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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Eksplora Informatika JURNAL PENDIDIKAN TAMBUSAI JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jusikom: Jurnal Sistem Informasi Ilmu Komputer bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jifosi PLAKAT : Jurnal Pelayanan Kepada Masyarakat Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Jurnal Ilmiah Teknologi Informasi dan Robotika JUSTIN (Jurnal Sistem dan Teknologi Informasi) International Journal Of Computer, Network Security and Information System (IJCONSIST) AJARCDE (Asian Journal of Applied Research for Community Development and Empowerment) Jurnal Ilmiah Teknik Informatika (TEKINFO) Sisfo: Jurnal Ilmiah Sistem Informasi Digital Transformation Technology (Digitech) MASALIQ: Jurnal Pendidikan dan Sains JEECS (Journal of Electrical Engineering and Computer Sciences) Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Journal of Innovative and Creativity Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) International Journal of Information Engineering and Science Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara
Ani Dijah Rahajoe
Department Of Computer Science, Faculty Of Informatics, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Medicine & Pharmacology Social Sciences Transportation Other

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Route Optimization of Waste Carrier Truck using Breadth First Search (BFS) Algorithm Muhammad Fahreal Bernov; Ani Dijah Rahajoe; Budi Mukhamad Mulyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 7 No. 2 (2022): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v7i2.23

Abstract

Waste problems have always been the main focus which still occurs in cities and regencies in Indonesia, andalso Sidoarjo Regency is no exception. Increasingly rapid population growth is one of the factors in the increasingpiles of waste in Sidoarjo Regency. The large number of villages with long distances and a large area means that wastecollection cannot be carried out on time, causing accumulation of waste that disrupts residents' daily activities. Thewaste transportation system in Sidoarjo Regency has so far not been optimal because there are still several problemswith the accumulation of waste in several sub-districts.In this study, an optimal route search system was created using the Breadth First Search and Depth First SearchAlgorithms as a search comparison in order to make it easier for Sanitation Service officers to carry out the wastetransportation process by considering the optimal destination location route according to input from the user. Theresults of this study will display information on the comparison of the total distance traveled and the total volumetraveled by the Breadth First Search and Depth First Search algorithms with different differences.
KNN and Webgis Classification to Recommend Mountain Location According to Hiker Abilities Shagi Hisyam Al Fathony; Ani Dijah Rahajoe; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 7 No. 1 (2022): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v7i1.222

Abstract

The increasing number of climbers has an impact on the need for a system that can recommend mountains for climbingaccording to the ability of climbers. This study aims to create a system that can help climbers determine the mountainaccording to their abilities. Researchers use one of the methods in data mining, namely classification, using the K =Nearest Neighbor (K-NN) algorithm.This research has produced a web-based system where this system can classify and provide recommendationsaccording to the ability of climbers. This system is equipped with a hiking trail map which is expected to help make iteasier for climbers to choose the mountain they will climb.
Decision Support System for Inheritance Distribution According to Islamic Law Using the Forward Chaining Method Mas Nurul Hamidah; Arif Arizal; Andriano Lukas; Rifki Fahrial Zainal; Ani Dijah Rahajoe
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 6 No. 2 (2021): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v6i2.206

Abstract

The rapid development of information technology in all aspects of the field in this digital era is very important, such as in the fields of business economics, agriculture, culture and religion. In the religious field, technological advances will make it easier for people to learn and seek information in the religious field, as is the case in the issue of inheritance distribution which so far not all people understand it, and also the limited number of experts in the field of inheritance. Religious science is expected to provide a way to learn about inheritance easily, and with this expert system the community will be facilitated in terms of inheritance distribution problems using the forward chaining method, the system will be tested with a 100% accuracy level value in 10 tests with variables different heirs, from the test results, it is found that the system can be used properly.
Optimasi Hyperparameter CatBoost dengan Particle Swarm Optimization untuk Klasifikasi Hipertensi Muhammad Iqbal Al Afgany; Ani Dijah Rahajoe; Henni Endah Wahanani
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16292

