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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Masyarakat Informatika JURNAL SISTEM INFORMASI BISNIS Bulletin of Electrical Engineering and Informatics Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information System E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) InComTech: Jurnal Telekomunikasi dan Komputer Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Biomedical Science and Bioengineering Jurnal Sistem Informasi Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Informatika
Adi Wibowo
Departement Of Computer Science, Informatics, Universitas Diponegoro
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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Modifikasi Pattern Informatics untuk Prediksi Hotspot Aktivitas Seismik pada Gempa di Pulau Jawa Adi Wibowo; Asep Insani; Boko Nurdiyanto S.
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 2: Mei 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (990.482 KB)

Abstract

Earthquake is a serious problem in economic, social, and cultural point of view. The forecasting and prediction can be one way solution in reducing the effects of earthquakes in a region. In this paper, pattern informatics method was modified with time parameters to conduct hotspot prediction of seismic activity for the earthquake forecasting in Java. The experiment using seismic activity and earthquake data in Java were conducted to examine the perfomance of proposed method with several period prediction scenarios. The prediction results show an improvement of prediction result and shorten the prediction period.
Combination of K-NN and PCA Algorithms on Image Classification of Fish Species Rini Nuraini; Adi Wibowo; Budi Warsito; Wahyul Amien Syafei; Indra Jaya
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5178

Abstract

To do fish farming, you need to know the types of fish to be cultivated. This is because the type of fish will affect how it is handled and managed. Therefore, this study aims to develop an image processing system for classifying fish species, especially cultivated fish, with a combination of the K-Nearest Neighbor (K-NN) algorithm and Principal Component Analysis (PCA). The feature extraction used is feature extraction based on its color and shape. The K-NN algorithm can group certain objects considering the shortest distance from the object. According to the best criteria, the PCA method is employed in the meanwhile to decrease and keep the majority of the relevant data from the original characteristics. On the basis of the test results, the accuracy value obtained is 85%. The use of a combination of the K-NN and PCA algorithms in the image classification of fish species in the research that has been done has been shown to be capable of increasing accuracy by 7.5% compared to only using the K-NN algorithm.
Sistem Penilaian Jawaban Singkat Otomatis pada Ujian Online Berbasis Komputer Menggunakan Algoritma Cosine Similarity Dedy Kurniadi; Rahmat Gernowo; Bayu Surarso; Adi Wibowo; Budi Warsito
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.66934

Abstract

Penggunaan teknologi di bidang pendidikan sekarang ini sedang trending ke arah penilaian secara otomatis, namun penilaian secara otomatis ini memiliki permasalahan yaitu belum bisa mengkoreksi jawaban teks singkat secara otomatis, selain itu pada saat ini juga belum tersedia platform yang bisa mengkoreksi jawaban singkat secara otomatis, penilaian jawaban teks singkat ini membutuhkan waktu koreksi yang lama dan hasil penilaian yang tidak konsisten jika koreksi dilakukan oleh manusia, pada penelitian ini diusulkan sistem yang mampu mengkoreksi ujian peserta didik pada bagian jawaban singkat secara otomatis atau disebut dengan Automated Short Answer Grading (ASAG) dengan menggunakan metode cosine similarity, tahapan yang dilakukan adalah melakukan ekstraksi pada dua variabel inputan yaitu teks pada jawaban peserta didik dan teks pada kunci jawaban yang dilakukan dengan ekstraksi teks casefolding, tokenizing, stopword removal, setelah tahapan tersebut dilakukan kemudian dihitung nilai similarity antara kunci jawaban ujian dengan jawaban peserta didik apakah jawaban peserta didik sama dengan kunci jawaban atau tidak, dengan menggunakan skor yang dinilai otomatis menggunakan sistem, dihasilkan similarity antara jawaban peserta didik dengan kunci jawaban rata-rata sebesar 85,4%, untuk menguji korelasi koreksi jawaban peserta didik dengan sistem dan koreksi yang dilakukan oleh manusia maka dilakukan uji korelasi antara hasil penilian yang dilakukan oleh sistem dengan hasil penilaian yang dilakukan oleh manusia (instruktur) dengan menggunakan kendall’s w value menghasilkan nilai w antara instruktur 1 dengan sistem sebesar 0,885 dan instruktur 2 dengan sistem sebesar 0,883 dengan nilai chi square sebesar 135,4 dan 133,8 dengan p sebesar 0,0001, hasil tersebut menunjukkan ASAG memiliki korelasi yang tinggi dan sistem ASAG ini bisa melakukan penilaian secara otomatis.
Fragile watermarking for image authentication using dyadic walsh ordering Prajanto Wahyu Adi; Adi Wibowo; Guruh Aryotejo; Ferda Ernawan
International Journal of Advances in Intelligent Informatics Vol 9, No 3 (2023): November 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v9i3.1017

