternatif mana yang memiliki nilai tertinggi sehingga dapat digunakan oleh perusahaan untuk memberikan hadiah atau kenaikan jabatan kepada karyawan terpilih dari hasil penilaian yang diberikan oleh sistem perusahaan
Klasifikasi SMS Spam Berbahasa Indonesia Menggunakan Algoritma Multinomial Naïve Bayes Herwanto Herwanto; Nuke L Chusna; Muhammad Syamsul Arif
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3119

Abstract

Based on a report submitted by Truecaller Insights Report 2020, Indonesia placed sixth position with the most spam messages, one of the spam applications is SMS. Spam SMS contains unwanted or unsolicited messages, including advertisements, scams and so on. The existence of this spam message causes inconvenience from the user's side when receiving spam SMS, and some even become victims of crime after responding to the SMS. To minimize inconvenience and crime caused by spam messages, the purpose of this study is to filter SMS spam or SMS filtering by classifying SMS spam using the Multinomial Naïve Bayes algorithm by looking for the best combination of parameters to improve the performance of the model that is formed. The results of model testing get the highest precision value in the MNB and SVM models by 93%, the highest recall value in the SVM model at 94%, the highest f1-score value in the SVM model at 94%, the highest accuracy value in the SVM model at 95%, and the fastest test time on the MNB model is 2.66 ms
Performance analysis of Navigation AI on Commercial Game Engine: Autodesk Stingray and Unity3D Moch Fachri; Ali Khumaidi; Nur Hikmah; Nuke L Chusna
Jurnal Mantik Vol. 4 No. 1 (2020): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (707.523 KB)

Abstract

This research establish crowd simulation on modern game engine such as Autodesk Stingray and Unity 3D. This paper explores the navigation system of both game engine. Furthermore we compare the navigation performance for each navigation system used by those engine: The gameware Navigation which is used in Stingray as its middleware for navigation AI, and Unity Navigation used in Unity3D. We simulate the crowd simulation using scenario of crossroad and narrow-passage. Experimental result demonstrates the navigation of hundreds of agents in densely populated environments.
Development of Slum District Application in The City of Bekasi Based on Web Nur Hikmah; Nuke L Chusna; Ali Khumaidi
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1015.pp1803-1807

Abstract

The Government of Bekasi City through The Department of Public Housing, Settlement Areas and Lands (DISPERKIMTAN) has a program to reduce slum areas with the City Without Slum Program (KOTAKU). District data collection is currently being carried out manually by the team and then the data is entered into the information system which can only be accessed internally. Existing data are not updated quickly so it is sometimes difficult to determine policies related to development assistance. Rukun Tetangga (RT) and Rukun Warga (RW) are part of the government structure closest to the community so that if data collection is carried out by them, the data will be fast and updated. This slum application development was developed using the SDLC model of waterfall method, while the stages include analysis, system design, system implementation, and system testing. Testing the application using a black box and the results are in accordance with the scenario and expectations.
Klasifikasi Citra Jenis Tanaman Jamur Layak Konsumsi Menggunakan Algoritma Multiclass Support Vector Machine Nuke L. Chusna; Mohammad Imam Shalahudin; Umbar Riyanto; Allan Desi Alexander
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): Juni 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (483.267 KB) | DOI: 10.47065/bits.v4i1.1624

Abstract

Mushrooms are plants that have high nutritional content and have various benefits for the health of the human body. However, not everyone knows the types of mushrooms that are suitable for consumption. The types of mushrooms have their own characteristics when viewed from the image. For this reason, a system is needed by utilizing digital image processing to classify types of mushrooms suitable for consumption, so that people can find out which types of mushrooms are suitable for consumption. This research is to classify types of mushrooms suitable for consumption using the Multiclass SVM algorithm with first-order feature extraction, which performs feature extraction based on the characteristics of the image histogram. The result of feature extraction is used as input for classification in Multiclass SVM. Multiclass SVM can map data points to dimensionless space to obtain hyperplane linear separation between each class. The developed method is implemented in Matlab, in order to produce a system in the form of a GUI so that it can be used by general users easily. Based on the test results, the average accuracy is 83%.
Analisis Kasus Perceraian Pada Pengadilan Negeri Bekasi Menggunakan Algoritma K-Means Clustering Uci Dwi Rahayu; Nuke L Chusna; Moch Fachri
ikraith-informatika Vol 6 No 1 (2022): IKRAITH-INFORMATIKA Vol 6 No 1 Maret 2022
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1173.058 KB)

Abstract

Perceraian merupakan berakhirnya suatu pernikahan. Saat kedua pasangan tersebut tidak inginlagi melanjutkan kehidupan pernikahannya, pada dasarnya hal ini disebabkan oleh banyak faktorsalah satunya antara suami dan istri sudah tidak menjalankan fungsinya dengan baik. Tercatatbahwa per tahunnya angka perceraian meningkat walaupun terkadang masih mengalami fluktuasi.Dari kasus tersebut peneliti melakukan pengembangan menggunakan metode k-means clusteringdengan parameter perbedaan usia pasangan, lama usia pernikahan, jumlah anak,wilayah/kecamatan dan jenis cerai. Dari hasil tersebut diharapkan agar dapat memberikan solusiyang tepat yakni mampu mengelompokan wilayah/kecamatan yang melakukan perceraian. Hasilclustering menunjukkan bahwa tingkat perceraian yang tertinggi berada di cluster 0 berjumlah 766items dan cluster 1 berjumlah 411 items
Penggunaan Sistem Pendukung Keputusan Dalam Evaluasi Program Pembagian Bantuan Sosial Covid-19 Adriyan Priyatma; Nuke L Chusna; Avip Kurniawan
ikraith-informatika Vol 6 No 1 (2022): IKRAITH-INFORMATIKA Vol 6 No 1 Maret 2022
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1169.105 KB)

