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All Journal Jurnal Teknoin Jurnal Teknologi Jurnal Informatika dan Teknik Elektro Terapan INFORMAL: Informatics Journal Proceeding SENDI_U RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA IJIS - Indonesian Journal On Information System JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT JMAI (Jurnal Multimedia & Artificial Intelligence) Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Innovation and Future Technology (IFTECH) Jurnal Informatika dan Rekayasa Perangkat Lunak JATI (Jurnal Mahasiswa Teknik Informatika) INFORMASI (Jurnal Informatika dan Sistem Informasi) Jurnal Sistem Komputer dan Informatika (JSON) jurnal syntax admiration Jurnal Sistem Informasi dan Sistem Komputer Jurnal Pengabdian Nasional (JPN) Indonesia Jurnal Teknik Informatika (JUTIF) Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Buletin Poltanesa Jurnal Pendidikan dan Teknologi Indonesia Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Teknik Informatika Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sains dan Teknologi Journal of Information System and Artificial Intelligence Innovative: Journal Of Social Science Research TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Teknomatika: Jurnal Informatika dan Komputer Jurnal Pengabdian Nasional (JPN) Indonesia Jurnal Publikasi Teknik Informatika
Sidiq Purnomo, Agus
Universitas Mercu Buana Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI KARIR UNTUK SISWA SMA MENGGUNAKAN METODE PROFILE MATCHING BERBASIS TEORI HOLLAND Aditya Yoga Saputra; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7967

Abstract

High school students often face challenges in choosing a career due to guidance processes that remain conventional, inefficient, and impersonal. To provide a more objective and scientifically sound career recommendation solution, this study focuses on the design and implementation of a Decision Support System (DSS) built on a web-based platform. The system integrates Holland’s personality theory (RIASEC) with the Profile Matching method to compare students’ interest scores against the ideal profiles of six career alternatives. The algorithm’s operation begins by measuring the distance between a student’s actual profile and the career profiles established as ideal standards. This distance value is then converted into systematically determined weight scores. The final stage involves aggregating the Core Factor and Secondary Factor scores, with a 60% weight for the Core Factor and 40% for the Secondary Factor, which then yields a final score as the basis for ranking. The system was implemented using Laravel, React, and PostgreSQL, and tested on 32 students. Validation was conducted by comparing the system’s recommendations with expert psychological assessments. Test results showed a 78.13% level of agreement, where the majority of recommendations aligned with the students’ dominant personality characteristics. These findings demonstrate that the integration of computational approaches and career psychology theory can enhance the efficiency, transparency, and accuracy of the guidance process, while also serving as a strategic tool for counselors in data-driven student potential mapping.
SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KESIAPAN PSIKOLOGIS CALON PEKERJA MIGRAN INDONESIA DENGAN AHP DAN TOPSIS: SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KESIAPAN PSIKOLOGIS CALON PEKERJA MIGRAN INDONESIA DENGAN AHP DAN TOPSIS Rizal Rio Andrian; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7978

Abstract

The selection of psychological readiness for Indonesian Migrant Worker Candidates (CPMI) at placement institutions often faces subjectivity constraints that risk mental unpreparedness in destination countries. This study aims to implement a Decision Support System (DSS) using a hybrid Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to enhance selection objectivity. The system development methodology follows the Turban model encompassing intelligence, design, choice, and implementation phases. The research employs eight psychological criteria involving three experts for criteria weighting and 40 alternative CPMI candidates for ranking. AHP weighting results indicate Work Motivation (0.206) and Discipline (0.203) as the most dominant parameters with validated Consistency Ratio ≤ 0.1. TOPSIS implementation produces preference values ranging from 0.134 to 0.882, classified into Ready, Sufficiently Ready, and Needs Strengthening categories. Sensitivity analysis demonstrates that the hybrid model aggregation is more robust indicated by the high stability of top-ranking candidates compared to individual expert preference scenarios and Equal Weight methods. In conclusion, this system successfully transforms qualitative assessments into transparent and accurate quantitative indicators to support managerial decision-making in the CPMI selection process.
EKSTRAKSI INFORMASI NOTA BELANJA INDONESIA MENGGUNAKAN INDOBERT DAN PENANGANAN NOISE BERBASIS FUZZY STRING MATCHING Niko Felix Chandra Arisco; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8103