Abstract

A digital image is subjected to the most manipulation. This is driven by the easy manipulating process through image editing software which is growing rapidly. These problems can be solved through the watermarking model as an active authentication system for the image. One of the most popular methods is Singular Value Decomposition (SVD) which has good imperceptibility and detection capabilities. Nevertheless, SVD has high complexity and can only utilize one singular matrix S, and ignore two orthogonal matrices. This paper proposes the use of the Walsh matrix with dyadic ordering to generate a new S matrix without the orthogonal matrices. The experimental results showed that the proposed method was able to reduce computational time by 22% and 13% compared to the SVD-based method and similar methods based on the Hadamard matrix respectively. This research can be used as a reference to speed up the computing time of the watermarking methods without compromising the level of imperceptibility and authentication.
Voting Classifier Technique and Count Vectorizer with N-gram to Identifying Hate Speech and Abusive Tweets in Indonesian Riza Arifudin; Dandi Indra Wijaya; Budi Warsito; Adi Wibowo
Scientific Journal of Informatics Vol 10, No 4 (2023): November 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i4.46633

Abstract

Purpose: The objective of this study is to identify hate speech and abusive tweets in Indonesian using a Voting Classifier technique and Count Vectorizer with N-grams. Voting Classifier technique involves combining multiple classifiers like Random Forest and Support Vector Machines to improve classification accuracy.Methods: This research begins by preprocessing the data. Voting classifier uses Support Vector Machine algorithm and Random Forest algorithm. Support Vector Machine and Random Forest serve as the estimators for the voting classifier. As for feature extraction, N-gram and count vectorizer were employed. The effectiveness of the suggested procedures is the desired outcome.Result: Combining the Voting Classifier approach with Count Vectorizer feature extraction and using 1 gram of N-grams, or 82.50%, resulted in the best accuracy. From this study, it can be inferred that the approach employed to identify hate speech and abusive tweets is extremely practical.Novelty: Combining multiple classifiers and using feature extraction techniques like count vectorizer and N-gram with machine learning algorithms can be used for sentiment analysis to differentiate between hate speech and abusive tweets.
Optimization of the algorithms use ensemble and synthetic minority oversampling technique for air quality classification Aziz Jihadian Barid; Hadiyanto Hadiyanto; Adi Wibowo
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1632-1640

Abstract

Rapid economic development, industrialization, and urbanization in Indonesia have caused a large increase in air pollution with negative impacts on the environment and public health. The aim of this research is to use machine learning techniques to categorize air quality and generate an air quality index (AQI) using a dataset that includes six prevalent air pollutants. Next steps are preprocessing and data extraction, K-nearest neighbors (KNN) classification, support vector machine (SVM), and random forest (RF) models are implemented. Furthermore, synthetic minority oversampling technique (SMOTE) is incorporated into the ensemble learning process to improve the results. This research uses K-fold cross validation for improve classification accuracy and reduce overfitting. Research findings show that the application of SMOTE brings a significant increase in model accuracy, effectively solving the problem of imbalanced data sets. These insights provide direction for effective air quality monitoring systems and informed decision making in air pollution management.
Combination of Matrix Simple Additive Weighting Algorithm (SAW) on the Reference URICA-Scale to Measure Readiness for Change in Narcotic Rehabilitation Patients Soni Adiyono; Rahmat Gernowo; Adi Wibowo
Jurnal Aisyah : Jurnal Ilmu Kesehatan Vol 7, No S1 (2022): Suplement 1
Publisher : Universitas Aisyah Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (775.939 KB) | DOI: 10.30604/jika.v7iS1.1118

