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All Journal Bulletin of Electrical Engineering and Informatics Prosiding SNATIF Jurnal Transformatika Jurnal Informatika Universitas Pamulang Jurnal Informatika dan Rekayasa Perangkat Lunak Abdimasku : Jurnal Pengabdian Masyarakat Journal of Future Artificial Intelligence and Technologies
Budi Widjajanto
Universitas Dian Nuswantoro
Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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EVALUASI LAYANAN INFORMASI PUBLIK BERBASIS TEKNOLOGI INFORMASI PADA SITUS KOPERTIS WILAYAH VI JAWA TENGAH Rijati, Nova; Widjajanto, Budi; Santoso, Dewi Agustini
Prosiding SNATIF Vol 1, No 1 (2014): Prosiding Seminar Nasional Teknologi dan Informatika
Publisher : Prosiding SNATIF

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak  Penelitian ini bertujuan  mengevaluasi layanan informasi publik berbasis teknologi informasi pada Kopertis Wilayah VI Jawa  Tengah  berdasarkan  UU 14/2008 tentang Keterbukaan Informasi Publik. Metode penelitian yang digunakan  dengan melakukan kajian  dan evaluasi terhadap layanan informasi publik berbasis teknologi informasi pada situs Kopertis Wilayah VI, kemudian  memetakan konten informasi pada menu /sub menu berdasarkan Permendiknas No 50 tahun 2011 tentang layanan informasi publik di lingkungan Kementerian Pendidikan dan Kebudayaan  dan menentukan konten informasi  publik yang  sesuai UU No 14/2008. Berdasarkan penelitian yang dilakukan diketahui bahwa dari 58 item informasi publik yang harus disediakan, ternyata hanya terdapat 17 item (29%) sehingga masih terdapat 71% item informasi publik yang belum tersedia, serta sifat situs www.kopertis6.or.id dalam memberikan layanan informasi publik masih sebatas menampilkan, namun belum memberikan layanan yang bersifat interaktif. Kata kunci: informasi publik, situs, Kopertis Wilayah VI
Implementasi K-Nearest Neighbor pada Decission Support System Pemilihan Satuan Pengamanan Event Perguruan Tinggi Setiawan, Aries; Widjajanto, Budi; Kurniawan, Achmad Wahid; Budi, Setyo
Jurnal Informatika Universitas Pamulang Vol 5, No 1 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (242.325 KB) | DOI: 10.32493/informatika.v5i1.4401

Abstract

Routine events required by tertiary institutions require escort from selected security guards. Elections based on personal subjectivity will lead to results that are not in accordance with the purpose of the security itself. However, if the selection is based on the objectives will give results that are in accordance with professionalism. Each security unit has a different level of importance, so that at the level of security the event needs a level of professionalism in accordance with the level of importance at the college level. In detail the selection of security units on several criteria, namely event, years of service, cooperation, service, personality, skills and responsibilities. The method used in this selection process is the K-Nearest Neighbor, with the final result approval rate of  0.88%
Metode Simple Additive Weighting untuk Penentu Peringkat Variabel Kepuasan Konsumen pada Layanan Jasa Budi, Setyo; Setiawan, Aries; Widjajanto, Budi; Kurniawan, Achmad Wahid
Jurnal Informatika Universitas Pamulang Vol 6, No 2 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i2.9790

Abstract

The level of service in an agency is a supporter of the survival of an agency. consumer goals that arise from good service quality, are believed to be the main factors of business success. The indicator of the level of customer satisfaction with service quality is when consumers get maximum results from a desired need. Consumer measurements can be seen from the results of the buyer's assessment given by the service manager, and services in the form of consumers which result in goods or services being used as drivers. The method that will be used in the process of ranking consumer satisfaction variables in this study is Simple Additive Weighting. This method has a work order sequence by determining the weight value of each variable, then the ranking process by determining the best variable from the consumer satisfaction variable. The final result of this research is the ranking of consumer satisfaction variables from the highest to the lowest using Simple Additive Weighting to obtain an accuracy rate of 90%. The variable "satisfactory taste" turned out to be the highest satisfaction service variable, meaning that the cafe service party needed to maintain the taste so that consumers were satisfied with the existing services.
DECISION SUPPORT SYSTEM PEMBUKAAN LOKASI BARU JASA SERVIS MOTOR BERBASIS PROFILE MATCHING Nuryanto, Imam; Setiawan, Aries; Farida, Ida; Wibowo, Sasono; Widjajanto, Budi; Prihandono, Adi
Jurnal Transformatika Vol. 21 No. 2 (2024): Januari 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.8166