Abstract

Indonesian shopping receipts have essential information like items, prices, taxes, and totals; however, their language is unstructured and susceptible to Optical Character Recognition (OCR) errors, such as misidentified characters and incomplete tokens. These problems make entity extraction less accurate, especially on numeric fields. Also, rule-based methods don't scale well, and deep learning models need a lot of labelled data. This study concentrates on developing a resilient information extraction system capable of handling text noise in Indonesian receipts. This method refines IndoBERT for Named Entity Recognition utilising the Consolidated Receipt Dataset (CORD), which has been manually re-annotated using the BIO scheme to identify four entities: ITEM, PRICE, TAX, and TOTAL, comprising 800 training instances, 100 validation instances, and 100 test instances, alongside Levenshtein Distance-based Fuzzy String Matching and rule-based validation. The fuzzy module is evaluated in two configurations, pre-processing and post-processing, via a six-scenario ablation study (S1-S6) in conjunction with OCR typo augmentation. The test findings indicate that the optimal configuration is S6 (IndoBERT + augmentation + FSM post-processing + rule-based validation), achieving a macro F1-Score of 0.7807, surpassing both the pre-processing placement (S5: 0.7733) and the pure IndoBERT baseline (0.7601). Rule-based validation yields the greatest contribution, with an F1 improvement of up to +0.028 due to enhanced recall. The conclusion is that fuzzy string matching is more effective as a post-processing technique, and the pipeline is implemented in a Streamlit-based online prototype that generates structured JSON output.
SISTEM KINERJA DAN KEPEGAWAIAN MENGGUNAKAN MULTI FACTOR EVALUATION PROCESS (STUDI KASUS: SMK MA'ARIF 1 TEMON YOGYAKARTA) Agus Sidiq Purnomo; Anief Fauzan Rozi; Dina Yulina Heriyani
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8150

Abstract

A personnel information system is an important requirement for educational institutions in managing employee data digitally. SMK Ma'arif 1 Temon Yogyakarta currently does not have an integrated personnel information system (SIMPEG), so the process of recruitment, attendance, employee profiles, leave applications, career paths, and performance appraisal are still done manually. This study aims to produce a prototype of a personnel information system and to apply the Multi Factor Evaluation Process (MFEP) method for employee performance assessment. The system development method uses the Waterfall Model with assessment criteria including years of service, education level, position, rank, and additional duties. The results showed that the system was able to perform MFEP calculations properly, producing the highest ranking for Alternative A22 with a score of 4.30. System functionality testing shows all features run well. This prototype can be a solution for digitalization of personnel management at SMK Ma'arif 1 Temon.
ANALISIS SPASIAL KLASTER KECELAKAAN LALU LINTAS MENGGUNAKAN ALGORITMA K-MEANS BERBASIS QGIS UNTUK IDENTIFIKASI BLACK SPOT DI KABUPATEN GUNUNGKIDUL Lukky Astuti; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8157

Abstract

Traffic accidents are a serious problem in Gunungkidul Regency, with more than 947 recorded incidents throughout 2025. This study aims to analyze spatial distribution patterns of accidents, identify risk cluster characteristics, determine black spot locations, and formulate mitigation recommendations. The method includes Risk Index calculation using Weighted Risk Assessment with five criteria (C1-C5), followed by the K-Means clustering algorithm validated using the Elbow Method to determine the optimal number of clusters (k=3) and the Silhouette Score (0.6645) to measure cluster quality, as well as QGIS-based spatial visualization. The results on 500 sample data show that the optimal number of clusters is k=3 with a Silhouette Score of 0.6645. Cluster 1 (low risk) includes 164 data (32.8%), Cluster 2 (medium risk) 273 data (54.6%), and Cluster 3 (black spot) 63 data (12.6%). Statistical validation using the Kruskal-Wallis test showed significant differences between clusters (H=419.5850; p<0.001). The main black spots are concentrated on the Wonosari-Yogyakarta Road, Patuk and Playen segments. This study produces specific mitigation recommendations for each risk cluster.
DISTROMATCH: SISTEM REKOMENDASI DISTRIBUSI LINUX DENGAN TOPSIS, BAYESIAN SHRINKAGE, DAN SOFT CONSTRAINT Aan Widianto; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8190

Abstract

The diverse Linux ecosystem complicates the selection of suitable distributions for users, particularly beginners. This study develops Distromatch, a web-based Decision Support System recommending from 30 Linux distributions using TOPSIS, enhanced with Bayesian shrinkage adjustment and user-level preference penalty as a soft constraint mechanism. Its five-stage pipeline includes criteria weight normalization from user questionnaires, TOPSIS calculation, Bayesian shrinkage, user-level preference penalty, and final ranking. Functional testing confirmed system operation, and domain expert validation for three user profiles (beginner, intermediate, advanced) showed contextually valid Top-5 recommendations, consistent with the Linux ecosystem. Bayesian shrinkage proved to be effective reduced bias for distributions with limited reviews, while soft constraints ensured level-mismatched distributions appeared in rankings with reduced scores. Calculation transparency is provided via an audit page.
Sistem Pendukung Keputusan Pemilihan Karir Mahasiswa Informatika dengan Metode SAW Arya Agus Wicaksana; A Sidiq Purnomo
Jurnal Publikasi Teknik Informatika Vol. 4 No. 2 (2025): Mei : Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v4i2.4701