Abstract

Hypertension is a cardiovascular disease affecting 11,952,694 residents aged ≥15 years in East Java in 2019, yet only 40.1% received healthcare services. This study aims to analyze the effect of Particle Swarm Optimization (PSO) on CatBoost algorithm performance in hypertension level classification. The research dataset combined data from Puskesmas Kepatihan Gresik (191 data) and Kaggle (12,500 data) divided with an 80:10:10 ratio. PSO was used for CatBoost hyperparameter optimization including iterations, depth, learning_rate, and l2_leaf_reg. Model evaluation utilized accuracy, precision, recall, and F1-score metrics. Results show that CatBoost with PSO optimization achieved 96% accuracy with optimal configuration of iterations=100, depth=3, learning_rate=0.055, and l2_leaf_reg=3, 2% higher than without optimization (94%). This study proves the effectiveness of PSO in optimizing CatBoost hyperparameters for more accurate early hypertension detection
ANALISIS KINERJA LOGISTIC REGRESSION, K-NEAREST NEIGHBOR, DECISION TREE, DAN RANDOM FOREST UNTUK PREDIKSI PUTUS STUDI MAHASISWA BERBASIS DATA AKADEMIK TABULAR Angga Dwi Cahyono; Khansa Alyssa Fauziyah; Arif Dwi Putra; Nafiendra Praba Hendyka; Aryo Bagus Satrio Wicaksono; Ani Dijah Rahajoe
Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara Vol. 5 No. 1 (2026): Volume 5 No 1 Tahun 2026
Publisher : PT Siantar Codes Academy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.260396/90f8b259

Abstract

Putusnya studi mahasiswa menjadi masalah bagi institusi perguruan tinggi karena berdampak pada kualitas lulusan, reputasi institusi, dan efisiensi pengelolaan pendidikan. Perguruan tinggi seringkali menggunakan pendekatan secara konvensional dalam melihat perkembangan mahasiswa. Namun, pendekatan konvensional tidaklah efektif karena bersifat subjektif dan memiliki bias kognitif. Pendekatan dengan menggunakan data mining dapat menjadi solusi bagi perguruan tinggi untuk dapat dijadikan sebagai sistem peringatan dini dalam memprediksi mahasiswa yang berpotensi mengalami dropout. Penelitian ini bertujuan untuk membandingkan empat algoritma klasifikasi data mining dalam mendeteksi potensi putusnya studi mahasiswa yaitu Logistic Regression, KNN, Decision Tree, dan Random Forest dengan menggunakan dataset sekunder yang didapatkan dari website Kaggle yang terdiri dari 4.424 data mahasiswa dengan variabel yang berbeda-beda. Evaluasi performa model dilakukan dengan menggunakan metrik accuracy, precision, recall, dan F1-Score. Hasil penelitian menunjukkan bahwa model Random Forest adalah model dengan performa terbaik dengan nilai precision dan F1-Score tertinggi dibandingkan algoritma lainnya. Model ini dapat digunakan sebagai dasar sistem peringatan dini untuk mendeteksi mahasiswa yang berpotensi mengalami dropout.
Efisiensi Pendataran Memori pada Komputasi Matriks Padat: Studi Komparatif Rust dan Go Hamdan Yuwafi Mastu Wijaya; Ani Dijah Rahajoe; Retno Mumpuni
Jurnal Ilmiah Teknik Informatika (TEKINFO) Vol. 27 No. 2 (2026): TEKINFO Vol 27 No 2 Oktober 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

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

Abstract

Modern high-performance computing (HPC) demands face the Memory Wall, wherememory layout efficiency is now more crucial in determining performance than the numberof processor cores. Nested dynamic array structures inherently induce pointer chasing,which breaks hardware-level data locality. This paper presents an architectural comparativestudy between the concurrency models of Go (M:N scheduling) and Rust (1:1 kernelthreads) through the evaluation of intensive matrix computations on the order of 500x500to 2000x2000. Experiments contrast conventional nested memory structures against a flatlinear layout (1D Contiguous Memory Layout). Empirical results from isolated tests showthat Go's native implementation dominates in efficiency at medium scales due to its lowGoroutine initiation overhead. However, in Rust, nested structures induce exponentiallatency spikes due to high cache miss metrics. Memory flattening in Rust has been shownjournals.upi-yai.ac.id/index.php/TEKINFO/issue/archiveP-ISSN: 1411-3635E-ISSN: 2962-5645TEKINFO VOL. 27, NO. 2, Oktober 2026 1to eliminate pointer chasing, reduce computational latency by up to 32.3% at the highestorder, and trigger the activation of automatic vectorization (SIMD) instructions by theLLVM compiler. In contrast, manual application of linear index transformations in Goactually creates a massive performance degradation of 79% due to the accumulatedarithmetic calculation load that the runtime fails to optimize. This research demonstratesthat there is no absolute language superiority; architecture selection should be based on thealignment of Data-Oriented Design with compiler capabilities, providing concreterecommendation parameters for designing industrial-scale software systems.
Sensitivity Test Of Simple Additive Weighting And Weighted Product Methods For Toddler Nutritional Status Nadia Dita Salsabila; Ani Dijah Rahajoe; Afina Lina Nurlaili
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3713

