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All Journal Dinamik GEMA TEKNOLOGI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Syntax Jurnal Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Mahasiswa FEB Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Berkala Epidemiologi Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri InComTech: Jurnal Telekomunikasi dan Komputer Prosiding Seminar Nasional Teknoka JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Telematika STRING (Satuan Tulisan Riset dan Inovasi Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Ilmu Komputer dan Bisnis Syntax Idea Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Mnemonic Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Journal of Computer Science and Engineering (JCSE) SKANIKA: Sistem Komputer dan Teknik Informatika Media Gizi Kesmas Jurnal Teknik Informatika (JUTIF) Jurnal Pewarta Indonesia JURNAL KOMUNIKASI DAN BISNIS Ascarya: Journal of Islamic Science, Culture and Social Studies Jurnal PkM (Pengabdian kepada Masyarakat) Humantech : Jurnal Ilmiah Multidisiplin Indonesia Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Journal Of Human And Education (JAHE) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Berita Kedokteran Masyarakat Journal of Systems Engineering and Information Technology J-Icon : Jurnal Komputer dan Informatika Jurnal Teknik Indonesia Research Horizon Jurnal Relawan dan Pengabdian Masyarakat REDI Jurnal Pengabdian Masyarakat Nasional Health Dynamics Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding SeNTIK STI&K Journal of Medical and Health Science Jurnal Ilmu Kesehatan Immanuel Jurnal Analogi Hukum
Arief Wibowo
Universitas Budi Luhur
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Refining Diabetes Diagnosis Models: The Impact of SMOTE on SVM, Logistic Regression, and Naïve Bayes Wibowo, Arief; Masruriyah, Anis Fitri Nur; Rahmawati, Selly
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.596

Abstract

Accurate diabetes classification is a significant challenge in medical diagnostics, especially in imbalanced datasets. This study addresses this issue by introducing A New Modified Weighted SMOTE (ANMWS), integrated with Priority of Attribute by Expert Judgement (PAEJ) framework, to enhance the performance of machine learning models for imbalanced data. PAEJ categorizes attributes into three levels—high, medium and low priority—based on expert knowledge, while ANMWS applies weighted oversampling using these priority levels to generate synthetic data more representative of real-world cases. The proposed method was evaluated using three algorithms: Support Vector Machine (SVM), Logistic Regression, and Naïve Bayes. Results indicate that applying ANMWS algorithm with PAEJ framework significantly improved predictive performance, with AUC values increasing to 0.995 for SVM, 0.993 for Logistic Regression, and 0.990 for Naïve Bayes, compared to 0.980, 0.978, and 0.975, respectively, using standard SMOTE. Additionally, precision and recall for SVM improved by 5% and 7%, respectively. These findings demonstrate the critical role of ANMWS algorithm and PAEJ framework in addressing class imbalance, providing a reliable method for early diabetes diagnosis and informed clinical decision-making.
PARTICLE SWARM OPTIMIZATION AND GRIDSEARCH OPTIMIZATION ON SUPPORT VECTOR MACHINE ALGORITHM ON SENTIMENT ANALYSIS OF DONALD TRUMP'S ASSASSINATION ATTEMPT Putra, Rinaldi Febryatna Duriat; Sudewo, Andika Hasbigumdi; Wibowo, Arief
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.2713

Abstract

Donald Trump is the 45th president of the United States, serving from 2017 to 2021. Within the 2024 race, Donald Trump is once more running for president of the United States from the Republican Party. Whereas campaigning in Butler, Pennsylvania, United States, a shooting occurrence happened that was distinguished as an endeavored death of Donald Trump. The occurrence gave rise to different master and con opinions among the open. This consider points to decide the propensity of open conclusion towards the endeavored death of Donald Trump and to classify estimations with respect to the occurrence. This think about compares the Molecule Swarm Optimization (PSO) and GridSearch optimization approaches on the Back Vector Machine (SVM) calculation to get the greatest level of precision from optimizing the calculation. In this think about, the dataset utilized was tweet information from July 15, 2024, totaling 1,586, which had been labeled with positive, neutral and negative estimations. The comes about of the tests carried out with comparison proportions of 90:10, 80:20, 70:30, and 60:40 appear that the optimization strategy through PSO can increment the exactness of the SVM calculation by 2.39% when compared to the GridSearch strategy.
PENGELOMPOKAN TRANSAKSI KARTU DEBIT PERBANKAN MENGGUNAKAN ALGORITMA K-MEANS Irawan, Iwan; Rahman, Reza; Wibowo, Arief
Jurnal Sistem Informasi dan Informatika (Simika) Vol 8 No 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3558

