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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmu Teknik dan Komputer Journal Collabits
Lukman Hakim
Universitas Mercu Buana
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Rice Distribution Clustering for Decision Support in Jakarta Suhendra Suhendra; Lukman Hakim; Fandi Ali Mustika
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 14 No. 1 (2026): March 2026
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v14i1.12245

Abstract

Rice distribution stability plays a strategic role in ensuring urban food security, particularly in metropolitan regions such as Jakarta where supply-demand dynamics are highly complex. This study aims to develop an integrated clustering-based decision support framework to classify regional rice distribution conditions and enhance adaptive allocation strategies. Monthly rice availability and demand data from 2021–2023 across seven administrative regions in Jakarta were analyzed using the K-Means clustering algorithm. Optimal cluster determination employed the Elbow and Silhouette methods. Cluster validation was conducted using Silhouette, Davies–Bouldin, and Calinski–Harabasz indices. A comparative analysis with Hierarchical Clustering (Ward linkage) was also performed. The clustering results were integrated into a Business Intelligence dashboard. Three optimal clusters were identified, representing high-surplus, moderate-surplus, and deficit conditions. K-Means demonstrated superior cluster compactness and separation quality compared to Hierarchical Clustering, with a Silhouette score of 0.62 and a Davies–Bouldin index of 0.41. The proposed framework improves operational transparency and supports evidence-based redistribution policies. This approach also contributes to strengthening adaptive food security management in metropolitan areas.
ANALISIS FAKTOR YANG MEMPENGARUHI PEMILIHAN GUBERNUR DAERAH KHUSUS JAKARTA MENGGUNAKAN ALGORITMA NAIVE BAYES DAN REGRESI LOGISTIK Yoga Nanda Khoiril Umat; Dhiaz Rusyda Nafsyi; Diana Kusumaningsih; Lukman Hakim
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 9 No 2 (2024): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v9i2.4778

Abstract

The election of the Governor and Deputy Governor of the Special Region of Jakarta (DKJ) in 2024 involves the community in determining leaders for the 2024-2029 period. This research analyzes the factors influencing voter decisions using the Naive Bayes algorithm and Logistic Regression. Survey data was collected via a Google Form questionnaire from Jakarta residents aged 17-71. The analysis process involves several stages: problem identification, literature study, data collection, preprocessing, and dividing the data into training and test data. The Naive Bayes algorithm is used to predict classification parameters based on a candidate's education, popularity, and track record, while Logistic Regression predicts factors that influence voter decisions. Naive Bayes shows high accuracy with advantages in speed and processing large data, while Logistic Regression shows strength in binary and multinomial classification analysis. The research results show that the track record factor significantly influences voter decisions. Naive Bayes prediction accuracy reached 85.00% and Logistic Regression 80.00%. The analysis results also reveal that the candidate's popularity and education factors rationally influence voter decisions, although not as strong as the track record. In addition, using these two algorithms provides a comprehensive understanding of voter behavior in Jakarta. Based on these results, governor and deputy governor candidates should also focus on improving their track record and popularity to increase their chances of being elected.
Sistem Kendali Kelembaban Dan Suhu Pada Jamur Berbasis Machine Learning Menggunakan Logika Fuzzy Sugeno Indriyana Nova Tahlia; Nabil Raihan Rabbani; Lukman Hakim
Jurnal Ilmu Teknik dan Komputer Vol. 9 No. 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jitkom.v9i1.004

Abstract

Mempertahankan kondisi ideal untuk pertumbuhan tanaman memerlukan pemantauan kelembaban dan suhu tanah. Untuk menentukan tingkat kelembaban dan suhu yang optimal, sistem kontrol sangat penting. Sistem kendali ini memanfaatkan data dari Jamur Tiram sebagai masukan untuk menghasilkan keluaran yang diinginkan. Dengan menggunakan logika fuzzy sebagai program pengambilan keputusan, sistem ini mengatur tingkat kelembaban dan suhu yang paling sesuai untuk Jamur Tiram. Logika fuzzy terbukti menjadi pendekatan yang efektif dalam sistem kendali, yang melibatkan proses fuzzifikasi, pembentukan aturan fuzzy, dan defuzzifikasi. Dalam sistem logika fuzzy khusus ini, dua input (tingkat kelembaban dan suhu) digunakan, sehingga menghasilkan penentuan waktu yang diperlukan untuk mempertahankan tingkat kelembaban dan suhu yang sesuai untuk Jamur Tiram.
Implementation Analytical Hierarchy Process Method to Improve the Effectiveness of Social Assistance Distribution Yunita Sartika Sari; Lukman Hakim
Journal Collabits Vol. 1 No. 1 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i1.25490

Abstract

Based on the report of the central statistics agency, the number of poor people in Indonesia reached 26.16 million people. The government has made efforts to provide assistance to overcome this problem, one of which is beneficiaries. The distribution of beneficiaries which is being held is still not optimal because of the uneven distribution of aid to underprivileged communities. The purpose of this research is to implement a Decision Support System (DSS) to determine the right community to receive beneficiaries which will be given based on several criteria used, namely: education, employment, and place of residence. In this study, proposes to build a model that has a decision-making concept. The method used in this Decision Support System is the Analytical Hierarchy Process (AHP). The expected results in this study are a decision support system that can assist in determining beneficiaries.
Co-Authors Dhiaz Rusyda Nafsyi Diana Kusumaningsih Fandi Ali Mustika Indriyana Nova Tahlia Nabil Raihan Rabbani Sari, Yunita Sartika Suhendra Suhendra Yoga Nanda Khoiril Umat