Abstract

Bantuan Sosial Covid-19 merupakan sebuah upaya pemerintah dalam membantuperekonomian warga dimasa pandemi Covid-19, dalam pendistribusian bantuan sosial Covid-19tentunya melalui tahapan-tahapan yang terstruktur mulai dari tingkat tertinggi (pemerintahan)sampai tingkatan yang paling bawah (RT/RW). Dalam pendistribusiannya pemerintah sangatmengharapkan agar bantuan sosial Covid-19 dapat tersalurkan secara benar dan terarah, agarterciptanya sila ke-5 pancasila yakni “Keadilan Sosial bagi seluruh rakyat Indonesia”.Dari tingkat atas pemerintah sebagai media penyalur tentunya memiliki metode tersendiridalam menyalurkan bantuan sosial dalam skala yang cukup besar, namun dalam skala yang kecilseperti halnya Rukun Tetangga (RT) dan Rukun Warga (RW), sistem pembagian bantuan sosialCovid-19 yang sudah diterima dari pihak RT dan RW dari kelurahan maupun kecamatan, sering kalidibagikan tanpa ada metode dan bisa dikatakan hanya menggunakan analisis pribadi dari panitiaataupun ketua RT/RW pihak penyelanggara pembagian bansos Covid-19 tersebut.Keadaan tersebut benar adanya terjadi dilingkungan warga RT.001/015 Kaliabang TengahKota Bekasi, maka dari itu Penggunaan Sistem Pendukung Keputusan Pembagian Bantuan SosialCovid-19 ini dibuat agar dapat menjembatani tujuan pemerintah dalam mensukseskanpendistribusian Bansos Covid-19 ini mulai dari tingkat atas sampai bawah.
Implementasi Metode Profile Matching Pada Sistem Pendukung Keputusan Seleksi Calon Ketua OSIS Amat Damuri; Herry Wahyono; Nuke L Chusna
Journal of Information System Research (JOSH) Vol 4 No 1 (2022): October 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (478.158 KB) | DOI: 10.47065/josh.v4i1.2337

Abstract

OSIS is the highest organization in the school that functions to mobilize students to be able to contribute to various activities that support the school. To get the OSIS chairperson, it begins with the registration of candidate candidates, then continues with a meeting to determine the candidate for the OSIS chairman. This is considered ineffective because there are no special criteria, so it is not right on target. In addition, the selection process in this way takes a long time. The purpose of this study is to develop a decision support system to select a candidate for the OSIS chairman by using the profile matching method through the required criteria so that the process will be faster and more precise. The profile matching method has the ability to determine the assessment based on the existing attributes. Based on the calculation of profile matching manually and the system built shows the same results. Based on the case study, candidate 1 got a final score of 9.14 and candidate 2 got a final score of 9.215. The results of the assessment of test cases that have been filled in by system users get the system functions developed in accordance with the test criteria carried out. As for the results of black-box testing, the value is 100%, this means that the system is in accordance with the functions and needs.
Dissolved Oxygen Prediction of the Ciliwung River using Artificial Neural Networks, Support Vector Machine, and Streeter-Phelps Yonas Prima Arga Rumbyarso; Nuke L Chusna; Ali Khumaidi
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 10 No 3 (2022): Vol. 10, No. 3, December 2022
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2022.v10.i03.p06

Abstract

Evaluation of Ciliwung river water quality can be done by analyzing the distribution of dissolved oxygen (DO). The purpose of this research is to analyze the environmental parameters that affect the distribution of DO, by carrying out predictive modeling to estimate the distribution of DO in the Ciliwung River. The research data used primary data and secondary data, some of which were obtained from previous studies. The water quality parameters used are DO, temperature, biochemical oxygen demand, chemical oxygen demand, power of hydrogen, and turbidity. The dataset used has a missing value of 28.8%. To optimize the model results, preprocessing is carried out using a machine learning approach, namely comparing support vector machine (SVM), artificial neural networks (ANN), and linear regression. The three models were compared to predict DO, the results of performance evaluation of the SVM, ANN and Streeter-Phelps models had RMSE values of 0.110, 0.771, and 0.114.
Co-Authors Adam Elvandi Yusup Adriyan Priyatma Ahmad Ari Aldino Alexander, Allan D Ali Khumaidi Amat Damuri Andrian Muljadi Avip Kurniawan Avip Kurniawan Fachri, Moch Herry Wahyono Herry Wahyono Herwanto Herwanto Herwanto Herwanto M.Ageng Laksono Mega Wahyu Rhamadani Moch Fachri Mohammad Imam Shalahudin Muhammad Syamsul Arif Nur Hikmah Nur Hikmah Nurhasan Nugroho Risanto Darmawan Uci Dwi Rahayu Umbar Riyanto Umbar Riyanto Yonas Prima Arga Rumbyarso