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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta JIKO (Jurnal Informatika dan Komputer) Informatics for Educators and Professional : Journal of Informatics Jurnal Teknik Informatika STMIK Antar Bangsa Jurnal Sisfokom (Sistem Informasi dan Komputer) Petir IJISTECH (International Journal Of Information System & Technology) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Mantik Jurnal Ilmu Komputer dan Bisnis Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Jurnal Teknik Informatika (JUTIF) International Journal of Educational Research and Social Sciences (IJERSC) SPEED - Sentra Penelitian Engineering dan Edukasi Journal of Innovation Research and Knowledge Paradigma Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Riset Sistem Informasi
Suhardjono S
Universitas Bina Sarana Informatika, Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Model Prediktif Keterlambatan Pembayaran Mahasiswa Berbasis Seleksi Fitur dengan Particle Swarm Optimization Desvia, Yessica Fara; Suharjanti; Suhardjono; Irmawati Carolina; Resti Lia Andharsaputri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.8973

Abstract

Keterlambatan pembayaran biaya kuliah menjadi salah satu permasalahan krusial di perguruan tinggi swasta yang dapat berdampak pada risiko akademik, seperti cuti atau putus studi. Penelitian ini diarahkan untuk mengembangkan model prediktif dalam mengidentifikasi keterlambatan pembayaran oleh mahasiswa, dengan memanfaatkan algoritma klasifikasi Decision Tree dan Random Tree, serta menerapkan metode Particle Swarm Optimization (PSO) untuk proses seleksi fitur. Data yang digunakan dalam penelitian ini mencakup 15.697 mahasiswa, masing-masing memiliki enam atribut sebagai variabel prediktor serta satu atribut target yang menunjukkan status mahasiswa, yaitu aktif atau cuti. Tahapan penelitian mencakup pengumpulan data, pra-pemrosesan, klasifikasi, seleksi fitur, dan evaluasi model dilakukan dengan menggunakan metrik akurasi, serta kurva ROC dan nilai AUC. Hasil penelitian menunjukkan akurasi model mencapai 98,83%, dengan peningkatan signifikan AUC pada Random Tree dari 0,632 menjadi 0,825 setelah seleksi fitur menggunakan PSO. Temuan ini menunjukkan bahwa PSO efektif dalam meningkatkan performa model klasifikasi dan mengurangi kompleksitas fitur yang tidak relevan. Sistem prediktif yang dihasilkan dapat membantu institusi pendidikan dalam melakukan deteksi dini mahasiswa berisiko menunggak, sehingga memungkinkan pengambilan tindakan preventif dan intervensi lebih tepat sasaran untuk mendukung keberlangsungan akademik mahasiswa.
New Technology in Automated Vehicles to Improve Passenger Safety Suhardjono, Suhardjono; Priyono, Priyono; Sri Iswiyanti, Agus; Parulian, Dudi; Syah Putra, Arman; Aisyah, Nurul
International Journal of Educational Research & Social Sciences Vol. 2 No. 3 (2021): June 2021
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijersc.v2i3.96

Abstract

The background of this research is by prioritizing how to improve the safety of passengers on a vehicle with increased security so that if an accident occurs, the passenger does not suffer any injury. If necessary, it is not scratched on the body. With this research, it is necessary to increase security in order to provide maximum protection. for passengers and motorists. The method used in this study using the literature review method based on research that has been done previously so that it can be the basis for this research. With the literature review, the research will be able to find new research problems so that this research can be the latest research in order to serve as the basis for future research. In this study, we will find out how to protect passengers on a vehicle with ways that passengers can do so that the security side can be improved. Therefore, the use of security in a vehicle is very important so that it can help drivers and passengers in driving. In this study will produce a proposed system that can be used as a basis as a guide in order to protect passengers and motorists and can improve the safety side of driving.
Application Design "Test Job Application" On Android OS Using The AHP Algorithm Suharjono; Hari Sugiarto; Istiqomah Sumadikarta; Muhammad Ryansyah; Muhammad Hilman Fakhriza; Arman Syah Putra
International Journal of Educational Research & Social Sciences Vol. 2 No. 5 (2021): October 2021
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijersc.v2i5.185

Abstract

The background of this research is how to make an application that makes it easier for job seekers to find work with an Android-based application method so that it can be done anywhere and anytime with a very small quota. Helped and employers and companies will also be helped. The method used in this research is to use the method of studying literature or literature by reading many journals related to this research, after that make a prototype so that it can be given an appearance. This research will be able to see whether it is successfully used or not. The problem raised in this research is how to help job seekers find work without leaving the house and being able to search for jobs around the world using only an Android based application that can be done from home. This research produces a prototype system that will be made in the future, so that it can help workers in finding work and companies in finding workers.
Classifying Half-Unemployment Levels in Indonesian Provinces: A K-Means Approach for Informed Policy Decisions Suhardjono Suhardjono; Hari Sugiarto; Dewi Yuliandari; Adjat Sudradjat; Luthfia Rohimah
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 2 (2023): September 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i2.7390