Abstract

This study aims to design a matrix combination in the URICA-Scale calculation and the simple additive weighting (SAW) method that can be used as a measuring tool to evaluate the readiness of drug rehabilitation patients using the University of Rhode Change Assessment Scale (URICA-Scale) as a desire combined with simple additive weighting (SAW) method in order to facilitate the design of electronic information systems regarding assessment tests with reference to URICA-Scale. In software development, the design modeling step in the system is one part of the (System Development Life Cycle) contained in the Waterfall model. The results of this study are able to provide an arrangement of calculation matrices where the combination of these matrices contributes to programmers in implementing them into certain programming languages. Abstrak: Penelitian ini bertujuan untuk merancang desain kombinasi matriks pada perhitungan URICA-Scale dan metode simple additive weighting (SAW) yang dapat digunakan sebagai alat ukur guna mengevauasi tentang kesiapan pasien rehabilitasi narkotika dengan menggunakan University of Rhode Change Assesment Scale (URICA-Scale) sebagai acuan yang dikombinasikan dengan metode simple additive weighting (SAW) agar dapat mempermudah dalam merancang sistem informasi elektronik mengenai tes asesmen dengan acuan URICA-Scale. Dalam pengembangan perangkat lunak langkah pemodelan desain pada sistem merupakan salah satu bagian dari (System Development Life Cycle) yang terdapat pada model Waterfall. Hasil penelitian ini mampu memberikan susunan matrix perhitungan dimana dengan adanya gabungan dari matriks tersebut memberikan kontribusi bagi programmer dalam melakukan implementasi kedalam Bahasa pemrograman tertentu.
Analisis Pengaruh Pemilihan Jumlah Variabel Linguistik Membership Function pada Metode Fuzzy Simple Additive Weighting (FSAW) untuk Perankingan Penerimaan Beasiswa Bagi Siswa Kurang Mampu (Studi Kasus : Sekolah Dasar Negeri Petompon 02 Semarang) Alfania Sarah Handayani; Adi Wibowo
Jurnal Masyarakat Informatika Vol 12, No 1 (2021): May 2021
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.12.1.41019

Abstract

SDN Petompon 02 Semarang merupakan salah satu Sekolah Dasar Negeri yang memiliki program beasiswa "Bumbung  Kemanusiaan"  yang ditujukan bagi siswa yang kurang  mampu. Oleh karena itu diperlukan perankingan siswa untuk memilih calon penerima beasiswa. Pengumpulan data untuk penelitian  ini  didapatkan melalui  wawancara  dengan  Kepala  Sekolah  SDN  Petompon  02  Semarang  untuk  mendapatkan  kriteria penerimaan beasiswa. Terdapat 5 kriteria untuk penerimaan beasiswa yaitu kepemilikan kartu miskin, rata-rata raport semester terakhir, kepemilikan piagam, penghasilan orang tua, dan tanggungan orang tua. Permasalahan ini merupakan permasalahan dunia nyata, sehingga data yang dikumpulkan biasanya melibatkan beberapa jenis ketidakpastian. Salah satu solusi dalam pengambilan keputusannya adalah memodelkan dengan fuzzy. Di dalam Metode Fuzzy Simple Additive Weighting terdapat pemilihan variabel linguistik membership function, dimana skala tersebut sangat berpengaruh  bagi perhitungan pada  metode.  Penelitian  ini bertujuan untuk  menganalisis pemilihan  jumlah variabel linguistik  membership  function  untuk mendapatkan nilai preferensi yang  sesuai dan nilai akurasi. Penelitian ini melakukan 2 percobaan yaitu dengan memilih jumlah variabel linguistik 5 dan jumlah variabel linguistik  7.  Hasil  penelitian  menunjukkan  nilai  akurasi  yang  lebih  baik  pada  pemilihan  jumlah  variabel linguistik 7 menggunakan metode Fuzzy Simple Additive Weighting mencapai 96,08%.
Evaluasi Usability pada Aplikasi Sistem Pencatatan Pegawai Menggunakan Metode Usability Testing dan USE Questionnaire Abraham Timotius Asmoro Putro; Adi Wibowo; Sutikno Sutikno
Jurnal Masyarakat Informatika Vol 15, No 2 (2024): November 2024
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.15.2.67263

