Jaya, Edo Sebastian
Fakultas Psikologi, Universitas Indonesia

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

Properti psikometris Big Five Inventory–2 versi Indonesia Firdhan Achmadan; Edo Sebastian Jaya; Sali Rahadi Asih
Jurnal Psikologi Sosial Vol 20 No 2 (2022): August
Publisher : Fakultas Psikologi Universitas Indonesia dan Ikatan Psikologi Sosial-HIMPSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7454/jps.2022.15

Abstract

The five personality traits are currently seen as the most widely used theoretical framework in explaining the variability of human behavior. Big Five Inventory (BFI) is one of the well-known inventories that contributes to the progress of the big five research. Recently, the developer updated and published the Big Five Inventory-2 (BFI-2). Various studies have been conducted to expand the scope of validation, but until now the testing has not been carried out involving Indonesian participants. The purpose of this study was to evaluate the psychometric properties of the BFI-2 in the Indonesian version. The researcher corresponds with the developer to obtain BFI-2 which has been officially translated by the International Situations Project (ISP). Data were collected by distributing online surveys through various social media platforms. A total of 1061 participants were involved in this study. The result showed adequate internal consistency on the domain level and somewhat lower on the facet level. The BFI-2 domains and facets also showed good convergent-discriminant validity in relation to IPIP-BFM-50 and TIPI. The factor analysis shows that the model fits the data after seven problematic items were not included in the analysis. Therefore, we concluded that the questionnaire could be used to measure the Big Five personality traits in Indonesia provided the problematic items found to be invalid are deleted.
Survei Longitudinal Indonesia tentang Kesehatan Mental dan Faktor Sosial (INDOLUMEN): Hasil Awal dan Protokol Edo Sebastian Jaya; Eko Hermanto; Shabrina Audinia; Shierlen Octavia; Salima Carter; Fadhilah Ramadhannisa
INSAN Jurnal Psikologi dan Kesehatan Mental Vol 7 No 1 (2022): INSAN Jurnal Psikologi dan Kesehatan Mental
Publisher : Airlangga University Press, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jpkm.v7i12022.1-35