Abstract

One of bank customers' most widely used non-cash payment methods is making payments to merchants using debit cards. The data generated from these transactions can be utilized effectively by banks. This study analyzes customer spending habits through debit card transactions, employing a data mining technique called K-means clustering. By identifying patterns in customer transactions, the research aims to assist business units in developing targeted product strategies. The analysis determined that four clusters were optimal, resulting in a tightly grouped dataset with an average distance of 5.764 from the respective cluster centers. Grouping nominal transactions based on the date and time of the transaction can provide valuable insights for bank management when considering customer fund allocation.
Data Mining Klasifikasi Untuk Memprediksistatus Keberlanjutanpolis Asuransi Kesehatan Dengan Algoritme Naïve Bayes Jovansgha Avegad; Arief Wibowo
Prosiding Seminar SeNTIK Vol. 3 No. 1 (2019): Prosiding SeNTIK 2019
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

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Abstract

Data Mining Klasifikasi Untuk Memprediksistatus Keberlanjutanpolis Asuransi Kesehatan Dengan Algoritme Naïve Bayes
Implementasi Fitur Referral Contest pada Aplikasi My Value dalam Mengembangkan Bisnis Elektronik di PT. Kompas Gramedia Ghapur, Abdul; Ningrum, Yogi Ajeng; Wibowo, Arief
Jurnal Teknik Indonesia Vol. 2 No. 2 (2023): Jurnal Teknik Indonesia
Publisher : Publica Scientific Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58860/jti.v2i2.17

Abstract

Tujuan yang ingin dicapai dalam penelitian ini adalah untuk mengetahui implementasi fitur referral contest pada aplikasi My Value dalam mengembangkan bisnis elektronik di PT. Kompas Gramedia. Penelitian ini berangkat dari masalah lambatnya kenaikan jumlah pengguna baru My Value sebelum adanya fitur referral contest. Mulai November 2022 di mana referral contest diaktifkan, jumlah pengguna baru meningkat. Dengan pendekatan kualitatif deskriptif, penelitian ini menganalisis implementasi fitur referral contest pada aplikasi My Value. Sehingga penelitian ini merupakan jenis penelitian kualitatif dengan pendekatan deskriptif. Penelitian ini menggunakan teknik pemeriksaaan keabsahan data dengan jenis keabsahan temporal. Penelitian menunjukkan bahwa fitur referral contest mendukung mengembangkan bisnis elektronik di PT. Kompas Gramedia dari sisi peningkatan jumlah pengguna baru My Value. Referral Contest juga merujuk pada sebuah kegiatan konsumen untuk mengajak konsumen lain atau affective yang dihasilkan dari preferensi. E-loyalty adalah niat konsumen untuk mengunjungi website, mobile apps, yang dapat diartikan sebagai ketertarikan konsumen kepada perusahaan untuk melakukan pembelian berulang yang terbagi menjadi empat dimensi yaitu cognitive, affective, conative, dan action. Dengan demikian dapat disimpulkan bahwa implementasi fitur referral contest mendukung mengembangkan bisnis elektronik di PT. Kompas Gramedia dari sisi peningkatan jumlah pengguna baru My Value.
SEGMENTASI PENDAPATAN DARI PAYMENT AGGREGATOR MENGGUNAKAN METODE KLASTERISASI K-MEANS Suntoro, Dimas Fahmi; Fitriani, Netty; Wibowo, Arief
J-Icon : Jurnal Komputer dan Informatika Vol 13 No 1 (2025): March 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v13i1.12691