Abstract

In the era of increasingly rapid digitalization, employee recording system applications have become an unavoidable necessity for companies for the efficiency and effectiveness of human resource management. In this context, the usability or usefulness of employee management system applications is a crucial factor in ensuring that users can smoothly and efficiently utilize the system provided. Usability is an important aspect in application design that is often overlooked. The success of an application is not only determined by its features and functionality, but also by the ease of use and user satisfaction in operating it. Therefore, usability evaluation is a very necessary step to ensure that the application being developed meets user needs optimally. The usability testing method and the use of questionnaires are common approaches used in evaluating the usability of an application. In the context of the CV. Cupang Semarangan employee recording system application, this study aims to evaluate the usability of the application using the usability testing method and questionnaire. This study resulted in usability values for the aspects of effectiveness, efficiency, ease of use, ease of learning, and satisfaction being 87.96%, 77.47%, 64.88%, 71.43%, and 68.57% respectively.
Evaluation of Machine Learning Algorithms for Classifying User Perceptions of a Child Health Monitoring Application Eka Rahmawati; Adi Wibowo; Budi Warsito
Jurnal Informatika Vol. 12 No. 2 (2025): October
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/

Abstract

Supporting children’s early development requires consistent attention, ensuring their growth aligns with health standards. PrimaKu is one of the mobile applications developed by the Indonesian Pediatric Society. That application was created to assist parents in recording developmental milestones, monitoring immunization schedules, and accessing practical health information. This study investigates user perceptions of the application by analyzing publicly available reviews and ratings from the Google Play Store. Four supervised machine learning algorithms were applied to classify the sentiment expressed in the reviews: Support Vector Machine (SVM), Random Forest, Decision Tree, and Naive Bayes. Among the models tested, SVM achieved the highest classification accuracy (81%), followed by Random Forest (77%), Decision Tree (74%), and Naive Bayes (73%). Precision, recall, and F1-score were also used to evaluate the performance of each model. The results highlight the relevance of machine learning in capturing and interpreting user sentiment toward digital health tools. Further exploration of deep learning architectures is encouraged to enhance classification accuracy and understanding of features.
Co-Authors Abraham Timotius Asmoro Putro Adian Fatchur Rochim Agus Winarno Alfania Sarah Handayani Andys Sandra Kurniawan Anief Fauzan Rozi Aris Puji Widodo Asep Insani Aziz Jihadian Barid Bayu Surarso Beta Noranita Beta Noranita Beta Noranita Boko Nurdiyanto S. Bramono Triprastowo Budi Warsito Budi Warsito Budi Warsito Budi Warsito Budi Warsito Budi Warsito Cahyo Adhi Hartanto Dandi Indra Wijaya Dedy Kurniadi Djalal Er Riyanto Djalal Er Riyanto Eka Rahmawati Eko Adi Sarwoko Emigawaty Ervin Gubin Moung Ferda Ernawan Fra Siskus Dian Arianto Gregorius Anung Hanindito Guruh Aryotejo H Hadiyanto Helmie Arif Wibawa Henri Tantyoko Iffa Zainan Nisa Indra Jaya Indra Waspada Junta Zeniarja Kabul Kurniawan Kusworo Adi Marsani Asfi Mohd Hanafi Ahmad Hijazi Mohd Suhairi Md Suhaimin Muh. Abdur Rohman Muh. Abdur Rohman Muh. Abdur Rohman Noel Segura Meraz Nurdin Bahtiar Patricia Anthony Prajanto Wahyu Adi Rahmat Gernowo Rahmat Jayanto Ratih Titi Komala Sari Retno Kusumaningrum Rini Nuraini Riza Arifudin Rizka Putri Nawangsari Satriawan Rasyid Purnama Soni Adiyono Sukmawati Nur Endah Sutikno Sutikno Wahyul Amien Syafei Whisnumurti Adhiwibowo Widowati Wirawan, Panji Wisnu Yesaya Rudolf Susanto Widyanto