Abstract

As the volume of motorbikes increases, the number of motorbike service outlets also increases. However, not all service places get customers equally, from the customer's side various variables really determine visits such as location, level of spare parts availability, level of service to consumers and price. Likewise, in terms of service owners, when opening a new service location, they need to pay attention to various variables such as proximity to residential areas, number of competitors, capacity of passing vehicles, and proximity to spare parts suppliers. To collaborate several influential variables to produce a decision regarding the right place, a method is needed that is capable of carrying out calculations to produce a ranking of locations that will have an influence. One method that can be offered is profile matching. This method performs by finding the difference between the weight value determined at the beginning and the input value for each location object. The ranking results of all location objects can be used as alternative locations for appropriate service locations..
Rancang Bangun Sistem Pengelolaan Aset Ilmiah Digital Pada Perpustakaan Perguruan Tinggi Setiawan, Aries; Ratnawati, Juli; Prihandono, Adi; Widjajanto, Budi; Farida, Ida
Jurnal Transformatika Vol 21, No 1 (2023): July 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.6938

Abstract

Perpustakaan merupakan satuan pendidikan tinggi yang mengelola perbendaharaan aset ilmiah. Aset ilmiah meliputi buku pelajaran, buku bacaan, tugas akhir mahasiswa, jurnal, CD berisi file tulisan dan video. Setiap periode selalu dianggarkan untuk pengadaan buku, setiap periode setelah pelaksanaan tugas akhir atau ujian skripsi, hardcopy tugas akhir yang akan dijadikan literatur juga bertambah. Bisa dibayangkan jika dalam satu tahun ada 3 periode ujian tugas akhir, dengan total sekitar 600 mahasiswa per periode, maka akan ada 1800 hardcopy tugas akhir mata kuliah. Hal ini berdampak pada kepenuhan ruang perpustakaan sehingga semakin sulit untuk mencari data laporan tugas akhir. Perlu dirancang sistem manajemen aset elektronik di perpustakaan yang mengumpulkan semua data buku dan literatur lainnya dalam bentuk file elektronik, pengunjung akan mudah menemukan literatur hanya dengan mencari sistem aset.
Profile Matching Untuk Sistem Pendukung Keputusan Penilaian Kinerja Driver Kurniawan, Achmad Wahid; Widjajanto, Budi; Farida, Ida
Jurnal Transformatika Vol. 19 No. 1 (2021): July 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i1.3128

Abstract

Penilaian secara periodik terhadap driver perlu dilakukan, untuk mengevaluasi kinerja. Pelaksanaan evaluasi membutuhkan waktu sehingga evaluasi sering dilakukan ketika terjadi keluhan dari penumpang, memberikan efek perubahan yang sifatnya sementara juga, setelah keluhan teratasi maka driver maupun pimpinan divisi transportasi menganggap tidak akan terjadi lagi kejadian yang sama. Bentuk evaluasi seperti di atas seringkali hanya  dilakukan terhadap driver yang dikeluhkan penumpang.   Penilaian kinerja yang termodel dan menyeluruh terhadap semua driver, yang sifatnya periodik dengan Sistem Pendukung Keputusan berbasis Profile Matching mampu meminimalisir kejadikan yang dikeluhkan penumpang..    
SISTEM MANAJEMEN PENEGAKAN DIAGNOSA PENYAKIT TYPUS DENGAN METODE NAIVE BAYES Setijaningsih, Retno Astuti; Setiawan, Aries; Sugiyanto, Zaenal; Farida, Ida; Widjajanto, Budi; Rizqa, Ifan
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5792

Abstract

Dalam dunia kesehatan, beberapa gejala yang timbul bisa menjadi tanda-tanda penyebab dari beberapa penyakit sekaligus. Kondisi yang dilematis ini sering kali mempersulit pengambilan keputusan mengenai penyakit yang diderita seseorang. Penentuan langkah pencegahan maupun pengobatan juga menjadi sulit untuk dilakukan, sehingga pemeriksaan lanjutan perlu dilakukan oleh tim medis. Sangat dimungkinkan jika tim medis kurang akurat dalam menentukan analisis penyakit dikarenakan munculnya gejala yang sama pada beberapa penyakit. Diperlukan sistem penegakan diagnose penyakit dengan metode na ve bayes akan mampu membantu pembelajaran bagi mahasiswa dalam mengenal gejala-gejala penyakit typus, dan juga dilengkapi dengan solusi pencegahan maupun solusi penanggulangan.
Exploring Machine Learning and Deep Learning Techniques for Occluded Face Recognition: A Comprehensive Survey and Comparative Analysis Muhamada, Keny; Setiadi, De Rosal Ignatius Moses; Sudibyo, Usman; Widjajanto, Budi; Ojugo, Arnold Adimabua
Journal of Future Artificial Intelligence and Technologies Vol. 1 No. 2 (2024): September 2024
Publisher : Future Techno Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/faith.2024-30