Abstract

Customer habits can influence revenue from financial technology-based companies in choosing the type of payment partner. Customers are very selective in having vendors oriented towards convenience, promotions given, and benefits offered. This study describes the application of data mining for clustering, using the K-means method by classifying income in a payment aggregator. The research aims to identify patterns and similarities in revenue data to help decision-making and business analysis. The K-means algorithm is used to partition income data into groups based on their similarities. The research results show that testing uses various quantities: k = 2; DBI = 0.023, k = 3; DBI = 0.209, k = 4; DBI = 0.116 with a max run of ten. This study obtained the best results at a value of k = 4, with a clustering pattern in four payment type categories: copper, silver, gold, and platinum. The results showed that the payment aggregator categories with the highest income values were the CASH, MINIATM TRANSFER, and VA TRANSFER methods with 10.78% from revenue. From the pattern and information provided, the company needs to maintain features that support the payment aggregator with the highest revenue, while for the payment aggregator generating lower revenue, an evaluation is required to consider adding merchants in order to boost transaction frequency and amounts.
Pencatatan dan Pelaporan Pemantauan Ibu Hamil Risiko Tingi di Puskesmas Kanor Afifatussalamah, Rizka; Wibowo, Arief; Wahyuni, Chatarina Unggul
JOURNAL OF MEDICAL AND HEALTH SCIENCE Vol. 1 No. 1 (2023): Juli
Publisher : Universitas Muhammadiyah Sidaorjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/anamnetic.v1i1.1583

Abstract

Pemantauan ibu hamil risiko tinggi merupakan kegiatan yang penting dilakukan karena kondisi ibu hamil dengan risiko memerlukan penanganan yang cepat dan tepat. Pencatatan dan pelaporan pemantauan ibu hamil risiko tinggi adalah sumber informasi yang dapat menggambarkan kondisi ibu hamil sebagai dasar pengambilan keputusan dan tindakan rujukan. Tujuan dari penelitian ini adalah untuk menggambarkan sistem pencatatan dan pelaporan pemantauan ibu hamil risiko tinggi di Puskesmas Kanor Kabupaten Bojonegoro. Desain penelitian deskriptif observasional. Informan dalam penelitian ini adalah 1 (satu) orang bidan desa di Puskesmas Kanor, 1 (satu) orang bidan koordinator di Puskemas Kanor, 1 (satu) orang kepala Puskesmas Kanor, 1 (satu) orang pemegang program KIA di Dinas Kesehatan Kabupaten Bojonegoro. Hasil penelitian menunjukkan terdapat beberapa permasalahan pada input, proses, dan output dari sistem pencatatan dan pelaporan yang saat ini sedang berjalan belum optimal dikarenakan sistem pencatatan dan pelaporan belum terintegrasi dan manual sehingga menyulitkan petugas dalam melakukan pemantauan kondisi ibu hamil risiko tinggi. Saran yang diberikan dengan melakukan pengembangan sistem basis data yang mengintegrasikan data terkait dengan pemantauan ibu hamil risiko tinggi
Kolaborasi Sivitas Akademika Jepang dan Indonesia dalam Penguatan Kesadaran Kebencanaan Tulus Yuniasih; Ryo Tanaka; Arief Wibowo; Didik Hariyadi Raharjo
Jurnal Relawan dan Pengabdian Masyarakat REDI Vol. 2 No. 3 (2025): Februari
Publisher : Yayasan REDI Tiga Monas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69773/t0kmx688

Abstract

Pengabdian kepada Masyarakat (Abdimas) merupakan implementasi tridharma perguruan tinggi yang bertujuan untuk memberikan solusi terhadap permasalahan yang dihadapi oleh masyarakat. Universitas Budi Luhur (UBL) bekerja sama dengan Chiba Institute of Science (CIS) Jepang dan Badan Riset dan Inovasi Nasional (BRIN) dalam program penguatan pengetahuan kebencanaan, khususnya menghadapi gempa bumi. Program abdimas ini mencakup pelatihan, simulasi evakuasi, serta pemanfaatan teknologi drone dalam pengelolaan bencana. Dalam kegiatannya, metode pelaksanaan mencakup paparan ilmiah, simulasi, dan pendekatan edukasi visual berdasarkan metode Kamishibai Jepang. Hasil kegiatan menunjukkan peningkatan kesadaran dan pemahaman civitas akademika UBL dalam aspek mitigasi bencana, pentingnya penggunaan teknologi dalam penanganan kebencanaan, serta teknik evakuasi yang benar. Program ini diharapkan memberikan kontribusi berkelanjutan dalam meningkatkan kesiapsiagaan bencana di lingkungan akademik dan masyarakat luas.
Implementasi Majority Voting pada Framework Cross-Industry Standard Process for Data Mining untuk Prediksi Kepatuhan Wajib Pajak Binarto, Antonius Jonet; Wibowo, Arief
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2165