Abstract

While many known risk factors and mechanisms for psychosis exist, the time it takes for these risk factors and mechanisms to influence psychosis remains unclear. Furthermore, the average duration of a psychotic symptom has not been estimated. The aim of the study is to discover the average duration of an episode of psychotic symptoms and other mental disorders, as well as the average duration by which psychological mechanisms of risk factors and psychotic symptoms or other mental disorders operate. This study is an online longitudinal survey with various time-interval assessments (baseline, 7 daily, 4 weekly, 4 fortnightly, and 6 monthly assessments). A community sample of Indonesians were recruited via internet and a sample of help-seekers were recruited from clinical practices. From November 2018 to March 2019, we recruited 464 participants who completed the baseline survey from the community. Of the 464 participants, 73% of them are female with ages ranging from 18 - 57 years and 33.2% reported having been diagnosed with at least one mental disorder. The expected results of the surveys provide us with estimates regarding appropriate time-intervals of risk factors and mechanisms of psychosis.
Editorial Note: Makara Human Behavior Studies in Asia’s Responds to Political Challenges in Scientific Publication Jaya, Edo S.; Sekarasih, Laras; Shadiqi, Muhammad Abdan; Riantoputra, Corina D. S.
Makara Human Behavior Studies in Asia Vol. 26, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Three challenges of political nature were identified in 2022: increasing number of institutions in many countries in Asia to require journal article publication for graduation of an academic degree, changes in Journal Citation Index (JCITM) policy, and a retraction case in Journal of Cross-Cultural Psychology. As a response to these challenges, Makara Human Behavior Studies in Asia made several changes. First, we now publish incrementally to accommodate the requirement to publish in time. In Indonesia, as well as in many parts of Asia, publications in journals are increasingly used to satisfy administrative requirements. We have received requests for faster publication due to graduation requirements from authors from Indonesia, Malaysia, and Pakistan. The importance of journal publication is increasing in the region. Second, the everchanging scientific landscape triggers a response from Clarivate Analytics that decided to include Journal Impact Factor (JIFTM) in the subsequent publication of the Journal Citation Reports (JCRTM) in 2023.
Editorial Note: A Long-term Endeavor of Citations in the Global South Open Access Journals Sekarasih, Laras; Jaya, Edo S.; Shadiqi, Muhammad Abdan
Makara Human Behavior Studies in Asia Vol. 27, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Citations have become a “currency” of research quality. If the number of papers published is a parameter of scholars’ productivity, the number of citations received by each paper serves as an indicator of the quality of the research. The number of citations is often used to assess the quality of an article. In this bibliometric measure, papers that attract citations are considered to have a meaningful contribution. A high number of citations, especially when they come immediately after the papers are published, indicates that the paper is well accepted by scholars in the field and contributes to the advancement of science.
Psychometric Properties and Use of the Indonesian Florida Obsessive-Compulsive Inventory Ticoalu, Christiana L.; Mar'at, Samsunuwijati; Suyasa, P. Tommy Y. S.; Storch, Eric A.; Goodman, Wayne K.; Hartanto, Steffi; Novrianto, Riangga; Jaya, Edo S.
Makara Human Behavior Studies in Asia Vol. 28, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Presently, in Indonesia, the lack of a validated measure for obsessive–compulsive disorder (OCD) hinders diagnosis and treatment of the disease. The current study evaluated the reliability, validity, and optimal cut-off score of the Indonesian Florida Obsessive-Compulsive Inventory (FOCI) in predicting OCD presence. The participants included 384 adults: 157 with OCD, 80 case controls with anxiety or mood disorders, and 147 healthy controls. Assessments were conducted using FOCI, Obsessive-Compulsive Inventory-Revised, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7. Test–retest reliability of the FOCI was evaluated for over 2 weeks in 30 OCD patients. The internal consistency within OCD samples for the FOCI Symptom Checklist and Severity Scale was strong (Kuder–Richardson 20, KR-20 = 0.86; Cronbach’s alpha, α = 0.86), as well as the test–retest reliability (intraclass correlation coefficient [ICC] = 0.98 [95% CI: 0.95, 0.99] and ICC = 0.73 [95% CI: 0.49, 0.86], respectively). Convergent and discriminant validity were moderate to strong. Confirmatory Factor Analysis revealed a unidimensional factorial structure for the FOCI Severity Scale. A cut-off score of ≥5 predicted OCD with a sensitivity of 85% and specificity of 65%. Results support the use of Indonesian FOCI in screening and assessing OCD in Indonesian samples.
Editorial Note: GenAI for Academic Writing – Friend or Foe? Riantoputra, Corina D.; Wongkaren, Turro S.; Jaya, Edo S.; Sekarasih, Laras; Shadiqi, Muhammad Abdan
Makara Human Behavior Studies in Asia Vol. 30, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In an article published in Nature titled “ChatGPT listed as author in research papers” Stone-Walker (2023) shocks the academic community with the fact that GenAI tools such as ChatGPT and Gemini have gained a substantive role in the production of knowledge and academic writing. He reports that one research company has published 80 articles produced by GenAI in academic journals.  In the wake of Stone-Walker’s article, many publishers and journal editors set guidelines in relations to the role of GenAI in academic writings. All of them disagree to allow GenAI as an author.  Further, the Stanford University Artificial Intelligence Index (2022) reports that there is a fivefold increase in research and publications on fairness and transparency relating to GenAI since 2014 indicating that the ethical issue is even more pressing now. Altogether, such development demonstrates that the academic community is feeling uneasy, disturbed, and anxious on the use of GenAI in the academic endeavour. Although everyone agrees on the practical assistance GenAI provides in academic writing, GenAI also brings epistemic challenges and accompanying integrity risks (Chesterman & Chieh, 2026). As a journal concerned with human behavior and socio-cultural processes in Asia, Makara Human Behavior Studies in Asia has a particular stake in addressing this issue as we take active roles in preserving academic authority related to journal publications. It is the aim of this editorial note to discuss principles in relation to how GenAI may be used in manuscripts submitted to this journal without sacrificing academic integrity. This editorial note does not yet introduce formal rules or technical instructions. Instead, it articulates the principles that will guide subsequent editorial policies. For this editorial note, GenAI refers to the term generative AI, which are computational techniques that are capable of generating seemingly new and meaningful content such as text, images, or audio from training data. (Feuerriegel et al., 2024). This can be used to perform tasks such as pattern recognition, prediction, generation, and optimization across research workflows.