The University of Timor (Indonesian: Universitas Timor, abbreviated Unimor) is an Indonesian public university in the island of Timor, in the town of Kefamenanu which is part of the North Central Timor Regency. As a public university, Unimor accepts students partially through the SNMPTN system administered nationwide. It is one of the two public universities on the Indonesian part of the island, the other being the University of Nusa Cendana.Following the independence of East Timor and exodus of Indonesian nationals (many to Kefamenanu), the teaching staff formerly from Universitas Timor Timur established the university in 2000 on a 40-hectare plot of land donated by the local council and a Rp 2 billion funding from the central government. Initially a private university, it attempted to be nationalized starting around 2010 and after several rejections, was officially made a public university in 2014.Located 7 hours away from the provincial capital of Kupang, the university is close to the border with East Timor and hence receive some students from across the border. In 2017, it claimed that 6,000 East Timorese students had studied at Unimor. As comparison, there were 5,000 active students in the same year with an intake of 1,500. It was classified as part of the fourth cluster - the lowest tier - among other higher education institutes in Indonesia as of 2017..
Depression is increasingly experienced by final-year university students due to academic pressure, with symptoms such as prolonged sadness, loss of motivation, sleep disturbances, and difficulty concentrating. Early detection remains limited because of restricted access to mental health professionals and the high cost of consultations. This study aims to develop an Android-based expert system for diagnosing depression levels using the Certainty Factor (CF) method. The research employed the Research and Development (R&D) method with the Rapid Application Development (RAD) model, which consists of requirements planning, design, construction, and implementation stages. The system utilizes 15 symptoms and classifies four levels of depression: mood disorder, mild depression, moderate depression, and severe depression. The evaluation was conducted on 20 respondents by comparing the system’s diagnostic results with expert analysis. The evaluation results showed that 17 out of 20 system diagnoses were consistent with the expert’s analysis, resulting in an accuracy rate of 85%. An example of the calculation process using the CF method produced a diagnostic value of 0.95 (95%), which falls into the severe depression category. The developed system is capable of supporting early detection of depression in a faster, more practical, and easily accessible manner through Android devices, and it can serve as an initial consultation tool for final-year students. The system can assist early detection more efficiently and with greater accessibility.
Delays in the early diagnosis of rabies remains a significant issue due to the limited of public knowledge in recognizing the symptoms of the disease, resulting in delayed medical treatment. This study aims to develop a web-based expert system designed to assist in the early diagnosis of rabies in humans using the Certainty Factor (CF) method. This method is used to calculate the confidence level of the diagnosis based on the symptoms selected by the user. The system knowledge base was obtained through expert interviews and literature studies, which were represented in the form of diagnostic rules. The system is capable of providing rabies diagnosis results along with their corresponding confidence values based on the symptoms entered by users. Functional testing using the Black Box Testing method showed that all system features functioned properly. In addition, system validation was carried out by comparing the system diagnosis results with expert diagnoses through 30 testing scenarios using different symptom combinations. The test results showed 27 matching data and 3 non-matching data, resulting in a system accuracy rate of 90%. This research contributes to the implementation of the CF method in a web-based expert system to support early rabies diagnosis in a fast and measurable manner.
Purpose –This study aimed to develop and examine the validity and reliability of pedagogical adaptability and contextual digital learning development instruments for senior high school teachers in the NKRI-RDTL border area. Methodology – This study employed a quantitative approach using an instrument development research design. The study involved 64 senior high school teachers and four expert validators. Instrument development was carried out through the stages of theoretical construct development, indicator and item blueprint formulation, expert validation, instrument revision, field testing and validity and reliability analysis. Content validity was analyzed using Aiken’s V, empirical validity was analyzed using Pearson Product-Moment correlation, and instrument reliability was analyzed using Cronbach’s Alpha. Findings – The findings showed that the developed instruments had high content validity, with Aiken’s V values ranging from 0.88 to 1.00. The empirical validity test showed that most statement items were valid, while the reliability of both instruments was categorized as high to very high. These findings indicate that the developed instruments are appropriate for measuring pedagogical adaptability and contextual digital learning development in border areas. Contribution – The novelty of this study lies in the development of instruments designed based on the characteristics of learning in border areas, particularly in relation to the demands of adaptive and contextual digital learning. The developed instruments can be used as assessment tools to map teachers’ personal capacities more accurately and to support teacher competency development programs in border areas.
Learning innovation is an effort that needs to be undertaken by teachers. This study was conducted to describe high school teachers’ perceptions of learning innovation in the Indonesia–Timor-Leste border region. This study employed a quantitative descriptive approach involving 90 high school teachers in Timor Tengah Utara Regency. Data were collected using a questionnaire on teachers’ perceptions of learning innovation. The collected data were analyzed using descriptive statistics. The results showed that high school teachers’ perceptions of learning innovation in the Indonesia–Timor-Leste border region were in the Fair category, with a mean score of 70.73. Most teachers, namely 83.33%, had perceptions in the Poor and Fair categories, while only 14.44% of teachers had perceptions in the Good and Excellent categories. These findings indicate the need to strengthen teachers’ perceptions of learning innovation and provide an empirical basis for developing contextual learning innovation guidelines to help teachers create learning that is creative, adaptive, and appropriate to local conditions.
India is the world’s largest importer of palm oil, with a significant share sourced from ASEAN-3 countries—Indonesia, Malaysia, and Thailand. The ASEAN-India Free Trade Agreement (AIFTA), implemented in 2010, aimed to strengthen trade ties by reducing tariffs on palm oil. However, previous studies have produced mixed results regarding AIFTA’s effectiveness, highlighting the need for further analysis. This study examined the impact of AIFTA on the palm oil export performance of ASEAN-3 countries by evaluating their competitiveness in the Indian market using Revealed Comparative Advantage (RCA), Export Product Dynamics (EPD), and Ordinary Least Squares (OLS) gravity models. Utilizing secondary data from 2007 to 2021 sourced from UN Comtrade, the World Bank, and CEPII, the study assessed competitiveness, identified export trends, and explored trade creation and diversion effects. Findings from the RCA and EPD analyses indicate declining competitiveness for Indonesia and Malaysia, while Thailand shows notable improvement. Despite tariff concessions under AIFTA, the gravity model reveals no significant trade creation effect, suggesting that non-tariff factors—such as India’s domestic production policies, export duties, and geographic proximity—play a more influential role. The study concludes that AIFTA’s impact on the palm oil trade remains limited. To enhance export performance, ASEAN-3 countries must pursue product diversification, sustainability initiatives, and strategic trade reforms. These insights offer valuable guidance for policymakers aiming to optimize FTA outcomes and navigate evolving market dynamics.