Abstract

Half-level unemployment refers to individuals who work part-time and are not fully employed. Increasing the half-poverty rate from year to year can lead to challenges in the lives of these individuals. The issue arising with the rise in the half-poverty rate is the government's difficulty in prioritizing areas that require intervention to address these problems. Consequently, an increase in the half-poverty rate can have adverse consequences. Therefore, it is necessary to categorize underemployment rate data obtained from public sources, specifically from data.go.id, using the widely recognized clustering method known as K-Means. The purpose of this categorization is to identify and classify provinces with a significant prevalence of half-poverty levels. This classification will assist the government in making informed decisions when addressing individuals who meet the half-poverty criteria. The results were obtained by grouping the data from the first to the eighteenth iteration into three categories: 'large' (C1), 'medium' (C2), and 'small' (C3) in terms of half-poverty levels. Group C1 comprises 17 provinces with a high half-poverty rate, while C2 includes only 2 provinces, and C3 covers 16 provinces with a significant half-poverty rate. Based on these findings, it is advisable for the Indonesian government to consider implementing policies aimed at reducing the poverty level by half. Priority should especially be given to the C1 group when creating employment opportunities for the province's residents
PENERAPAN ALGORITMA KLASIFIKASI C4.5 REVIEW PELANGGAN DALAM BERTRANSAKSI PADA PT. DAPOER MAMIH Wahana Indra Komala; Andri Yansah; Resti Pebrina; Suhardjono Suhardjono
Jurnal Riset Sistem Informasi Vol. 3 No. 1 (2026): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/p6wz6n47

Abstract

Wahana Indra Komala (19242542), Andri Yansah (19242561), Resti Pebrina (19242563), Implementation of C4.5 Classification Algorithm Customer Review in Transactions at PT. Dapoer Mamih Dapoer Mamih is a company engaged in the culinary field and is committed to providing the best service to its customers. One way to radiate service quality and customer satisfaction is by analyzing customer Reviews. This study aims to classify customer Reviews in transactions using the C4.5 classification algorithm. The C4.5 algorithm was chosen because of its ability to form an effective Decision Tree in handling categorical and numeric data and handling missing data values. The data used in this study came from customer Reviews collected by the company. The analysis process begins with the data preprocessing stage, attribute selection, model training, and evaluation of model classification performance. The results of the study show that the C4.5 algorithm is able to group customer Reviews into certain categories such as positive, neutral, and negative with an adequate level of accuracy. These findings can be the basis for companies to make strategic decisions in improving service quality and customer experience. Keywords: Classification; C4.5; Customer Reviews; Decision Trees; Data Mining.
Prediction Of Infant Mortality Using The Decission Tree And Genetic Algorithm Methods Suhardjono Suhardjono; Adjat Sudradjat; Bilal Abdul Wahid; Hari Sugiarto; Hafis Nurdin
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1819

Abstract

One of the things that plays a role in reducing infant mortality is the government. Based on infant mortality data in Jakarta in 2018 that has been previously tested with the decision tree algorithm, the update in this study is to use the genetic algorithm. The purpose of the update is to increase the accuracy of the results to be maximized. From the test results with the DT algorithm optimized by GA, the maximum accuracy value is 100%, and each attribute has a weight value of 1 where the value is the maximum value. After obtaining maximum results, the data will be used to reduce infant mortality, especially in Jakarta
Co-Authors Abdul Hamid Abdul Hamid Abdul Hamid ADE RISNA SARI Adjat Sudradjat Ainayah Al Fathiyyah Andri Yansah Anus Wuryanto Arman Syah Putra Arman Syah Putra Arman Syah Putra Cakranegara, Pandu Adi Desvia, Yessica Fara Dewi Yuliandari Firstianty Wahyuhening Fibriany Ganda Wijaya Ganda Wijaya, Ganda Gilang Purnama Adji Hafis Nurdin Hari Sugiarto - UBSI Hendra Hendra Herlina, Maria Hermanto Hermanto Hermanto Hilmiah Indah Ariyati Irmawati Carolina ispandi ispandi Istiqomah Sumadikarta Jajang Jaya Purnama Kholifah, Desiana Nur Lisnawanty Maisyaroh Mochammad Abdul Azis Muhammad Fahmi Muhammad Faisal Muhammad Hilman Fakhriza Muhammad Iqbal Muhammad Ryansyah Nanny Mayasari Nurul Aisyah Nurul Aisyah Olivia, Shinta Parulian, Dudi Priyono Priyono Priyono Priyono Resti Lia Andharsaputri Resti Pebrina Ridwansyah Ridwansyah Ridwansyah Rino Ramadan Rio Wirawan Rohimah, Luthfia Rudy Max Damara Gugat Sri Iswiyanti, Agus Suhardjono Suhardjono suharjanti Suryadhitia, Rachmat Syah Putra, Arman V.H. Valentino Wahana Indra Komala Wahid, Bilal Abdul Yumi Novita Dewi