Abstract

Face recognition occluded by occlusions, such as glasses or shadows, remains a challenge in many security and surveillance applications. This study aims to analyze the performance of various machine learning and deep learning techniques in face recognition scenarios with occlusions. We evaluate KNN (standard and FisherFace), CNN, DenseNet, Inception, and FaceNet methods combined with a pre-trained DeepFace model using three public datasets: YALE, Essex Grimace, and Georgia Tech. The results show that KNN maintains the highest accuracy, reaching 100% on two datasets (Essex Grimace and YALE), even in the presence of occlusions. Meanwhile, CNN shows strong performance, with accuracy remaining 100% on YALE, both with and without occlusions, although its performance drops slightly on Essex Grimace (94% with occlusion). DenseNet and Inception show a more significant drop in accuracy when faced with occlusion, with DenseNet dropping from 81% to 72% on Essex Grimace and Inception dropping from 100% to 92% on the same dataset. FaceNet + DeepFace excels on more large dataset (Georgia Tech) with 98% accuracy, but its performance drops dramatically to 53% and 70% on Essex Grimace and YALE with occlusion. These findings indicate that while deep learning methods show high accuracy under ideal conditions, machine learning methods such as KNN are more flexible and robust to occlusion in face recognition.
Pengenalan E-Modul Untuk Pengenalan Food And Baverage Pada Himpunan Mahasiswa Program Studi Pengelolaan Perhotelan Hariyadi, Guruh Taufan; Lewa, Andi Hallang; Kurniawati, Neni; Setiawan, Aries; Farida, Ida; Widjajanto, Budi; Prasetya, Jaka; Widyatmoko, Karis; Nuryanto, Imam; Purwatiningsih, Aris Puji
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 2 (2024): MEI 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i2.2344

Abstract

Terkait pembelajaran tentang dunia kuliner, selama ini masih menggunakan buku atau modul pembajaran manual atau walaupun sudah berbasis komputer namun hanya sebatas mengumpulkan bahan pembelajaran dari artikel di internet. Pada intinya modul pembelajaran fungsinya mendampingi siswa dalam kegiatan belajaran mengajar, namun yang terjadi selama ini sebagai dampak perkembangan teknologi dan gadget membuat mahasiswa malas untuk belajar dari buku atau modul manual, mereka lebih senang browsing dari literatur yang ada diinternet. Berkaitan permasalah diatas maka teknologi informasi mempunyai peranan penting, salah satu model pemberian materi yang bisa digunakan adalah E- modul. Tujuan dari pelatihan pembuatan e-modul ini adalah memberikan pengetahuan kepada para mahasiswa khususnya anggota HMPP dalam menyusun buku resep yang praktis dan mudah memberikan tutorial menu resep masakan. Setelah adanya pelatihan pembuatan E-Modul, mahasiswa pada program studi Pengelolaan Perhotelan, mampu dengan mudah belajar tentang kuliner berbasis e-modul.
Optimizing earthquake damage prediction using particle swarm optimization-based feature selection Anisa Sri Winarsih, Nurul; Anggi Pramunendar, Ricardus; Fajar Shidik, Guruh; Widjajanto, Budi; Syaifur Rohman, Muhammad; Oka Ratmana, Danny
Bulletin of Electrical Engineering and Informatics Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i1.8421

Abstract

Earthquakes have destroyed the economy and killed many people in many countries. Emergency response actions immediately after an earthquake significantly reduce economic losses and save lives, so accurate earthquake damage predictions are needed. This research looks at how machine learning (ML) techniques are used to predict damage from earthquakes. The ML algorithms used are k-nearest neighbors (KNN), decision tree (DT), random forest (RF), and Naïve Bayes (NB). Feature selection is necessary, it needs to select the most relevant features from big data. One of the most commonly used algorithms to optimize ML is particle swarm optimization (PSO). PSO is also suitable for feature selection. This research compares various of PSO. Based on research, the RF algorithm with Phasor PSO has the highest fitness score. This process succeeded in reducing features from 38 features to 14 features. Based on the process after feature selection, it was found that the KNN, DT, and RF algorithms had improved. RF obtained the best accuracy, namely 72.989%. The processing time in DT, RF, and NB is faster than before. In conclusion, the ML algorithm can be combined with PSO feature selection to create a classification model that provides better performance than without feature selection.
Co-Authors Achmad Wahid Kurniawan Anggi Pramunendar, Ricardus Anisa Sri Winarsih, Nurul Budi, Setyo De Rosal Ignatius Moses Setiadi Dewi Agustini Santoso Ery Mintorini Fajar Shidik, Guruh Hariyadi, Guruh Taufan Ichwan Setiarso, Ichwan Ida Farida Ifan Rizqa Imam Nuryanto Jaka Prasetya Juli Ratnawati Karis Widyatmoko karmila karmila Kurniawan, Setyo Budi Kusumaningrum, Lely Kusumaningrum Lewa, Andi Hallang Mertha Agung Durya, Ngurah Pandji Moch. Sjamsul Hidajat Muhamada, Keny Neni Kurniawati Nova Rijati Ojugo, Arnold Adimabua Oka Ratmana, Danny Pandji Mertha Agung Durya, Ngurah Prawitasari, Dian Prihandono, Adi Puji Purwatiningsih, Aris Puspita Sari, Raden Ayu Aminah Rizkia Retno Astuti Setijaningsih Sasono Wibowo Setiawan, Aries Sudibyo, Usman Syaifur Rohman, Muhammad Yenny Ernitawati Yulita Setiawanta Zaenal Sugiyanto