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All Journal Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Pengabdian Masyarakat Tekno
Riefky Sungkar
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Computer Science & IT Control & Systems Engineering Engineering

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Penerapan Algoritma C4.5 , SVM Dan KNN Untuk Menentukan Rata-Rata Kredit Macet Koperasi Siswanto, Siswanto; Riefky Sungkar; Basuki Hari Prasetyo; M.Anif; Subandi, Subandi; Gunawan Pria Utama; Raden Sutiadi; Buana Suhurdin Putra
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

problem that often occurs is the difficulty in determining the average bad credit spread across 7,823 savings and loan cooperatives in Indonesia. The main problem faced by savings and loan cooperatives is the difficulty in identifying and mitigating credit risks that can cause bad credit. Bad credit not only harms cooperatives, but can also disrupt the financial stability of cooperative members. The lack of effective tools to measure and predict credit risk makes cooperatives potentially face unnecessary losses. The aim of this research is to apply the C4.5, SVM, and KNN algorithms in determining the average non-performing loans of savings and loan cooperatives, comparing the results and performance of the three such algorithms in the context of credit risk management, and improve understanding of the use of machine learning techniques in identifying credit risk patterns that may be difficult to detect manually. The application of the C4.5 Algorithm, SVM (Support Vector Machine), and KNN (K-Nearest Neighbors) models in determining the average bad credit in the context of savings and credit cooperatives is carried out by considering the appropriate configuration. This research first collects and preprocesses data which includes credit history, income, length of membership, and other related factors from savings and loan cooperatives. Next, factor analysis and feature selection are carried out to identify the factors that most influence credit risk. The results of the three models are evaluated using various evaluation metrics, such as accuracy, precision, recall, F1-score, and AUC-ROC. The results of this research The results show that the SVM model has the highest performance in predicting credit risk, followed by the C4.5 and KNN algorithms. Careful feature selection and robust model validation are also key components in accurate credit risk assessment. Thus, the results of this research can help cooperatives better manage credit risk and make more informed decisions regarding loan approvals.
Pemberdayaan Warga RW12 Kelurahan Larangan Utara Penggunaan Aplikasi Monitoring Dan Kendali Banjir Siswanto; Windu Gata; Riefky Sungkar; Muhammad Anif; Ari Saputro; Grace Gata; Subandi; Yuliazmi; Hari Prasetyo, Basuki
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 3 No 2 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v3i2.4639

Abstract

Community service (PKM) is carried out in the Tangerang area, precisely in the Puri Beta 1 RW 12 Cluster Flamboyan housing. Puri Beta housing consists of three areas, namely Puri Beta Utara, Puri Beta 1, and Puri Beta 2. Housing Puri Beta 1 has many clusters with the condition of the area being traversed starting from the Pine cluster to the Flamboyan cluster, often when heavy rains occur. become a flood prone area. Every year with the rainy season ranging from October to February are the months that need to be observed. In anticipation of this incident, flood control is needed that can provide information on the level of water levels that pass through this cluster, as an early warning so that residents will be alert in the event of a flood. This activity is divided into 3 (three) stages of implementation, namely preparation, implementation, and evaluation. This PKM has been carried out from March 18, 2019 to July 18, 2019, which was carried out offline. In the UAT test, a questionnaire with a Likert scale scale of 5. was used. As a result, the respondents agreed (above 83.3%) that the overall empowerment training for RW12 residents of Larangan Utara Village using flood monitoring and control applications was interesting and understandable.
Pemberdayaan Calon Instruktur Dalam Memahami Materi Skema Operator Komputer Madya Siswanto; Riefky Sungkar; Muhammad Anif; Ari Saputro; Subandi; Hari Prasetyo, Basuki
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 4 No 1 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v4i1.5179

Abstract

Pengabdian kepada masyarakat (PKM) dilakukan di Balai Pelatihan & Pengembangan Teknologi Informasi & Komunikasi (BPPTIK) Cikarang Kabupaten Bekasi Jawa Barat. BPPTIK mempunyai tugas melaksanakan pelatihan, uji kompetensi, sertifikasi dan akreditasi lembaga pelatihan pemerintah, serta pelayanan produk jasa di bidang teknologi Informasi dan Komunikasi. Selama ini permasalahan mitra PKM adalah: instruktur-instruktur yang tergabung dalam BPPTIK belum memiliki tenaga pelatih untuk memberikan pengetahuan, skill dan sikap materi skema operator komputer madya yang berbasis SKKNI. Tujuan dari pelatihan ini adalah memberikan pelatihan komputer meliputi: pengetahuan, skill dan sikap materi skema operator komputer madya yang berbasis SKKNI kepada calon instruktur yang tergabung dalam BPPTIK Cikarang Kabupaten Bekasi Jawa Barat, sehingga instruktur-instruktur dapat menyampaikan dekripsi, kurikulum, silabus, bahan ajar dan modul materi skema operator komputer madya yang menyenangkan, menarik, lebih interaktif dan tidak membosankan bagi siswa yang dididik dengan perangkat multimedia. Kegiatan ini untuk calon instruktur operator komputer madya yang tergabung dalam BPPTIK Cikarang. Adapun puncak dari kegiatan PKM ini adalah pengembangan materi skema operator komputer madya berupa nara sumber teknologi informasi dan master of trainer untuk pelatihan materi skema operator komputer madya yang telah dilaksanakan dari tanggal 12 Desember 2023 sampai dengan 16 Desember 2023, yang dilakukan secara offline dengan mempertimbangkan kondisi keamanan dan kesehatan akibat pandemi Covid-19. Pada pengujian UAT, telah digunakan kuesioner dengan likert scale skala 5. Hasilnya, para responden setuju (di atas 81.4%) bahwa secara keseluruhan pelatihan materi skema operator komputer madya yang berbasis SKKNI buat calon instruktur operator komputer yang tergabung dalam BPPTIK Cikarang menarik dan paham.
Pemberdayaan Calon Instruktur Dalam Memahami Materi Skema Associate Data Scientist Siswanto; Riefky Sungkar; Muhammad Anif; Ari Saputro; Subandi; Djati Kusdiarto; Wahyu Pramusinto; Hari Prasetyo, Basuki
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 4 No 2 (2023): Desember 2023
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v4i2.5580

Abstract

At the Information & Communication Technology Training & Development Center (BPPTIK) Cikarang, Bekasi Regency, West Java, community service (PKM) was performed. BPPTIK is responsible for conducting competency assessments, certifying and accrediting government training facilities, and providing information and communication technology product services. The current issues facing PKM partners are as follows: teachers who are part of BPPTIK are now lacking in trainers to impart associate data scientist scheme material based on SKKNI, which includes knowledge, abilities, and attitudes. The goal of this training is to prepare aspiring instructors who are BPPTIK Cikarang members with the knowledge, abilities, and attitudes of the SKKNI-based associate data scientist scheme material so that instructors can deliver descriptions, curriculum, syllabus, teaching materials, and modules. In the UAT test, a questionnaire with a Likert scale of 5 has been used. As a result, the respondents agreed (above 79.24%) that overall the SKKNI-based associate data scientist scheme material training is interesting and understood by prospective associate data scientist instructors who are members of BPPTIK Cikarang.
Co-Authors Ari Saputro Basuki Hari Prasetyo Buana Suhurdin Putra Djati Kusdiarto Gata, Windu Grace Gata, Grace Gunawan Pria Utama Hari Prasetyo, Basuki Ida Ayu Putu Sri Widnyani M.Anif Muhammad Anif Raden Sutiadi S Siswanto Siswanto Subandi Subandi Wahyu Pramusinto Yuliazmi, Yuliazmi