Abstract

The significant mismatch between graduates’ competencies and industry demands poses a critical challenge in career decision-making, particularly within the field of Information Technology. 
PENERAPAN METODE SAW DALAM SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN WAJIB PAJAK BERPRESTASI Firmansyah A Abdulrahman; Agus Sidiq Purnomo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7149

Abstract

Penelitian ini bertujuan untuk mengembangkan Sistem Pendukung Keputusan (SPK) berbasis metode Simple Additive Weighting (SAW) untuk menentukan wajib pajak berprestasi di Kota Gorontalo. Wajib pajak adalah individu, badan usaha, atau entitas hukum yang berkewajiban memenuhi pembayaran pajak sesuai ketentuan hukum. Selama ini, penilaian wajib pajak berprestasi dilakukan secara subjektif oleh pegawai Badan Keuangan, yang berisiko menghasilkan keputusan kurang akurat. Metode SAW digunakan untuk menilai wajib pajak berdasarkan empat kriteria utama: besaran pembayaran pajak sesuai potensi, ketepatan waktu pembayaran, kelengkapan administrasi perpajakan, dan kepatuhan terhadap regulasi. Hasil perankingan 3 teratas menunjukkan WP-1 (Rm. Marry Coffee) memperoleh skor tertinggi 1.00, diikuti oleh WP-2 (Rm. D'cozy Can Cook) dengan skor 0.95, dan WP-10 (Rm. Grande Bistro) dengan skor 0.94. Sistem berbasis web yang dikembangkan meningkatkan efisiensi, transparansi, dan objektivitas dalam evaluasi wajib pajak. Dengan penelitian ini, metode SAW diharapkan dapat diterapkan secara luas untuk mendukung penilaian wajib pajak berprestasi secara adil dan akurat, serta mendorong wajib pajak lain untuk memenuhi kewajibannya dengan baik.
SPK UNTUK MENENTUKAN LOMBA PEMILIHAN PELAKSANA POSYANDU TERBAIK KABUPATEN BREBES MENGGUNAKAN METODE MFEP Rosmawatul Khotimah; Agus Sidiq Purnomo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7113

Abstract

Pelaksana kegiatan posyandu memiliki peran penting dalam mendukung kesehatan masyarakat, terutama ibu dan anak, melalui berbagai layanan kesehatan dasar. Namun, proses seleksi pelaksana posyandu terbaik sering menghadapi tantangan objektivitas dan akurasi, terutama jika dilakukan secara manual. Penelitian ini bertujuan untuk mengembangkan Sistem Pendukung Keputusan (SPK) dengan menerapkan metode Multi Factor Evaluation Process (MFEP) untuk mempermudah proses evaluasi terhadap pelaksana posyandu di Kabupaten Brebes. MFEP dipilih karena mampu menangani berbagai kriteria evaluasi yang kompleks dengan memberikan nilai kepada setiap kriteria sesuai dengan tingkat kepentingannya. SPK ini dirancang menggunakan teknologi berbasis web, melibatkan pemrograman PHP, basis data MySQL, dan framework CodeIgniter, dengan data yang diperoleh dari wawancara pakar serta dokumentasi lomba posyandu tahun 2023. Dalam pengujian sistem, Posyandu 9 (Mawar Sigambir) dinobatkan sebagai pelaksana terbaik dengan skor tertinggi 3.64, diikuti oleh Posyandu 11, 7, 14, dan 10. Sistem ini membuktikan kemampuannya dalam meningkatkan efisiensi, akurasi, dan objektivitas penilaian, sekaligus memotivasi pelaksana posyandu lainnya untuk meningkatkan kinerja. Hasil penelitian menunjukkan bahwa SPK berbasis MFEP tidak hanya memberikan rekomendasi yang akuntabel, tetapi juga diharapkan menjadi langkah strategis dalam mendukung pengelolaan posyandu, meningkatkan kualitas pelayanan kesehatan, dan mempromosikan kesejahteraan masyarakat di tingkat lokal.
Sistem Rekomendasi Mobil Listrik Menggunakan Metode SAW Ahmad Baehaqi; Agus Sidiq Purnomo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7169

