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Program Studi Informatika, Fakultas Teknik, Universitas Janabadra. Jalan Tentara Rakyat Mataram No. 55-57, Yogyakarta 55231
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INDONESIA
Informasi interaktif : jurnal informatika dan teknologi informasi
Published by Universitas Janabadra
ISSN : 25275232     EISSN : 25275240     DOI : 10.37159/jii
Core Subject : Science,
Computer Science & IT
Jurnal Informasi Interaktif membahas topik-topik yang secara umum berkaitan dengan isu-isu Hukum di Indonesia dan di seluruh dunia. Artikel yang dikirimkan mungkin mencakup isu-isu topikal di Kecerdasan Buatan Jaringan Saraf Tiruan Algoritma Genetik Grafika Komputer Sistem Pakar Wireless and Mobile Technology Remote Sensing Image and Signal Processing Multimedia Teknologi Web Data Center Distributed System Middleware Arsitektur Komputer Sistem Operasi Rekayasa Perangkat Lunak Sistem Informasi Sistem Informasi Geografi Optimasi dan Teknologi Basis Data Interaksi Manusia dan Komputer Data Mining Kriptografi Keamanan Teknologi Informasi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 74 Documents
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ANALISIS RISIKO SISTEM MANAJEMEN RANTAI PASOK MAMMA ROTI BERDASARKAN ISO 31000 Pankrasius Aryo Wicaksono; Putra Arianto; Mirza Rabbani Kobandaha; Luthfi Jatmiko Nugroho; Ayasha Zahwa; Erly Krisnanik
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 11 No 1 (2026): Bahasa Indonesia
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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Abstract

The Food & Beverages (F&B) industry in Indonesia faces complex challenges in managing supply chain operational risks, particularly for rapidly growing franchise companies like Mamma Roti established since 2021. This research aims to identify and analyze operational risks using the ISO 31000:2018 framework as a structured risk management standard. Descriptive qualitative method was applied through direct observation and semi-structured interviews, with analysis following stages of context establishment, identification, likelihood-impact matrix analysis, acceptance criteria evaluation, and risk treatment procedures. Research results identified twelve operational risks (R1-R12) with most at moderate levels, while two risks (R5 and R11) obtained critical scores of 9 related to continuous improvement mechanisms. Recommendations include implementing measurable action trackers, Service Level Agreements (SLA), concise Standard Operating Procedures (SOP), and Business Continuity Plan (BCP) and Disaster Recovery Plan (DRP) with Recovery Time Objective (RTO) of 2-24 hours. Mitigation strategies are expected to reduce risks within 1-3 months and enhance Mamma Roti's operational resilience.
PREDIKSI PREDIKSI TIMBULAN SAMPAH RUMAH TANGGA DI KOTA BEKASI MENGGUNAKAN RANDOM FOREST DALAM PERENCANAAN PRODUKSI KOMPOS Widiyasih, Amelia; Salsabila, Ghina; Mumtazah, Aida; Chrisnawati, Giatika
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 11 No 1 (2026): Bahasa Indonesia
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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Abstract

The rapid population growth and urban activity have caused a continuous increase in household waste generation. Bekasi City is one of the major contributors, with a significant amount of organic household waste requiring a sustainable management strategy. This research proposes a Machine Learning approach based on the Random Forest algorithm to predict household waste generation for compost production planning. The dataset includes demographic variables and annual waste records from 2022 to 2024. The method consists of preprocessing, data splitting, and model evaluation stages. Results show that the model achieved an MAE of 1111.70, RMSE of 1549.57, and an R² value of 0.95, indicating strong predictive capability. The model was then used to calculate household waste prediction for 2025 to 2030, showing an increasing trend. Additionally, the projection enabled the estimation of compost production potential based on an assumption that 70% of total waste is organic and 50% of it can be processed into compost. This research confirms that Machine Learning and Artificial Intelligence approaches can support local waste management policy and long-term sustainability planning.
ANALISIS PENGGUNAAN APLIKASI LINKEDIN DALAM MEMBANGUN PERSONAL BRANDING PADA MAHASISWA UNIVERSITAS NEGERI GORONTALO MENGGUNAKAN MODEL UTAUT Lantu, Zulvikry Andre; Kusuma, Ma'rifatul Sasmitha; Ts. Bullah, Ilham; Amali, Lanto Ningrayati
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 11 No 1 (2026): Bahasa Indonesia
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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Abstract

Personal branding is an important element for students in shaping their professional image and preparing themselves for the world of work. As a professional social networking platform, LinkedIn offers various features that can support the formation of a professional identity, but its utilization by students is still not optimal. This study aims to examine the strength of the relationship between variables in the UTAUT model and the behavior of using LinkedIn as a means of personal branding among students at Gorontalo State University. Using a quantitative descriptive approach, data was collected through a questionnaire (gfrom) distributed to 80 students who actively use LinkedIn. The analysis was conducted using the PLS-SEM tool with the SmartPLS version 4 application. The results show that Social Influence and Performance Expectancy have an influence on Behavioral Intention with a t-statistic > 1.990 and a p-value < 0.05, while Effort Expectancy does not show a significant influence because the results do not meet the criteria. In addition, Facilitating Condition and Behavioral Intention also had an effect on Use Behavior. UTAUT in this study was able to explain 59.3% of the variance in Behavioral Intention and 58.4% of the variance in Use Behavior. These findings indicate that perceived benefits and environmental support have a stronger influence than ease of use in encouraging students to use LinkedIn.
SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI PENERIMAAN PEGAWAI BARU MENGGUNAKAN METODE KNN DAN WEIGHTED PRODUCT Febriani, Siska
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 11 No 1 (2026): Bahasa Indonesia
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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Abstract

  Searching for prospective employees is quite an important thing in the company because every job done by employees will affect the stability of the company. In the recruitment of employees, the quality of prospective applicants is already convincing, but the salary he submits is not in accordance with the ability of the company, or the prospective applicants do not match the criteria that the company is looking for. This mismatch will certainly slow down the company to find the best staff. The results of this study are to provide recommendations for the best employees who understand some of the criteria set by the system using the k-nearest neighbor (KNN) method and weighted product (WP). The parameters used to obtain wisdom are using GPA values, academic values, science and technology values and interview scores. The data that will appear at the conclusion is the ranking of the participants, the type of classification and recommendations chosen by the company. With these data, the company can determine the next policy that can be taken. The results of the accuracy obtained are 87% with a value of k = 3.

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