Abstract

This research aims to predict taxpayer compliance (compliant or non-compliant) using 2,167 rows of tax data. The CRISP-DM (Cross-Industry Standard Process for Data Mining) framework was used to guide the process, as it has a structured framework. Five machine learning algorithms were compared, namely Naive Bayes, Support Vector Machine (SVM), Decision Tree, Logistic Regression, and Deep Learning, trained and tested using RapidMiner tools. To improve the prediction accuracy, the majority voting ensemble method which is the simplest and most efficient ensemble is used by combining the prediction results of these algorithms and evaluated and implemented on Google Collab using Python to validate the performance on new data and successfully provide more stable accuracy than individual models. This research contributes to tax data management, especially policy makers can optimize the use of technology to improve the efficiency of the process of monitoring and evaluating taxpayer compliance. This research also underscores the importance of exploring various machine learning algorithms and ensembles and other parameters to produce effective solutions in the field of taxation.
Trend Analysis and Prediction of Violence Against Women and Children Cases in Jakarta Based on the Victim’s Education Level Using ARIMA and SARIMA Method Kurniawan, Zaqi; Tiaharyadini, Rizka; Wibowo, Arief; Rusdah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2349

Abstract

Violence against women and children remains a critical social issue in Jakarta, Indonesia, where densely populated urban areas often correlate with increased risks of domestic abuse. The urgency of addressing this problem lies in its direct impact on public health, education, and community well-being. This study uses time series prediction models to examine and anticipate trends in the number of reported incidents of violence against women and children in Jakarta. Using publicly accessible data from Jakarta Open Data and the National Commission for the Protection of Women and Children, we applied the ARIMA and SARIMA  Models. Key variables included in the dataset are the data period, education level, and total number of victims Using three performance indicators—MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error)—to assess model accuracy the ARIMA model performed better than the SARIMA model. SARIMA recorded an RMSE of 80.26, an MAE of 66.21, and an undefined MAPE because of zero values in the real data, while ARIMA specifically obtained an RMSE of 32.22, an MAE of 32.09, and a MAPE of 5.19%. These results suggest that the non-seasonal ARIMA model is more suitable for this dataset. The study contributes to policy planning and early intervention strategies by offering a data-driven approach to predicting trends in violence within urban contexts.