Abstract

Penelitian ini bertujuan merancang sistem rekomendasi mobil listrik berbasis metode Simple Additive Weighting (SAW) untuk membantu konsumen memilih mobil yang paling sesuai dengan kebutuhan. Sistem ini mempertimbangkan berbagai kriteria, seperti harga, kapasitas baterai, dan fitur kendaraan, dengan pendekatan berbasis bobot yang mencakup kriteria biaya (cost) dan manfaat (benefit). Data penelitian diperoleh melalui studi literatur dengan menelaah berbagai sumber referensi yang relevan. Metode SAW digunakan untuk menganalisis alternatif berdasarkan normalisasi matriks keputusan, sehingga memungkinkan perbandingan nilai antar-alternatif dalam skala yang setara. Penelitian ini menggunakan 22 nama mobil listrik dari berbagai merek di Indonesia sebagai alternatif. Hasil perhitungan menunjukkan bahwa sistem dan perhitungan manual menghasilkan nilai yang sama, dengan nilai tertinggi sebesar 0,793333 yang diraih oleh mobil listrik Mifa 9 dari merek Maxus. Kesamaan ini membuktikan bahwa penelitian memiliki tingkat akurasi 100%. Sistem rekomendasi yang dirancang tidak hanya mempermudah konsumen dalam memilih mobil listrik, tetapi juga berkontribusi pada percepatan adopsi kendaraan ramah lingkungan di Indonesia. Dengan hasil ini, penelitian diharapkan mampu menjadi landasan pengembangan sistem pendukung keputusan yang lebih efisien di masa mendatang.
Co-Authors Aan Widianto Ade Fitriadin Aditya Yoga Saputra Agung Prinato Ahmad Baehaqi Alfian Romadhon Ali, Ficky Septian Andi Atmaja Kusuma Wijaya Andres Anief Fauzan Rozi Anief Fauzan Rozi Anief Fauzan Rozi Anief Fauzan Rozi Ari Cahyono Arif Wiji Setiyanto Arifi Zulaika Aris Susanto Arya Agus Wicaksana Bagas Irvan Bagaskara Barbo Bero Berita Estu Widodo Bima Pangestu, Danang Bowo Nugroho Dany Suktiawan Irman Fiano Dede Widiyanto, Dede Widiyanto Dewi, Mellania Metta Dina Yulina Heriyani Dionata Pin Asa Disantis Dwiki Kurniawan, Yohanes Edwin Rafiza Pradana Nasution Elisabeth Helsi Nggebu Emi Agustina Erlangga Samudera Kencana Fandi Azis Fauzan Rozi, Anief Fauzyah, Luthfia Feby Kristina Butar Butar Fendy Nugraha, Arbiana Fernando Bayu Andika Firmansyah A Abdulrahman Gaputra, Raygo Genoveva Seniyati Moruk Gita Prastianingrum Hafiid Alfayed, Muhammed Hukom, Jessy Indah Susilawati Irfan Pratama Ismunu, R. Sumarwan Jery Mechael Pentagon Lumbantoruan Jeseka Bintar Laksana Jevi Ariyanti Kadek Ayu Puspita Dewi Kali, Steven Kamto, Kevin Arsan Letsoin, Amrul Louis Fernando Sinaga Lukky Astuti M. Ridwan Nur Septian Maharani, Zelvia Olga Maria Anggelina Klau Maria Mitro Wid Eko, Antonius Marsela, Dwi Maya Putri Nur Fajri Mokoagow, Mohamad Akbar Mutaqin Akbar Muthia Gidriani Maelan Na'imah, Alifatun Nadafi'ah Hari Fitri Natalia Anjela Sagat Niko Felix Chandra Arisco Nisriina Nuur Hasanah Octy Kartika Dewi Prasetyaningrum, Putri Taqwa Putri, Novita Anggraini Rahmandhita Fikri Sannawira Rahmandhita Fikri Sannawira, Rahmandhita Fikri Ridi Ferdiana Rika Handayani Rizal Rio Andrian Robi Adi Saputra Rosmawatul Khotimah Rosmeri Maramba Santoso, Muhammad Iqbal Rafid Sembiring, Kristian Eykman Sisilia buik Stefanus M Patanduk Subardjo, Ratna Yunita Setiyani Suharjo, Imam Supatman Supatman Supriyantoo Susanto, Handy Tri Astuti Prihatin Venola Onibala, Injili Wahyu A, Shella Widatin Mayasari Wijayanti, Berlian Rezki Wulan Sari Kaslumin Yasser Yazid Mohammad Yuliana Rahayaan Yulisa Safitri