Abstract

Toddler nutritional status is an important indicator of child health and development and requires accurate assessment. In Posyandu, nutritional evaluation is often performed manually, which may lead to inefficiencies and inconsistencies when processing large amounts of data. Decision Support Systems (DSS) can assist health workers in conducting more systematic and objective assessments. Previous studies have applied multicriteria decision-making methods such as Simple Additive Weighting (SAW) and Weighted Product (WP) in various decision-making contexts. However, most studies mainly focus on producing ranking results and rarely examine how sensitive these methods are when criteria weights change. In addition, only limited research evaluates these methods using real anthropometric data collected from community health services such as Posyandu. Therefore, this study aims to analyze and compare the sensitivity of the SAW and WP methods in determining toddler nutritional status using empirical anthropometric data. The dataset consists of 412 toddlers collected from Posyandu activities, including gender, age, weight, height, and body mass index, which were converted into nutritional indicators. Sensitivity was assessed by modifying each criterion weight under two scenarios (0.5 and 1) and measuring the percentage change in the resulting preference values. The results show that the SAW method produced a change of 4%, whereas the WP method showed a change of 0.0028%. These findings indicate that SAW is more responsive to weight variations, while WP produces more stable preference values. The results provide empirical insight into the behavior of different multicriteria decision-making methods when applied to real nutritional monitoring data.
Co-Authors Achmad Ario Dwi Maulana Agung Subekti, Mohamad Rafli Agussalim Agussalim Agussalim, Agussalim Ainur Rahim Akash, Fransisco Rivaldi Andre Leto Andreas Nugroho Sihananto Andriano Lukas Angelo A Beltran Angelo A Beltran Jr Angga Dwi Cahyono Aninditya Daniar Anna Fauziah Arif Arizal arif arizal Arif Dwi Putra Arif Setyo Wibowo Aryo Bagus Satrio Wicaksono Azaidane, Dandi Azmi Maulana Mahardika Bawazir Fadhil Mohammad Bawazir Fadhil Muhammad Bimantoro, Bisma Satrio Brahmantio Widyo Trenggono Budi Mukhamad Mulyo Chaurina, Agfanadita Rezkia Denisa Septalian Alhamda Dhian Satria Yudha Kartika Dian Agus Prawinata Eka Prakarsa Mandyartha Eva Yulia Puspaningrum Fairus Irhab Adinata Efendi Fajar Indra Nur Alam Feriza, Reyana Dinda Maulan Fransiska, Amelia Hamdan Yuwafi Mastu Wijaya Henni Endah Wahanani I Gede Susrama Mas Diyasa I Gede Susrama Mas Diyasa Ida Retno Moeljani Indartono, Taqiyya Irsyad Rafi Naufaldi Jr, Angelo A. Beltran Kartini Kartini Khansa Alyssa Fauziyah M Mahaputra M. Mahaputra Made Hanindia Prami Swari Mas Nurul Hamidah Maulana, Hendra Megantara, Sofia Ramadhani Muchamad Dicky Alifiansyah Muchlisiniyati Safeyah Muhammad Aldi Maulana Muhammad Fahreal Bernov Muhammad Farhan Maulana Muhammad Iqbal Al Afgany Muhammad Rizky Firdaus Muhammad Suriansyah Muttaqin, Faisal Nadia Dita Salsabila Nafiendra Praba Hendyka Nurlaili, Afina Lina Nurlaili, Afina Lina P. Eko Prasetyo Pahlevy, Mohammad Reza Pangesti N Perkasa, Laurensius Gading Surya Piter Rudi Irson Rivaldo Lapon Pradana, Ilham Akbar Pramnesti, Adisty Regina Putra Bramantyo, Adam Putra, Brian Akhdan Rangga Laksana Aryananda Retno Mumpuni Retno Mumpuni Reza Aminullah Rifki Fahrial Zainal Rino Zakaria Satrio Budi Wahyuono Shagi Hisyam Al Fathony Soffiana Agustin, Soffiana Subekti, Mohamad Rafli Agung Suriansyah, Muhammad Suryantari, Putu Anggi Syariful Alim Waskito, Muhammad Rizal Winarko, Edi Yushinta Aristina Sanjaya