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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Indonesian Journal of Electrical Engineering and Computer Science Buletin Poltanesa
Teddy Mantoro
Nusa Putra University
Agriculture, Biological Sciences & Forestry Computer Science & IT Education

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User-Centric Waste Management Through Reward-Based Digital Systems Ama Muzni Mahmudi; Teddy Mantoro
Poltanesa Vol 26 No 1 (2025): June 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v26i1.3380

Abstract

The effective management of household and urban waste is a critical challenge in achieving sustainability within the fields of waste management and circular economy practices. Traditional waste sorting systems face inefficiencies due to low user participation, limited accountability, and inadequate transparency in tracking and reporting waste contributions. This research addresses these challenges by introducing a reward-based digital platform that incentivizes users to sort and deposit waste at designated collection points. The platform assigns points based on the type and quantity of waste submitted, tracks contributions, and provides detailed reports to users, fostering transparency and trust. The proposed solution demonstrates potential to increase user engagement, improve waste sorting accuracy, and enhance reporting capabilities, supporting the transition toward sustainable and circular waste management systems.
ENHANCING COFFEE PRODUCTION FACTOR ASSESSMENT USING LINEAR REGRESSION AND AHP FOR RELIABLE WEIGHT CONSISTENCY Aris Gunaryati; Teddy Mantoro; Septi Andryana; Benrahman; Mohammad Iwan Wahyuddin
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6788

Abstract

The agricultural sector, particularly coffee production, plays a crucial role in Indonesia’s economy as both a domestic commodity and an export product. However, efforts to optimize coffee production are often constrained by traditional Multi-Criteria Decision-Making (MCDM) methods that rely heavily on subjective judgments, leading to potential inconsistencies—especially in the presence of multicollinearity among variables. This study addresses that challenge by proposing a data-driven and consistent weighting method that integrates Multiple Linear Regression (MLR) with the Analytic Hierarchy Process (AHP). Regression coefficients derived from MLR—based on variables such as the area of immature (-0.2419), mature (0.8357), and damaged (0.5119) coffee plantations—are normalized and incorporated into the AHP pairwise comparison matrix. The resulting Consistency Ratio (CR) values are all below 0.1, indicating high internal consistency and statistical reliability of the derived weights. This integrated approach offers an objective and systematic foundation for MCDM in coffee production analysis, enhances the accuracy of agricultural planning, and supports evidence-based policymaking, while also providing a replicable model for addressing similar challenges in other sectors
Improving the performance of wireless sensor network using multi-hopping clustering partition Robby Rizky; Mustafid Mustafid; Teddy Mantoro; Wahyul Amien Syafei
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 1: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i1.pp81-92

Abstract

Wireless sensor networks (WSNs) enable large-scale event monitoring; however, their performance is often constrained by low throughput. This study aims to develop a cluster-based routing protocol by implementing the multi-hopping clustering partition (MHCP) method. The MHCP process consists of three main stages: (i) cluster head (CH) selection, (ii) evaluation of node proximity to their respective CHs, and (iii) cluster partitioning to reduce intra-cluster variation. Four clusters were formed and interconnected through multi-hop communication, achieving throughput values of 142.0033, 244.1318, 119.0804, and 305.6159, respectively. In addition to the development of MHCP, the scientific contribution of this study is strengthened through the integration of the LEACH protocol and the K-means algorithm as a complementary methodological approach. LEACH improves energy efficiency through adaptive CH rotation, while K-means optimizes spatial node grouping. The combination of these methods ensures a balance between energy consumption and spatial proximity, resulting in improved throughput and extended network lifetime. Experimental results demonstrate that the proposed MHCP protocol achieves higher throughput than the conventional LEACH protocol across all clusters while maintaining acceptable delay and packet loss. These findings confirm that the integration of multi-hop communication and cluster partitioning effectively enhances data transmission efficiency and overall network performance in WSNs.
Co-Authors Ama Muzni Mahmudi Aris Gunaryati Benrahman Mohammad Iwan Wahyuddin Mustafid Mustafid Robby Rizky Septi Andryana Wahyul Amien Syafei