Co-Authors - Arientawati - Sumardianto Adita, Ita Afifah Khaerani Afifatussalamah, Rizka Ahmad Sururi Ahmad Sururi Akbar, Ahmad Aldizar Al Fatach, M Khabib Anggraini, Julaiha Probo Anita Diana Anugrah Sandy Yudhasti Apriati Suryani Ardhianto, Angga Ardianah, Eva Ari Wibowo Arief Umarjati Asep Permana Atik Ariesta Bayu Sadewo Bayu Satria Pratama Binarto, Antonius Jonet Boerhan Hidayat, Boerhan Danar Wido Seno Darki, Ni Wayan Yustika Agustin Diah Indriani Didik Hariyadi Raharjo Didin Muhidin Dwi Kristanto Dwi Yulianti Dyah Retno Utari Dyah Retno Utari, Dyah Retno Endah Sarah Wanty Fajar Siddik Chaniago Farah Chikita Venna Farid Setiawan Farid Setiawan, Farid Febrilliani, Jihan Sastri Fenny Irawati Fernando, Donny Firman Noor Hasan Firmanty Mustofa, Vina Fitri Nur Masruriyah, Anis Fitri Rachmilah Fadmi Fitriadi, Rifqi Fitriani, Netty Fransiska Vina Sari Frenda Farahdinna Fried Sinlae Ghapur, Abdul Gurdani Yogisutanti Hadidtyo Wisnu Wardani Hananto, Agustia Handoko, Andy Rio Hanindita, Meta Herdiana Hari Basuki Notobroto Haris Achadi, Abdul HARIYANTO HARIYANTO Harun Nasrullah Hayatul Khairul Rahmat Henry Henry Hidayat, Manarul Hidayat, Sarifudlin Huda, Ratu Najmil I MADE MINGGU WIDYANTARA, I MADE MINGGU Indah Rizky Mahartika Inge Virdyna Irfan Hadi Irfan Nurdiansyah Istiqoomatun Nisaa Iwan Irawan Jasmine, Meuthia Joko Sutrisno Jovansgha Avegad Jumaryadi, Yuwan Kanasfi, Kanasfi Karma, Ni Made Sukaryati Karyaningsih, Dentik Kresno Yulianto KRESNO YULIANTO KUNTORO Kuntoro Kuntoro Kurnia Setiawan Kutanto, Haronas Larasati, Pamela Linda Lingga Desyanita Luthfi Akbar Ramadhan Mahmudah Mahmudah Mailana, Agus Maria Adiningsih Marlina, Hesti Maskur A, Moch Riyadi Megananda Hervita Permata Sari Megawati, Rina Miftahul Arifin Miftahul Arifin Mochammad Rizky Royani Moh Makruf Muhamad Fadel Muhammad Febrian Rachmadhan Amri Muhammad Risky Mulyati Mulyati Nendi, Nendi Ningrum, Yogi Ajeng Nugroho, Angelika Pratiwi Widya Nur Aisiyah Widjaja, Nur Aisiyah Nur Rohman Nurcahya, Gelar Nurfidaus, Yasmine Nursyi, Muhamad Pattipeilohy, William Frado Pattipeilohy, William Frado Pebriaini, Prisma Andita Poppy Ruliana Pradiptha, Anindya Putri Probo Anggraini, Julaiha Purwadi Purwadi Putra, Andi Agung Putra, Rinaldi Febryatna Duriat Rachmah Indawati Rahman, Reza Rahmawati, Nur Anisah Rakhman, Abdulah Rakhmat Rakhmat Rakhmat Rakhmat RAMAYU, I Made Satrya Rangkuti, Muhammad Yusuf Rizqon Ratna Ayu Sekarwati Ratna Ayu Sekarwati Relawanto, Bowo Ria Puspitasari Rika Nurhayati Riki Ramdani Saputra Rina Megawati Ririh Yudhastuti Risaychi, Diva Ajeng Brillian Ristiana, Ina Riza, Yeni Rizkiyanto, Muhamad Ardiansyah Roedi Irawan Rojakul, Rojakul Rosita Dewi, Erni Ruliana, Poppy Rusdah Ryo Tanaka Sabirin, Sahril Sadewo, Bayu Santoso, Febrina Mustika Saptari Wijaya Mulia Sari Anggar Kusuma Melati Sari, Fransiska Vina Sasongko, Raden Satiri Satiri, Satiri Selly Rahmawati Selly Rahmawati Septian Firman S Sodiq Septiani, Riska Setya Haksama Setyowati, Erlin Shofinurdin Shofinurdin Siddik Chaniago, Fajar Sigit Ari Saputro Sigit Budi Nugroho Siregar, Sutan Syahdinullah SITI NURUL HIDAYATI Sitti Aliyah Azzahra Soenarnatalina Melaniani Sudewo, Andika Hasbigumdi Sugiyarta, Ahmad Sujiharno Sujiharno Sumarna, Presma Dana Scendi Suntoro, Dimas Fahmi Tiaharyadini, Rizka TRISNAWATI, WULAN Tulus Yuniasih Umam, Mohamad Hafidhul Vasthu Imaniar Ivanoti Wahyu Cesar Wahyu Desena Wahyudi, Widi Wahyuni, Chatarina Unggul Wangsajaya, Yosia Heartha Dhalasta Wasis Budiarto Wibiyanto, Alif Dewan Daru Widiyaningrum, Diyah Kiki Widyanto, Tetrian Windhu Purnomo Yahya Darmawan Yudanto, Satyo Zakaria Anshori Zaqi Kurniawan